The Third International Self-report Study of Delinquency among

Transcription

The Third International Self-report Study of Delinquency
among Juveniles in Switzerland and in Indonesia
Report to the Swiss National Science Foundation
(Project 100015_138401/1)
on the Survey conducted in Switzerland
by
Martin Killias & Anastasiia Monnet Lukash
University of St. Gallen
Forschungsgemeinschaft Rechtswissenschaft
Tigerbergstrasse 21
CH-9000 St. Gallen
[email protected]
[email protected]
1st September 2015
Index
Page
Chapter 0. Introduction
01. Background
6
02. The Swiss Report
6
03. Fieldwork in Switzerland
7
04. Acknowledgements
7
05. Abbreviations
9
Chapter 1. Juvenile Delinquency in Switzerland: An Overview
1.1. What this Chapter is about
10
1.2. Social background variables
1.2.1
Gender and age in our samples
1.2.2
Birthplace
1.2.3
Family constellations
1.2.4
Religion
1.2.5
Employment and economic wellbeing
1.2.6
Changes between 2006 and 2013
10
10
11
14
14
16
19
1.3 Association between social background and delinquency
1.3.1
Gender, age and delinquency
1.3.2
Birthplace and delinquency
1.3.3
Family constellation and delinquency
1.3.4
Religion and delinquency
1.3.5
Economic status and delinquency
24
24
25
32
33
35
1.4 Comparison between ISRD-2 and ISRD-3
1.4.1
Trends in delinquency
1.4.2
Demographic characteristics and delinquency
1.4.3
Economic status and delinquency in 2006 vs. 2013
38
38
38
40
1
1.5 Victimization and demographic background
1.5.1
Gender and age
1.5.2
Birthplace and victimization
1.5.3
Different family configurations and delinquency
1.5.4
Social standing and economic well-being
42
42
44
48
49
1.6 Conclusions: Factors of delinquency and victimization
53
Chapter 2. Family, parental control and delinquency
2.1 Overview
54
2.2 Family life and parental control across regions
2.2.1
Dinner with family
2.2.2
Parental control
54
54
56
2.3 Family life, parental control and delinquency
2.3.1
Family life and delinquency
2.3.2
Parental control and delinquency
61
61
62
2.4 Conclusions
69
Chapter 3. Attitudes towards and perceptions about the school, school
performance and delinquency
2.1 Overview
70
2.2 Descriptive Statistics
2.2.1
Feelings about school
2.2.2
Perceptions about the school environment
2.2.3
Performance at school and truancy
71
71
75
77
3.3 Association between school-related variables and delinquency
3.3.1
Attitudes towards school and delinquency
3.3.2
Problems in the school environment and delinquency
82
82
86
3.4 Main findings and discussion
90
Chapter 4. Victimization
2
4.1 Overview
92
4.2.1
The prevalence of victimization across regions
4.2.2
More victimizations and less reporting?
92
92
93
4.3 Association between demographic variables, victimization and reporting to 95
the police
4.3.1
4.3.2
4.3.2.1
4.3.2.2
4.3.3
Gender, victimization and reporting to the police
Birthplace, victimization and reporting to the police
Country of birth and victimization
Reporting to the police by country of birth
Religion and victimization
95
95
95
100
102
103
Chapter 5. Leisure time, life style, peers, happiness and delinquency
5.1 Overview
105
5.2 Frequencies in the national and the regional samples
5.2.1
Leisure-time activities
5.2.2
Peers and friends
105
112
5.3 Consumption of alcohol and cannabis
5.3.1
Leisure-time and use of substances
5.3.2
Peers, friends and the use of substances
116
116
127
5.4 Computer games as other types of leisure-time activities
131
5.5 Changes in leisure-time activities between 2006 and 2013
135
5.6 Happiness, leisure-time, peers and substance use
144
5.7 Leisure-time, life style, peers, happiness and delinquency
5.7.1
Leisure-time and delinquency
5.7.2
Peer-networks and delinquency
5.7.3
Problem behaviour and delinquency
5.7.4
Are delinquents happy?
5.7.5
Delinquency by computer games
155
155
162
165
168
169
3
5.8 Summary and discussion
171
Chapter 6. Perception of right and wrong
6.1 Overview
174
6.2 Moral judgements across regions
6.2.1
Perception of right and wrong
6.2.2
Feelings of shame
174
174
177
6.3 Self-control, risky behaviour and altruistic vs. egocentric attitudes
6.3.1
Risk taking and accidents
6.3.2
Egocentrism
183
183
189
6.4 Good and bad neighbourhoods
191
Chapter 7. Delinquency over space and time in various degrees of
seriousness
7.1 Overview
199
7.2 Delinquency across Switzerland’s several regions
199
7.3 Trends in delinquency over time
200
7.4 Versatility: Are offenders specialists or generalists
203
7.5 Conclusion
205
Chapter 8. Contact with the police and perception of the image of the
police
8.1 Overview
207
8.2 Experience with and attitudes to the police
8.2.1
Attitudes across regions
8.2.1.1
The prevalence of contact with police because of illegal behaviour
8.2.1.2
Opinion of young people about the police
8.2.2
Opinion of young people about the police by respondents’ birthplace
207
207
207
207
216
4
8.2.3
Opinion of young people about the police by delinquency
8.3 Conclusion
221
230
Chapter 9. Technical report
9.1 Background
231
9.2 Sample design
9.2.1
Step 1. Selection of schools
9.2.2
Step 2. Collecting information about number of classes
9.2.3
Step 3. Random selection of classes
9.2.4
Step 4. Additional sample
231
232
232
232
232
9.3 Fieldwork
9.3.1.
Contacting schools
9.3.2.
Data collection
232
233
233
9.3.3.
235
Interviews and teachers
9.3 Questionnaire content and development
235
9.4 Interviews and teachers
235
9.5 Computer and Internet
236
9.6 Data processing and output
237
9.7 Data weighting
1. Attachment 1.
2. Attachment 2.
3. Attachment 3
4. Attachment 4
5. Attachment 5
6. Attachment 6
7. Attachment 7.1-7.3
8. Attachment 8.
9. Attachments 9
237
239
241
242
250
252
252
252
252
252
5
Chapter 0
Introduction
0.1 Background
It is about 25 years ago when, in 1989, some 20 specialists of self-report surveys gathered in a
conference hotel in Nordwijkerhout (NL) to discuss the feasibility of an international survey of
juvenile delinquency using the method of self-reported questionnaires. The first author of this
report was invited to participate in that meeting, as a specialist of conducting international,
comparative victimization surveys. Indeed, the first international crime victimization survey (van
Dijk, Mayhew &Killias 1990) had been in the field exactly about at that time. Encouraged by the
success of that first truly international survey in the field of criminology, Dr.JosineJunger-Tas
gathered around her a first steering group called to organize what then, in 1992, became the First
International Self-reported Delinquency Survey (ISRD-1) in which 12 countries had participated
(Junger-Tas, Terlouw& Klein 1994). Switzerland had been on board and it remained so at every
sweep ever since with a national sample.
After that first attempt, it was felt that next sweeps would need to be more tightly standardized.
The Steering Committee (of which the first author has remained a member since that time)
started working on a new project from 2003. In 2006, a second survey was launched, with about
30 countries participating (ISRD-2). This larger project has led to two major publications
(Junger-Tas et al. 2010, 2012). Already during the preparation of these two volumes, a new wave
(ISRD-3) has been organized in which again some 30 countries are participating. The present
report represents, so to speak, the first results of this new initiative, given that Switzerland and
Finland are among the first to have their results ready for analysis and distribution. As with
ISRD-2, the data of ISRD-3 will be publically accessible once the main analyses have been
achieved. The data of all countries participating will be introduced into a central database located
at the University of Hamburg. Since data collection is still ongoing in many countries, complete
international analyses will be available not before 2016 at best. Since Switzerland has, through
funds made available by the Swiss National Science Foundation (Switzerland and Indonesia), the
Federal Office of Migration (Serbia) and the Jacobs Foundation (Ukraine, Armenia, BosniaHerzegovina, Macedonia, Kosovo and India), coordinated the ISRD-3 in nine countries all in all,
we expect being able to present at least some comparative international data in the course of
2015 already.
0.2 The Swiss Report
The present report has been prepared keeping in mind that the first priority should be
documenting the Swiss National Science Foundation with all details about the realization of this
study that might be relevant to researchers who consider using these data for their own work. For
that purpose, as well as for the Members of the SNF Council, having a detailed overview about
what is in this project should be the priority. We have, therefore, presented several hundred
mostly bivariate Figures and Tables that document the wealth of the questionnaire used and the
6
potential of a fairly large sample. Indeed, the 8 Chapters that follow give an account of correlates
of juvenile delinquency that go beyond what has usually been communicated in research papers
on this subject. Many more Figures and Tables have been prepared but, finally, eliminated from
this report in order to keep it within reasonable size. They can be obtained from the authors on
request. This broad thematic perspective has obviously had its price in the sense that we could
not, at the same time and with the given resources, prepare multivariate analyses. Over the
upcoming months, we are going to prepare a series of conference papers and publications
devoted to several aspects of juvenile delinquency where more advanced methods of data
analysis will be used. A second compromise required to refer to the existing literature only
parsimoniously, i.e. at the end of each of the following chapters and to the extent it seemed
necessary to explain certain findings in a broader context. Without such restrictions, the present
report would have grown beyond any reasonable proportions.
The report of the project in Indonesia has been completed and presented to the Swiss National
Science Foundation. We are happy that the Indonesian research team of the University of
Surabaya had the courage and the energy to overcome all the endless obstacles (natural disasters
and political troubles) that could not be reasonably anticipated.
0.3 Fieldwork in Switzerland
The fieldwork in Switzerland was relatively demanding, since more than over 200 classes out of
more than 100 schools had to be contacted. In the end, more than 4’158 students in grades 7 to 9
have participated. Three cantons – St. Gallen, Aargau and Ticino – expressed interest in having a
deeper, more detailed analysis of the situation in their canton.
Detailed indications on sampling, weighting and other aspects of the methodology can be found
in the Technical Report (Chapter 9).
0.4 Acknowledgements
There are many people who, at some time or another over the last four years, have helped to
bring this project to a good end. Our first thank goes to the Swiss National Science Foundation
and in particular to Dr. Kathrin Weder whose support was absolutely decisive in the start and the
realization of the project. We further acknowledge the kind and generous technical support that
we received, all along this project, from other Members of the ISRD Steering Committee and in
particular from Prof.Dr. I. Haen Marshall, from Dr. D. Enzmann, Prof.Dr. M. Steketee and
Prof.Dr. J. Kivivuori. Regarding the survey in Switzerland, we received kind and efficient
support from the Direction of the Conference of Education Departments, namely former cantonal
Minister I. Chassot, Secretary General H. Ambühl and Dr. T. Mattmann-Arnold, from the many
cantonal Departments who authorized us to interview students in their schools, from nearly 100
school principals and, last but not least, from nearly 200 school teachers. We feel deeply
indebted to all these personalities and express here our sincere gratitude, including to all those
that we omit mentioning here by their names but who have in many ways contributed to the
success of this project.
7
St. Gallen/Lenzburg, 31 January 2015
Martin Killias
AnastasiiaMonnet Lukash
References
Junger-Tas J., TerlouwG.J. & Klein M.W. (1994)Delinquent Behaviour among Young People in the
Western World, Dordrecht/Boston: Kluwer 1994
Junger-Tas J., Marshall I., Enzmann D., Killias M., Gruszczynska B., Steketee M. (2010) Juvenile
Delinquency in Europe and Beyond: Results of the Second International Self-Report Delinquency
Study.Berlin/New York: Springer 2010
Steketee M., Moll M., Kapardis A. (Editors) Juvenile delinquency in six new EU member states.January
2008. Utrecht: Verwey-JonkerInstituut, 2008. 190 p. P.16
Junger-Tas J., Marshall I., Enzmann D., Killias M., Steketee M., Gruszczynska B. (2012) The Many
Faces of Youth Crime: Contrasting Theoretical Perspectives on Juvenile Delinquency across Countries
and Cultures.Berlin/New York: Springer 2012
vanDijk J.J.M., Mayhew P.&Killias M. (1990)Experiences of Crime across the World. Key findings of the
1989 International Crime Survey, Deventer/Boston: Kluwer 1990
8
0.5.Abbreviations
CH = Switzerland
DE = German speaking part of Switzerland
FR – French speaking part of Switzerland
ITA – Italian speaking part (canton of Ticino)
SG – the canton of St. Gallen
AG – the canton of Aargau
GE – the canton of Geneva
ZH – the canton of Zurich
ltp – life time prevalence
lyp – last year prevalence
lmp – last month prevalence
IV – independent variable
DV – dependent variable
*** p≤.001 (high significant)
** .001<p≤.010 (significant)
* .010<p≤.050 (nearly significant)
n.s. p>.050 (not significant)
9
Chapter 1
Juvenile Delinquency in Switzerland: An Overview
1.1.What this Chapter is about
Module 1 of the ISRD-3 questionnaire includes questions on the social background of
respondents. In this Chapter, we shall present basic demographic information on our sample,
both for the national as well as the several regional subsamples, i.e. on variables including age,
sex, migrant status, religion and its importance, living arrangement, family influence, and
ethnicity. In the second part, we shall present basic findings about delinquency and its
distribution across space and time, as well as basic associations with social background
variables, such as social wellbeing, ethnicity, religion, family constellation etc. We shall
conclude with some information about victimization.
1.2. Social background variables
1.2.1. Gender and age in our samples
Table 1.1 informs about the distribution of male and female respondents across the national and
the various regional subsamples.
Table 1.1
N=
male
female
Gender by main sample and subsamples in %. Weighted data.
Switzer
land
4158
48.7
51.3
DE
FR
2560
48.5
51.5
956
48.6
51.4
ITA
(TI)
642
51.8
48.2
SG
AG
GE
ZH
625
47.8
52.2
555
52.4
47.6
268
47.7
52.3
266
44.9
55.1
Gender distribution in the national and the various regional samples is fairly even. With a
proportion of about 50 per cent of boys and girls, the samples are in line with the gender
distribution in the Swiss general population aged 12-16. According to population statistics of the
Swiss Federal Statistical Office, 51.4% of the age-group 12-16 is male1.
1
Bevölkerung nach Alter und Geschlecht. Swiss Federal Statistical Office (FSO)
http://www.bfs.admin.ch/bfs/portal/de/index/themen/01/02/blank/key/alter/nach_geschlecht.html
10
Table 1.2
Age of respondents in %. Weighted data.
Age
% in the main sample
12
13
14
15
16
17-19
% in total population 2
6.1
26.1
31.2
25.6
9.6
1.4
24.8
24.7
25.1
25.5
The age distribution in our national sample matches fairly well the student population in 7th – 9th
grades of secondary schools. The proportion of students below 13 and above 16 is small, since
these respondents may have experienced a somewhat unusual school career. In sum, the age and
gender distribution in our sample matches population data very closely.
1.2.2. Birthplace
Since the ISRD-3 was designed to be conducted in some 30 countries around the globe, the
instrument needed to take very different situations of migration into account. The solution
adopted was to ask about country of birth of respondents and of their mothers and fathers, rather
than about nationality in a formal sense. Since these questions were asked the same way in
ISRD-2, comparisons between 2006 and 2013 are possible.
Figure 1.1
Respondents’ birthplace by main and subsamples in %3.
30.0
26.9
21.3
20.0
10.0
13.8
7.7
2.33.9
10.5
4.9
2.82.8
18.2
14.2 13.7
5.6
1.5
6.56.0
1.3
14.0
6.0
3.64.5
11.6
4.43.04.2
7.5
1.2
9.8
5.5
2.51.8
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
Born NOT in Switzerland
Ex-Yugoslavia
West Europe
Other (countries of Asia, Africa, N. America, S. America, E. Europe, C. Europe)
2
Swiss Federal Statistical Office (FSO), same source as in Footnote 1 (Tables je-d-01.02.01.02.03). Respondents of
the survey were supposed to be in the 13-15 years range. Some younger and older subjects are in our sample
because students were surveyed in classes.
3 Weighted data
11
Nationwide, 14% of respondents were born outside of Switzerland. This percentage is 11% in
German-speaking cantons and about twice that high in the Romandie (21%). The countries of
birth are predominantly located in Asia, Africa, Americas, and Central/Eastern Europe. In
comparison with 2006, fewer students were born in the countries of Ex-Yugoslavia,
Fathers’ birthplace by main and subsamples in %4.
Figure 1.2
ZH
(N=266)
.8 4.1
.2 3.6 9.4
.22.3
4.4
6.4
6.4
GE
(N=268)
1.44.6
6.310.5
13.618.5
.4
1.2 7.0
7.4
AG
(N=555)
.4
.7 6.1
2.3
.72.2
3.3 9.1
6.9
6.9
SG
(N=625)
.4
.6 4.9
1.14.3
.9 3.8
8.9
6.3
4.5
37.8
Eastern, Central Europe
Asia/Oceania
Africa
West Europe
35.7
Portugal
Germany
24.0
DE
(N=2'560)
.51.7
1.1 7.5
.92.5
3.5
5.8
5.4
5.0
Switzerland
(N=4'158)
.82.1
6.5
2.2
4.3
4.0
2.7
4.8
4.9
5.9
0.0
Ex-Yugoslavia, Albania
43.7
Kosovo
1.6
3.1
5.0
5.18.8
10.8
1.1
2.5
4.2
4.7
FR
(N=956)
Americas (North, South)
38.7
.52.3
2.1
.91.9
5.2
.7 5.0
1.3
ITA
(N=642)
71.0
Italy
47.1
33.9
38.2
20.0
40.0
60.0
80.0
Fathers were more often born abroad than our respondents. In the Romandie, in Zurich and
Geneva, close to, or over 50 per cent, of respondents have a father born abroad.As the following
Figure illustrates, mothers were also very often born abroad.
4 Weighted data
12
Mothers’ birthplace by main and subsamples in %5.
Figure 1.3
ZH
(N=266)
2.6
3.1 10.9
1.0
.21.64.7
5.2
4.4
2.6
GE
(N=268)
1.1
4.17.8 12.9
13.5 20.5
1.1
3.0
1.0
AG
(N=555)
.82.3
2.5 7.2
2.3
1.6
3.1 9.6
6.1
3.9
36.3
Asia/Oceania
Africa
Portugal
Germany
50.2
34.3
1.8
3.56.6
3.1
4.9
4.5
2.8
5.2
3.9
2.9
Switzerland
(N=4'158)
0.0
10.0
Kosovo
Italy
1.6
2.6 8.2
1.2
2.8
1.0
3.96.3
4.5
2.2
DE
(N=2'560)
38.1
2.25.3
3.57.5
10.0
12.2
.82.5
3.3
2.8
FR
(N=956)
West Europe
39.2
2.1
4.1
2.8
2.0
1.85.7
.7 5.5
1.4
12.0
ITA
(N=642)
39.3
1.3
1.9
1.24.7
6.2
.9 3.9
9.9
3.35.9
SG
(N=625)
65.0
39.1
20.0
30.0
40.0
50.0
60.0
70.0
5 Weighted data
13
1.2.3. Family constellations
The vast majority of respondents live with (step)father and (step)mother. Roughly one in six
lives with one parent alone. Other arrangements are exceptional. There is little variation across
Switzerland.
Who brought you up by main and different subsamples in %6.
Figure 1.4
100.0
84.7
82.9
80.0
77.7
88.3
83.5
82.7
85.3
75.3
60.0
40.0
15.0
2.1
20.0
13.6
1.7
19.4
2.9
DE
(N=2'560)
FR
(N=956)
8.33.4
14.0
2.4
14.0
3.3
SG
(N=625)
AG
(N=555)
23.4
1.3
13.9
0.8
GE
(N=268)
ZH
(N=266)
0.0
Switzerland
(N=4'158)
ITA
(N=642)
(step)father and (step)mother
1 of parents
other (divorces parent(s), grandparent(s), other (aunt, uncle, governante, 2 fathers, internat, social workers,
sister etc.)
Given the international character of the ISRD instrument, it was decided to include also an item
on racial identity. Table 1.3 gives the details for Switzerland.
Table 1.3
To which group do you belong? (Minority) by main and subsamples in %7.
Switzerland
(N=4'158)
European
African
Asian
Other
90.9
1.7
4.1
3.3
DE
FR
ITA
SG
AG
GE
ZH
(N=2'560) (N=956) (N=642) (N=625) (N=555) (N=268) (N=266)
90.9
1.0
5.6
2.5
89.9
3.2
1.5
5.3
96.3
.6
1.4
1.6
92.9
.8
3.2
3.0
92.3
1.4
4.0
2.3
86.5
3.9
.6
9.0
87.1
1.4
7.5
4.0
This is the country specific question, where each country must find its own variant. In
Switzerland minorities were defined in the form of self-identification as European, African,
Asian, and others.
Most of respondents identify themselves as Europeans in Switzerland.
1.2.4 Religion
6 Weighted data
7 Weighted data
14
Although the interest in the questions regarding religion will be centred on international
comparisons (some Muslim and other Non-Christian countries participate in ISRD-3), the
following Figures disclose a few interesting patterns.
Figure 1.5
Religious affiliation in%8.
80.0
71.0
70.0
60.0
50.0
40.0
47.9
37.8
34.2
29.2
44.7
44.0
39.9
36.5
24.8
24.8
19.9
19.9
19.1
18.0
17.7
17.0 14.0
20.0 15.0
13.3
12.9
12.4
10.7
10.2
9.8
9.6
8.6
8.29.0
7.8
7.3
6.6
6.37.2
6.24.3
6.06.8
5.4
5.4
5.36.2
4.4
4.2 6.1 4.3
4.13.6
10.0
3.3
2.4
2.2
2.2
1.7
.1
30.0
0.0
Switzerland
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
do not belong to a religion/religion community
protestant
other christian confessions
other
AG
(N=555)
GE
(N=268)
ZH
(N=266)
catholic
orthodox
muslim
Most students belong to any of the Christian denominations. There is, not unexpectedly, some
variation across the country. Particularly noteworthy is the low proportion of respondents that
say belonging to the protestant (reformed) Church that used to be the dominant denomination
one generation ago. Muslims are more frequent in Zurich, Aargau and St. Gallen.
Figure 1.6
60.0
40.0
20.0
Importance of religion in %9.
43.1
38.7
18.2
47.1
35.2
47.4
34.6
18.1
17.7
52.3
42.1
33.4
24.5
51.9
30.6
29.5
18.2
36.7
33.0
30.4
17.5
42.9
40.0
17.1
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
Very important
ITA
(N=642)
SG
(N=625)
neither/nor
AG
(N=555)
GE
(N=268)
ZH
(N=266)
very unimportant
Beyond formal membership in any church or religion, the instrument asked about the importance
religion plays in respondents’ every-day life. As it turns out, students saying religion to be
completely unimportant to them are more numerous than those attributing it much importance.
This holds particularly true in French-speaking cantons. Weak attachment to religion is, as the
8 Weighted data
9 Weighted data
15
following Figure illustrates, particularly frequent among respondents who say to belong to the
protestant church.
Importance of religion by religious affiliation in %10.
Figure 1.7
79.2
58.1
53.4
43.847.8
47.2
36.0
30.9
18.9
21.8
8.3
2.0
catholic
42.0
36.2
37.9
21.8
16.9
15.7
do not belong to a
religion/religion
community
42.7
35.5
3.9
protestant
orthodox
very important
other christian
confessions
neither/nor
muslim
other
very unimportant
Religion is very important mostly for Muslims. It is also fairly important to students of NonChristian or “other” Christian denominations.
1.2.5 Employment and economic wellbeing
Given the high unemployment rates in several Western countries, the following items will be of
interest mostly in international comparisons.
Fathers’ employment status by main and subsamples in %11.
Figure 1.8
93.8
100.0
94.1
93.6
91.6
94.5
93.5
94.7
92.6
50.0
2.1
4.0
2.1
3.8
2.1
4.3
3.5
4.9
1.4
4.1
2.7
3.8
2.5
2.8
2.9
4.5
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
Yes, he is unemployed
SG
(N=625)
AG
(N=555)
No, he is working
GE
(N=268)
ZH
(N=266)
other
The level of unemployment is very low in Switzerland and does not vary across regions. Mothers
are somewhat less employed, but still at a comparatively very high rate. Again, there is little
variation across the country.
Figure 1.9
Mothers’ employment status by main and subsamplesin%12.
10 Weighted data
11 Weighted data
16
100.0
80.0
60.0
40.0
20.0
0.0
78.4
78.2
80.3
7.5 14.1
7.1 14.7
Switzerland
DE
(N=4'158) (N=2'560)
70.4
78.1
7.7 12.0
12.0 17.6
7.7 14.2
6.5
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
Yes, she is unemployed
77.5
16.0
No, she is working
76.6
76.5
8.5 14.9
8.4 15.1
GE
(N=268)
ZH
(N=266)
other
A related question is whether or not the family has its main income from father’s and/or
mother’s earnings, or from other sources (mostly presumably social welfare).
Figure 1.10
120.0
100.0
80.0
60.0
40.0
20.0
0.0
Income: Earning, wages, salary and other source by main and subsamples in %13.
95.0
96.3
92.4
93.1
97.7
3.9 1.1
2.7 1.0
6.4 1.1
4.9 2.0
1.2 1.0
1.5
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
unemployment or social welfare benefits
97.6
.9
86.6
12.0
94.8
1.4
3.8 1.3
GE
(N=268)
ZH
(N=266)
earnings, wages, or property
other
As Figure 1.10 illustrates, respondents’ families obtain their incomes almost exclusively from
earnings. Social welfare plays only in French-speaking cantons and in Geneva a more than
marginal role.
12 Weighted data
13 Weighted data
17
“How well-off is your family in comparison with others” by main and
subsamples in %14.
Figure 1.11
60.0
50.0
49.6
48.5
51.5
52.7
49.8
46.5
47.5
43.3
40.0
30.0
20.0
10.0
23.0
22.5
20.5
19.7
19.5
19.3
18.8
18.0
17.4
16.2
16.1
15.8
15.1
14.5
11.7
11.7
10.9
9.8
8.9
8.4
8.1 5.5
7.5 6.0
6.8 6.6
6.7
5.4
5.3
4.4
4.3
3.8
3.1
3.0
2.7
2.7
1.4.8
1.4
1.1
.9.4
.7.5
.7.4
.61.5
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
much better off
better off
somewhat better off
somewhat worse off
worse off
much worse off
GE
(N=268)
ZH
(N=266)
the same
By far the largest group among our respondents are those who say their family’s wellbeing to be
about average. There are, in all regions, more students who say being better off than average
families, than there are students who claim being worse off than other families.
“How much money do you have by your own”, in comparison with others in
%15.
Figure 1.12
60.0
50.0
46.5
44.7
55.1
54.0
49.1
46.5
45.8
38.8
40.0
30.0
20.0
10.0
25.4
20.5
20.1
18.9
17.8
16.5
16.2
15.5
15.3
14.5
14.4
13.9
13.8
13.1
12.2
11.0
10.0
10.0
9.5
8.8
7.7
7.5
7.3
7.3
5.7
5.6
5.5
5.5
5.2
5.1
5.0
5.0
4.9 3.5
4.9
4.0 2.9
3.9
3.6
2.4 4.2
2.3
1.9 4.2
1.7
1.4
1.0 3.0
0.0
Switzerland
DE
(N=4'158) (N=2'560)
much more
more
FR
(N=956)
ITA
(N=642)
somewhat more
SG
(N=625)
the same
AG
(N=555)
somewhat less
GE
(N=268)
less
ZH
(N=266)
much less
An additional question was about how much money juveniles have available for their own needs.
The distribution is very similar to what came out in Figure 1.10 regarding the family’s economic
situation. Also in this respect, roughly half of respondents rate themselves as average, while the
overall distribution resembles very much a Gaussian curb in all regions.
14 Weighted data
15 Weighted data
18
In order to make these items more helpful for further analysis, an index has been constructed by
collapsing, in dichotomized form, (1) the source of income of the family (unemployment or
social welfare benefits vs. earnings, wages, or property of the parents); (2) the well-off of the
family, compared to others (better/same vs. worse); (3) amount of respondent’s personal money
to spend (pocket money + presents + own earnings, etc.) in comparison with others (more/same
& less). Respondents were rated as “middle or high levels” if (1) they get money from earnings,
wages, property; (2) are better off or the same as other families; and (3) have more or the same
amount as others to spend on personal needs.
Economic level in regions and selected cantons in %16.
Figure 1.13
100.0
80.0
60.0
40.0
20.0
0.0
72.9
27.1
74.8
25.2
Switzerland
DE
(N=4'158) (N=2'560)
69.7
67.9
30.3
32.1
FR
(N=956)
ITA
(N=642)
Low level
77.0
76.4
23.6
23.0
SG
(N=625)
AG
(N=555)
67.6
73.3
32.4
26.7
GE
(N=268)
ZH
(N=266)
Middle and high levels
As Figure 1.13 illustrates, between two thirds and three quarters of respondents rate themselves
as middle or high levels.
1.2.6 Changes between 2006 and 2013
Table 1.4
12
13
14
15
16
17+
Age of respondents in % for ISRD-2 and ISRD-3.
ISRD-2 (not weighteddata)
3.2
20.3
33.0
30.1
11.7
1.7
ISRD-3 (weighteddata)
6.1
26.1
31.2
25.6
9.6
1.4
The age distribution is almost identical in 2006 and 2013. This underlines the fact that our
sample is fairly representative for the student population in grades 7 to 9.
16 Weighted data
19
Figure 1.14
Respondents’ birthplace by main and subsamples in % for ISRD-2 and ISRD-317
30.0
26.9
21.3
Switzerland
DE
FR
11.6
ITA
SG
AG
7.5
ISRD-3 (N=268)
1.2
ISRD-2 (N=224)
ISRD-3 (N=555)
ISRD-2 (N=220)
6.5
6.05.0
6.0
4.5
4.44.2
3.6
2.8
2.2
1.90.9
1.83.2 3.0 2.7
1.3
ISRD-3 (N=625)
8.4
4.2
18.2
13.7
16.5
11.6
GE
9.8
5.5
2.5
1.8
0.8
6.76.2
ISRD-3 (N=266)
13.7
ISRD-2 (N=293)
ISRD-3 (N=956)
ISRD-2 (N=799)
ISRD-3 (N=2'560)
ISRD-2 (N=2'551)
ISRD-3 (N=4'158)
ISRD-2 (N=3'643)
13.8
12.4
15.0 10.9
10.2 10.5
8.0
7.7
10.0
5.6
4.9 3.5
4.45.9 3.9 4.74.9 2.8
2.8
2.3
5.0
1.5
0.9
0.6
0.6
0.0
14.0
ISRD-2 (N=224)
14.212.6
ISRD-3 (N=642)
20.0
ISRD-2 (N=980)
25.0
ZH
Ex-Yugoslavia
West Europe
As Figure 1.14 shows, the proportion of students born abroad has increased in Switzerland,
particularly in French-speaking cantons. The percentage of students from former Yugoslavia has
decreased. When we consider father’s birthplace, the trend is similar between 2006 and 2013.
17 Weighted data (ISRD-3, N=4158), not weighted data (ISRD-2, N=3643).
20
Figure 1.15
Fathers’ birthplace by main and subsamples in % for ISRD-2 and ISRD-318.
0.5
2.3
2.1
0.9
1.95.2
0.7 5.0
1.3
ITA
ISRD-3 (N=642)
24.0
0.7
1.4
2.5
0.7
2.1
2.16.0
ISRD-2 (N=293)
43.7
28.1
43.8
1.6
3.1
5.0
5.18.8
10.8
1.1
2.5
4.2
4.7
FR
ISRD-3 (N=956)
Asia/Oceania
ISRD-2 (N=2'551)
0.9
1.14.9
1.5
2.9
1.3
1.95.8
4.1
5.8
ISRD-3 (N=4'158)
0.8
2.1 6.5
2.2
4.3
4.0
2.7
4.8
4.9
5.9
ISRD-2 (N=3'643)
0.8
1.44.1
2.04.4
2.7
1.6
5.2
3.6
7.2
Switzerland
DE
ISRD-3 (N=2'560)
0.5
1.7 7.5
1.1
2.5
0.9
3.5
5.8
5.4
5.0
0.0
Africa
47.1
0.7
2.4
2.2
4.1 10.6
7.7
0.9
2.6
2.4
4.2
ISRD-2 (N=799)
West Europe
Portugal
Germany
37.7
Kosovo
Italy
33.9
30.3
38.2
33.0
20.0
40.0
60.0
In general the proportion of respondents having fathers born abroad has increased from ISRD-2
to ISRD-3 in all regions. Some nationalities such as Italians have considerably decreased,
whereas Yugoslavs have remained stable. No nationality seems to dominate. In other words,
Switzerland’s foreign population has increased overall and at the same time has become more
diverse.
18 Weighted data (ISRD-2 and ISRD-3)
21
Figure 1.16
Mothers’ birthplace by main and subsamples in % for ISRD-2 and ISRD-319.
ISRD-2 (N=293)
1.4
3.5
2.5
0.4
3.5
1.8
0.7
2.1 7.4 13.4
ITA
ISRD-3 (N=642)
2.1
4.1
2.8
2.0
1.85.7
0.7 5.5
1.4
12.0
ISRD-2 (N=799)
1.2
3.3
2.3
5.3 10.9
8.1
0.9
2.3
2.7
3.1
FR
ISRD-3 (N=956)
2.25.3
3.57.5
10.0
12.2
0.8
2.5
3.3
2.8
ISRD-2 (N=2'551)
1.0
2.55.4
1.4
3.0
1.7
3.06.1
4.0
3.2
ISRD-3 (N=4'158)
1.8
3.56.6
3.1
4.9
4.5
2.8
5.2
3.9
2.9
ISRD-2 (N=3'643)
1.0
2.8
4.5
2.2
4.8
3.1
2.4
5.4
3.6
4.0
Switzerland
DE
ISRD-3 (N=2'560)
1.6
2.6 8.2
1.2
2.8
1.0
3.96.3
4.5
2.2
0.0
38.1
36.7
Asia/Oceania
Africa
50.2
West Europe
Portugal
Germany
40.1
Kosovo
Italy
34.3
31.4
39.1
33.7
20.0
40.0
60.0
Compared to 2006, the proportion of respondents having a mother born abroad has increased.
Again, there is no dominating group, Switzerland’s immigrant population being fairly diverse.
Father’s employment situation has remained unchanged since 2006. Both in 2006 and in 2013,
over 90 per cent are (at least partially) employed.
22
Percent fathers who are unemployed, in % for ISRD-2 and ISRD-320
Figure 1.17
6.0
4.3
1.3
4.0
4.0
2.1
1.1
4.6
3.8
2.1
4.3
2.1
2.0
5.8
4.9
3.5
4.1
2.3
1.8
1.4
1.4
3.8 3.4
2.4 2.7
1.4
5.3
2.8
2.5
4.5
2.9
1.2
ISRD-2
(N=3'643)
ISRD-3
(N=4'158)
ISRD-2
(N=2'551)
ISRD-3
(N=2'560)
ISRD-2
(N=799)
ISRD-3
(N=956)
ISRD-2
(N=293)
ISRD-3
(N=642)
ISRD-2
(N=224)
ISRD-3
(N=625)
ISRD-2
(N=220)
ISRD-3
(N=555)
ISRD-2
(N=224)
ISRD-3
(N=268)
ISRD-2
(N=980)
ISRD-3
(N=266)
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
Switzerland
DE
FR
ITA
SG
He is unemployed (he cannot find a job)
AG
GE
ZH
Other (ill, handicapped, retired, other)
Although the number of unemployed fathers has almost doubled between 2006 and 2013 (from
1.3 to 2.1 per cent in the national sample), the proportion of those who do not belong to the
workforce (because of illness, handicaps etc.) has remained stable. With respect to mother’s
employment situation, no change between 2006 and 2013 can be observed, with the exception of
a higher unemployment rate (that rose from 2.7 to 7.5 per cent).
Figure 1.18
73.6 78.4 74.8 78.2 74.6 80.3
Switzerland
DE
FR
ITA
SG
AG
GE
ISRD-3 (N=266)
ISRD-2 (N=980)
ISRD-3 (N=268)
ISRD-2 (N=224)
ISRD-3 (N=555)
ISRD-2 (N=220)
ISRD-3 (N=625)
ISRD-2 (N=224)
ISRD-3 (N=642)
ISRD-2 (N=293)
ISRD-3 (N=956)
ISRD-2 (N=799)
75.1 78.1 75.8 77.5 76.1 76.6 76.5 76.5
60.3 70.4
38.6
23.8 14.1 22.6 14.7 22.0
17.6 23.17.714.2 22.4 16.0 19.48.514.9 20.48.415.1
12.0
12.0
7.7
7.5
7.1
3.4
3.1
2.6
2.6
1.8 6.5 4.5
1.8
1.0
ISRD-2
(N=3'643)
ISRD-3
(N=4'158)
ISRD-2
(N=2'551)
ISRD-3
(N=2'560)
100.0
80.0
60.0
40.0
20.0
0.0
Mothers’ employment rate in % for ISRD-2 and ISRD-321
ZH
She is unemployed (she cannot find a job)
Wokrs (permanent job, own business, sometimes work)
As a result, the economic level (as defined above) has remained stable as well (not shown).
23
1.3 Association between social background and delinquency
1.3.1 Gender, age and delinquency
The Figure 1.19 and Table 1.4 illustrate the distribution of delinquency across gender and age.
Delinquency (last year prevalence) by gender in %,N=4051-406822
Figure 1.19
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
16.4
16.0
13.3
9.6
7.7
5.4
4.0
11.0
10.6
9.8
9.5
2.3
0.6
3.7
3.1 2.4
2.4
0.8
0.4
0.3
male
4.9
3.8
4.2 4.9
1.6
3.5
5.1
2.2
female
Boys are more likely to commitoffences than girls. The difference is highest for serious and
violent offences, and weakest for shoplifting.
Delinquency (last year prevalence) by age in %, N=4040-406123
Table 1.4
Graffiti Vandal
ism
Shoplif
ting
Burglar Bicycle Motorb Car
y
theft
ike/car break
theft
Robber
y
Theft
Weapo
n
Group
Fight
Assault Drug
Dealin
g
Animal
Cruelty
11-12 3.3
5.3
7.3
0.4
1.6
0.4
3.3
0.8
4.9
6.1
6.1
1.2
0.8
3.3
13
3.9
8.6
10.8
0.7
2.3
0.2
1.3
0.7
6.6
6.6
5.7
1.6
1.4
3.6
14
5.6
7.5
10.4
0.6
4.1
0.7
1.4
0.7
7.0
8.8
5.0
2.4
4.7
3.7
15
9.5
11.0
16.2
2.1
11.5
2.8
2.9
2.0
9.1
13.1
9.6
4.6
8.3
3.4
16
11.6
14.5
17.8
3.9
13.4
2.3
3.9
2.8
9.3
16.4
15.0
6.5
13.2
3.4
10.0
16.0
2.0
5.9
3.9
2.0
0.0
16.0
10.2
8.0
0.0
14.0
0.0
.000
.000
.000
.000
.000
.005
.001
.013
.000
.000
.000
.000
.840
17-19 7.8
p=
.000
22 Weighted data
23 Weighted data
24
Respondents older than 14 are more likely to commit offences, the maximum being reached at
age 16. The group of 17 and older students is, beyond its small size, characterized by an
unconventional school career and, thus, not necessarily comparable to younger students. The
differences across age are significant formost offences.
1.3.2 Birthplace and delinquency
Delinquency rates by birthplace (immigrant) background can be seen in the following Figures.
Delinquency (last year prevalence) by respondents’ birthplace (dichotomized) in
%, N=4048-406424
Figure 1.20
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
13.7
13.5
15.6
12.2
12.5 13.0
9.6
9.0
7.0
6.6
11.9
10.9
8.6
5.7
5.6
3.1
1.1
4.5
4.0
3.4
2.0
0.9
0.8
not in Switzerland
2.3
6.7
5.4 4.5
3.4
Switzerland
Respondents born abroad are more likely to commit offences. The difference is, although
significant for most offences, not all too large when compared to other variables considered in
this report. Drug dealing and shoplifting are two examples where youths born abroad do not
differ significantly from juveniles who were born in Switzerland.
24 Weighted data
25
Delinquency (last year prevalence) by mothers’ birthplace in %, N=4023-404125
Figure 1.21
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
9.4
10.8
8.2
14.3
11.4
10.0
4.9
4.1
1.51.2
9.8
11.0 10.8
9.2
6.1
2.8
2.4
1.7 2.20.8
0.5
not in Switzerland
5.1 4.6
2.2
6.4
4.9 4.1
3.2
Switzerland
Respondents whose mothers were born abroad report more offences than those, whose mothers
were born in this country.
25 Weighted data
26
Figure 1.22 Delinquency (last year prevalence) by mothers’ birthplace in % (detailed),
N=4023-4041 26
1.3 2.6
3.33.84.6 5.8
2.6
2.9
3.5
3.2
3.3 4.5
2.7
3.8 4.9
5.3
5.2
1.6
2.1
5.2
2.0
2.5
1.7
2.2
Animal Cruelty*
Drug Dealing***
Assault***
5.6
5.1
Weapon***
Theft***
Car break*
Motorbike/car theft***
Bicycle theft***
Burglary***
8.0
8.2
11.4
9.3
9.4 10.5
8.7
8.0
9.6
20.3
16.0
Americas
(North, South)
14.3
6.4
10.211.3
6.0
16.7
12.6
17.7
Asia/Oceania
6.0
9.2
18.9
13.7
5.7
10.511.8 13.7
Africa
5.25.8
11.3
6.1 7.8
West Europe
5.0
Group Fight***
Robbery***
9.4
9.310.0
9.7
8.89.7
1.3
1.1
0.8
1.5
1.6
1.92.6
5.7
0.9
0.8
4.0
2.9
0.00.8 2.2 4.1
2.7 4.3
1.72.6 4.5
4.0 5.1
0.0 1.5
1.5 2.7
2.7
2.4
0.5 1.72.5
5.3
8.3 9.7
6.5
6.6
4.1 6.0
1.3 2.9
0.4
0.0
0.0 1.1
7.1
2.4
0.6
0.9
1.2
9.3
13.1
13.6
Portugal
Germany
11.6
11.5
Kosovo
Italy
14.6 16.6
Switzerland
15.0
11.7
14.6
15.2
12.1
15.5
11.4 12.7
15.6
7.1
5.7
13.8 15.2
9.8
6.3
12.1
12.0
8.2
6.7
6.8
15.2
6.0 7.8 8.9 10.7
5.1
8.6
4.9
Shoplifting
Vandalism***
Graffiti***
0.0
5.0
10.0
15.0
18.5
17.9
18.7
18.4
20.0
25.0
If respondents with mothers born abroad commit more offences overall, Figure 1.22 shows that
there is considerable variation across countries of origin.
26 Weighted data
27
Delinquency (last year prevalence) by fathers’ birthplace in %, N=3990-400527
Figure 1.23
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
14.3
8.0
10.3
8.2
11.3
10.3
10.1
10.4
9.6
5.8
5.3
4.1
2.0
1.0
2.9
2.6
1.7 2.4
0.6
0.6
not in Switzerland
11.5
4.7 5.4
1.8
6.9
4.9
3.83.4
Switzerland
Students, whose fathers were born not in Switzerland, report more offences. The differences are
generally larger than according to mothers’ birthplace. Again, the difference varies a lot across
countries of origin (Figure 1.24).
27 Weighted data
28
Delinquency (last year prevalence) by fathers’ birthplace in % (detailed),N=39904005 28
Figure 1.24
Animal Cruelty
Drug Dealing***
Assault***
Group Fight***
Weapon***
Theft***
Robbery***
Car break
Bicycle theft***
Burglary**
Shoplifting*
Vandalism*
Graffiti***
0.0
5.7
3.1
1.22.3
2.53.7
3.7 6.2
3.4 5.8
9.1
13.8
3.4
9.2
6.9
2.5
7.3 9.7
7.7
4.9 6.7
15.2
14.0
0.0 1.7 4.2
7.4 8.8
3.8
4.15.4
1.8
12.5
12.8
5.76.9
8.0
14.9
10.1
15.3
19.1
10.3
4.7
9.1
17.2
5.0 7.0
13.2
6.9 9.3
12.8
17.5
8.69.6
12.1 14.0
6.1
12.6
16.1
13.1
3.7 5.3
14.9
9.0
5.8
3.1 4.6
0.00.8 2.9
Asia/Oceania
0.6
1.6 3.7 5.7
0.6 2.2
Africa
3.1
1.12.33.5
4.0
2.5
2.83.7
West Europe
5.2
2.1
1.7
8.29.1
Portugal
1.1
1.1 2.9
2.5
2.8
2.1
2.6
Germany
0.6 2.6
6.1
15.3
5.86.98.0
6.9
6.5
13.2
21.2
7.3
4.1
Kosovo
3.1
3.5
0.4
0.0 2.3
0.6
0.9
3.7
Italy
3.1
1.02.1
6.3
18.4
13.0 15.1
Switzerland
10.3
18.1
11.212.8
16.1
16.6
11.3
15.2
15.1
7.3
3.5
9.7
10.0 11.9
8.5
12.314.0
8.2
18.8
14.0
6.5
3.5
8.5
6.2
13.6
9.1
5.7
6.0
5.3
0.0
5.0
10.0
15.0
20.0
25.0
Respondents with fathers born in Switzerland do not have the lowest rates of delinquency
throughout all offences. For example,vandalism, shoplifting, caring weapons, drug dealing and
animal cruelty are cases where juveniles born in Switzerland have fairly high rates. In general,
28 Weighted data
29
however, father’s origin seems to be more important than respondents’ and mother’s country of
birth. In the following Figure, we have combined the information on parental origin.
Delinquency (last year prevalence) by parents’ birthplace in %, N=3972-3991 29
Figure 1.25
20.0
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
17.7
8.5
7.2
4.7
12.0 13.1
10.1
9.9
7.5
11.7 11.9
10.6 10.5
9.8
9.0 8.7
10.7
8.2
1.8
1.7
0.9
3.3 3.0
3.1
2.1
1.6 2.6
1.1
0.7
0.7
0.5
Both parents born NOT in Switzerland
5.0
4.1
7.0
6.6
5.5
4.4 4.3 3.4
3.4
2.7
1.7
1 of parents were born in Switzerland
Both parents born in Switzerland
Respondents with parent(s) of foreign origin are more likely to commit an offence than their
peers with both parents born in this country. Interestingly, respondents with only one parent born
abroadtend to have the highest rates of shoplifting and drug dealing.
Given the international character of ISRD-3, it was necessary to assess ethnicity also by a
question regarding racial characteristics. The following Figure shows the association and
delinquency.
29 Weighted data
30
Figure 1.26
25.0
20.0
15.0
10.0
5.0
Delinquency (last year prevalence) by social groups, minorities in %, N=40434064 30
23.5
21.5 22.7
18.217.2
17.9
17.0 17.8 17.8
15.6 14.914.9 14.9
14.9
14.7
13.4
13.4
12.4
11.2
10.5
9.7 8.9
9.4 8.8 8.1
9.1
7.6
7.6 7.5
7.3
6.9 5.9 7.4
6.7
6.5
6.4 5.1 5.3
6.0
6.0
5.9
4.55.6
4.1
3.8
3.3 3.5
2.6
2.4
2.0
1.8
1.8
1.2
1.0
0.9
22.2
0.0
European
African
Asian
None of the above
Students who indicated being Africans report higher delinquency rates than their European and
Asian peers.
30 Weighted data
31
1.3.3 Family constellation and delinquency
The following Figure illustrates the importance of the family background. The question in the
instrument was, once more, not about formal settings, but about by whom the respondent
actually has been brought up.
Delinquency (last year prevalence) by “Who brought you up?” in %, N=4052406831
Figure 1.27
25.0
20.0
15.0
10.0
5.0
0.0
18.6
7.4
6.2
20.9
18.4
15.1
12.9 11.3
8.5
16.5
10.5
9.2
7.9
7.4
5.8 5.8
4.7
4.7
3.5
1.9
1.9 1.2
1.9
1.8 2.2
1.2
1.2
father and mother
one parent only
18.8
11.4
9.5
17.9
8.9
7.0
11.8
8.2 9.4
5.6 4.7
4.7
3.6
3.3
2.7
other situation
The findings shown in Figure 1.27 confirm the importance of being brought up by two parents,
either natural or stepparents. Children from single-parent households have slightly higher
delinquency rates. More problematic are respondents brought up in other settings.
31 Weighted data
32
1.3.4 Religion and delinquency
The following two Figures show delinquency rates by religious affiliation, and by the importance
religion plays in respondents’ every-day life.
Delinquency (last year prevalence) by religious affiliation in %, N=4021-4040 32
Figure 1.28
5.5 7.5
3.6
2.6
1.8 4.0
8.7
7.2
7.9
4.5
4.0
8.1
5.1
3.6 5.8
2.9
3.0
2.0
4.7
5.3
5.4 7.4
5.6
6.3
7.6
7.4 9.7
Animal Cruelty***
Drug Dealing***
Assault*
Group Fight***
Caring weapon***
5.1
5.9
5.6
7.7
Theft***
Car break
Bicycle theft***
2.0
2.0
1.6
0.81.6
1.5
Burglary
muslim
11.4
orthodox and other
christian confessions
protestant
19.2
catholic
10.9
12.1
11.9
11.5
Shoplifting*
7.3
6.9
5.5
6.1 7.9
Graffiti*
5.0
15.2
11.7 14.1
5.97.0
0.0
16.6
5.9
5.66.6
4.8
4.8
Vandalism***
other
16.0
10.7
2.0
2.3 4.7
0.9
0.9
0.3
2.4 4.4
1.6
2.1
1.9
2.3
2.8
2.9
2.6
0.51.3
0.7
Robbery***
22.0
do not belong to a
religion/religion
community
16.8
9.8
10.0
11.4
10.0
15.0
20.0
25.0
32 Weighted data
33
Students who indicate Islam or religions of Asia or Africa as their affiliation have rather higher
delinquency rates. The same is true, for some offences, also for respondents who say not to
belong to any religion. In some offences, Orthodox students are also more delinquent. Catholics
and Protestants generally have the lowest delinquency rates. This result obviously can be
attributed to integration, since both Protestants and Catholics are likely from Swiss background.
Figure 1.29
Delinquency (last year prevalence) by importance of religion in %, N=4036405233
15.1
16.0
14.0
12.0
10.0
8.0
6.0
7.6
6.4
5.6
11.2
11.1
10.2
9.28.6
4.0
2.0
12.5
11.8
10.7
9.0
8.1
7.8
6.9
6.4
6.0
9.2
6.3
5.2
2.2 2.0
0.6
2.9 2.8 3.2
2.5
1.21.0 1.4
1.00.9
7.9
5.4
5.4
3.83.13.1 3.6
3.52.9
0.0
Very important
Neither/nor
Very unimportant
Most offences are reported by students for whom religion is either very important or not
important at all. This apparently paradoxical result could be related to the various attitudes of the
several religions to stealing and violence.
33 Weighted data
34
1.3.5 Economic status and delinquency
The following Figures illustrate the importance of several indicators of social and economic
conditions of the respondents’ families.
Figure 1.30
20.0
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Fathers’ employment status in %, N=4024-4041 34
17.4
16.5
12.1
11.811.5 12.5
9.4 8.5 9.1
9.3
6.5
10.3
8.1
6.0
1.3
0.0
10.5
9.3
16.5
14.5
11.812.1
9.3 9.1 9.6
7.5
7.2 7.0
8.5 9.3
5.5 5.3
3.62.4
3.1
4.2
2.4 2.0
1.2
1.11.8
he is unemployed
he is working
12.8
other
Students, whose fathers work permanently, have lower rates of delinquency. The highest
delinquency rates can be found among respondents whose fatheris unemployed. This could point
to the importance of economic strain, but might be also seen as an outcome related to other
social problems. In a country with very low unemployment rates, persons not belonging to the
workforce are likely to be confronted with other social problems, too. Similar results can be
found for mother’s employment status.
34 Weighted data
35
Figure 1.31
Mothers’ employment status in %, N=4042-406235
25.0
21.3
20.0
15.0
10.0
10.810.7
8.9
8.9
6.75.8
13.5
12.6
8.4
5.95.3 4.9
4.9
5.0
4.6
4.6
2.2
1.2 1.10.7
1.10.9
1.20.7
14.4
13.1
10.6
9.6
11.7
7.6
5.8
7.9
5.54.6 5.6 5.8
3.0
3.02.5
6.87.6 7.2
0.0
she is unemployed
she is working
other
Students are more likely to commit an offence if their mothers are unemployed and cannot find a
job. However, if mothers do not work for other reasons, the effect is quite different from what
has been observed for the father (Figure 1.30).
Figure 1.32
Source of income of the family in %, N=4016-4034 36
25.0
19.1
20.0
15.0
10.0
10.4
9.89.2
6.4
5.0
18.4
14.9
12.3
11.5
5.2
1.1
6.1 7.5
6.3
6.3
2.0
1.0
1.0
7.4
14.5
9.6
7.1
15.0
9.2
8.0
5.2
3.3
2.5
0.0
other sources of income
earnings, wages or property of my parents
35 Weighted data
36 Weighted data
36
The role of social problems other than just economic strain due to unemployment is underlined
by Figure 1.33. Indeed, respondents from families who receive their income mainly through
sources other than earnings or wages have considerably higher delinquency rates.
Figure 1.33
“How well-off is your family compared to others” and delinquency in %,
N=4026-404137
45.0
39.7
40.0
32.4
31.6
35.0
29.4
26.3
30.0
21.2
21.1
20.6
25.0
18.8
18.1 18.1
18.1
15.8
20.0
15.5
15.2
14.8
14.7
14.7
14.5
14.3
14.0
13.8
13.2
13.2
13.0
12.1
12.0
11.8 11.8
11.8
11.7
11.3
10.7
15.0 8.4 9.1
10.0
10.0
9.5
9.5
9.1
9.1
8.9
8.9
8.8
8.6
8.6
8.5
8.4
7.8
7.8
7.7
7.6
6.6
6.6
6.5
6.4
6.2 7.1
6.1
6.0
6.0 6.4 4.1 3.9
5.8 6.9 5.3
10.0 5.6
5.1
5.0 4.7
4.7
4.7 5.3 6.4
4.5
3.6
3.3
3.1
2.8
2.6
2.1
1.8
1.8
1.6 1.1
1.6
1.2
1.2 2.0
1.1
0.9
0.9
0.9
0.8
0.8
0.8
0.8
5.0
0.0
much better off
better off
somewhat better off
somewhat worse off
worse off
much worse off
the same
Students who say their family is worse and much worse off than other families have the highest
delinquency rates in general and with regard to the most serious offences in particular.
Interestingly, the difference is striking only for the extreme category (“much worse”), not really
for those who describe their family’s economic situation as just “worse” or “some worse”. It may
well be that the “much worse” category is characterized by many other social problems as well.
The relatively moderate importance of economic strain as such is further underlined by the often
also higher delinquency rates among those who say their family is “much better off”.
37 Weighted data
37
Own money to spend in comparison with others in %, N=4026-404138
Figure 1.34
25.0
22.2
19.0 17.6
18.5
16.7
16.1
15.7
15.5
14.9 15.4
13.1
12.8
12.5
15.0
12.2
11.5
10.8
10.4
10.2
10.0
10.0
9.7
9.5
9.07.8
8.7
8.6
8.6
8.3
8.0
7.9
7.7
7.5
7.5
10.0 7.56.8
7.26.5
7.2
7.2
7.0
6.8
6.87.2
6.4
6.3
6.1
5.2
5.0 4.7
5.0
4.9
4.7
4.7
4.64.14.6
4.6
3.8
3.3 2.3
3.0
2.9
2.8
2.7
2.32.8
5.0
1.8
1.8
1.8
1.4
1.4
1.4
1.3
1.3
1.1
1.1
1.1
0.9
0.8 0.9
0.8
0.8
0.80.5
0.0
20.0
much more
more
somewhat more
the same
somewhat less
less
The findings presented in Figure 1.35 illustrate this further. Also when respondents are asked
about own money they have at their disposal, it is not so much the perceived inequality with
respect to others but probably the extreme situation that is associated with higher delinquency
rates. The question, again, is whether it is lack of money or the co-occurrence of many related
social problems that lead to delinquency.
1.4 Comparison between ISRD-2 and ISRD-3
1.4.1 Trends in delinquency
Trends in delinquency over all three ISRD sweeps (1992, 2006 and 2013) are presented in
Chapter 7 (Figure 7.2). Similar trends can be seen with regard to victimization (increase from
ISRD-2 to ISRD-3, Table 4.2). In this Chapter, we are looking whether the association with
some of the independent variables considered in the preceding sections has changed.
1.4.2 Demographic characteristics and delinquency
As data not shown suggest, delinquency has, since 2006, increased in about even proportions
among girls and boys. The same is true for the several age brackets (not shown). Delinquency
has in both sweeps been concentrated among those aged 15 and above, and this gap has become
slightly more pronounced in 2013.
38 Weighted data
38
With respect to birthplace, we consider here the association between delinquency and country of
birth of the respondents (Figure 1.36).
Delinquency (last year prevalence) by respondents’ birthplace in % for 2006 and
201339
7.2
6.5
5.4
5.4
ISRD-3***
3.9
ISRD-2**
1.3
ISRD-3***
Group fight
ISRD-3***
Caring
weapon
ISRD-3***
Robbery
ISRD-3***
ISRD-3***
13.6
2.7
9.2 11.0
5.4
2.3
1.0
ISRD-2**
Car break
Assault
Drug dealing
Figure 1.35
1.2
8.7
3.2
Burglary
ISRD-3***
Shoplifting
ISRD-3
Vandalism
ISRD-3***
14.9
17.5
7.7
10.3
12.0
9.6
13.7
6.9
6.4
7.6
ISRD-2
ISRD-2
17.4
9.1
ISRD-2***
ISRD-2
13.1
10.9
6.6
0.6
0.9
0.5
0.0
1.9
0.9
2.0
1.3
2.0
0.5
0.0
0.6
1.1
1.3
1.1
1.0
0.7
0.9
ISRD-2
17.4
4.2
9.8
West Europe
11.0
Ex-Yugoslavia
3.2
7.8
4.5
15.2
12.1
12.2
ISRD-2
8.9
8.6
6.5
5.0
Switzerland
16.6
11.1
12.4
ISRD-2*
17.2
9.3
9.1
9.2
4.5
0.0
Other (countries of
Asia, Africa, N.
America, S. America, E.
Europe, C. Europe)
18.2
7.8
10.0
15.0
20.0
39ISRD-2 – not weighted data, N= 3648; ISRD-3 - weighted data, N=4158
39
Delinquency increased, over the last seven years, mostly among juveniles born in Ex-Yugoslavia
and in a residual category of “other” countries. However, it increased also among respondents
born in Switzerland. The only group with a clearly different trend are juveniles from other
Western European countries whose delinquency rate decreased for most offences.
Parents’ countries of birth are similarly associated with delinquency in 2006 and in 2013. This
holds true for fathers’ as well as for mothers’ origin (data not shown).
1.4.3 Economic status and delinquency in 2006 vs. 2013
Parental unemployment has been shown to be significantly associated with delinquency (Figures
1.18 and 1.19). The following Figure suggests that this association may have become even
stronger in 2013. Eventually, unemployment goes more along with personal and social problems
today than a few years ago.
Delinquency (last year prevalence) by fathers’ employment in % for 2006 and
2013,40
Figure 1.36
Vandalism Shoplifting Burglary
Car break
Robbery
Caring Group fight
weapon
Assault
ISRD-3**
ISRD-2
ISRD-3*
ISRD-2
ISRD-3*
ISRD-2
ISRD-3*
ISRD-2
ISRD-3***
ISRD-2**
ISRD-3***
ISRD-2
ISRD-3***
ISRD-2**
ISRD-3
ISRD-2
ISRD-3
ISRD-2
16.5
16.5
18.0
14.514.0
14.0
16.0 13.6
13.4 12.5
12.811.8
12.8
12.1
12.1
14.0
11.8
11.5
10.5
12.0
9.6
9.4 9.1 8.7
9.3
9.3
8.5
8.5
10.0
7.6
7.4
7.4
7.2
7.0
6.8
8.0
5.5
5.3
4.2 3.4
6.0
3.4
2.7 3.1 2.3
2.7
2.0
4.0
1.8
1.3
1.3
1.1
1.0
0.8
0.7
0.7
0.0
0.0 0.0
0.0
0.0
0.0
2.0
0.0
Drug
dealing
He is unemployed (he cannot find a job)
Wokrs (permanent job, own business, sometimes work)
Students whose fathers are unemployed or who do not work for other reasons are more likely to
commit an offence (both in 2006 and in 2013). However, this association became more
significant in 2013. For mother’s unemployment, the association is not as strong and the increase
is less consistent since 2006 (data not shown). It could be that unemployment of fathers and
mothers has different social meanings and that it is differentially associated with personal or
social problems.
40Weighted data (ISRD-2, N=3648 and ISRD-3, N=4158)
40
In this context, it is interesting to see that, according to Figure 1.37, the relationship between
economic well-being and delinquency of respondents is not as straightforward as one might
suspect. Although delinquency increased more, from 2006 to 2013, among those whose families
are less well off, the difference is not consistent for all offences nor is it systematically strong.
Figure 1.37
16.6
13.1
7.8
7.3
9.2 9.5 9.0
8.3
7.1
Car break
Low level
Robbery
Caring Group fight
weapon
Assault
4.8
ISRD-3***
ISRD-3*
ISRD-2
ISRD-3**
ISRD-2
ISRD-3*
ISRD-2
ISRD-3
ISRD-2
ISRD-3**
ISRD-3***
ISRD-2*
ISRD-3***
ISRD-2
Burglary
ISRD-2
5.0
3.0
2.6 1.8
1.3
1.2
2.7
2.4
2.0 1.4 2.0
1.0
0.9 1.1 1.0
0.9 1.1
0.8
Vandalism Shoplifting
7.8
ISRD-3***
9.6
8.0 7.3
12.4
11.3
ISRD-2
8.1
7.8
ISRD-2
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Delinquency (last year prevalence) by economic level in % for 2006 and 201341
Drug
dealing
Middle and high levels
This underlines, once more, the possibility that the association between parental unemployment
and delinquency is indeed mediated by higher exposure to social and/or personal problems.
41ISRD-2 – not weighted data, N= 3648; ISRD-3 - weighted data, N=4158 (4006-4021)
41
1.5 Victimization and demographic background
1.5.1 Gender and age
The ISRD is not simply a survey of self-reported delinquency, but also a victimization survey.
The following Figures show how victimization relates to gender and age.
Victimization (last year prevalence) by gender in %, N=4120-413642
Figure 1.38
40.0
29.1
24.6
30.0
18.619.5
20.0
10.0
11.3
5.0
1.6
6.0 5.3
4.4 3.3
5.9
5.6 5.3
0.0
Robbery***
Assault
Personal
theft***
Hate
male
Cyber
bullying***
Parental
violence
Parental
maltreatment
female
Males are more often victims of delinquency than females whenever violence and aggression are
involved, such as in robbery and assault. They are also more often victims of theft and hate
crimes, probably because of their greater presence in urban night-life. Girls, in turn, become
more often victims of cyber bullying and parental assault.
Figure 1.39
Victimization (last year prevalence) by age in %, N=4111-412543
32.6
30.0
26.826.3 25.5
22.4
35.0
30.0
25.0
22.8
20.9
20.020.120.0
16.0
20.0
15.0
10.0
5.0
7.1
5.1
4.8
4.6
3.6
3.6
3.6
3.1
3.0
2.4 1.8 2.4
0.0
10.3
9.2
8.5 8.4
7.9
7.6
6.2
5.4
4.6 5.4
4.4
3.6
16.4
8.4
5.7
4.8
4.8
4.6
11-12
13
14
15
16
17-19
42 Weighted data
43 Weighted data
42
Respondents become victims of all offences at all ages, except robbery and hate crimes that are
more often experienced at age 16 or older. Also victims of parental assault are more often young
men of 16 or 17. These situations may be related to domestic conflict where older adolescents
are relatively often involved – as victims, but quite often also as offenders.44
The findings in Figure 1.39 are challenging. In ISRD-2, it has often been observed that
delinquency rates in Eastern and Asian countries are extremely low, whereas victimization rates
were not. The favorite explanation had been that these juveniles may feel more inhibited to
report offences they actually had committed, than experiences as victims. Although this
possibility certainly has to be considered, it might also be that juveniles of younger ages often
experience victimizations from older peers. The results presented in Figure 1390 offer some
support to this hypothesis. Indeed, it is not very plausible why our respondents were so much
inhibited to self-report offences, and the idea that they were actually victims of somewhat older
juveniles is certainly appealing. We shall look into that when we analyze the detailed
circumstances of experienced offences, since gender, age and a few more characteristics of the
assailant have also been recorded in the questionnaire.
44
See the survey on domestic violence in the Canton of Geneva, conducted in 2012-13 by our team.
43
1.5.2 Birthplace and victimization
As mentioned above, foreign origin has been measured by recording the country of birth of
respondents and their parents. In connection with delinquency, we have seen that the fact of
having been born abroad, or of having foreign-born parents, is associated with higher rates of
delinquency (Figures 1.21-1.26). In this section, we shall look at victimization by having been
born abroad.
Figure 1.40
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year prevalence) by respondent’s birthplace in %, N=4118413245
34.3
25.6
25.1
18.2
4.0 3.1
6.3
3.4
7.4 5.3
not in Switzerland
10.2 8.4
10.2
4.7
Switzerland
Although respondents born abroad are more likely to become victims of delinquency, the
differences are less pronounced than in Figure 1.21. The same is true when parents’ county of
birth is considered (Figure 1.42).
45 Weighted data
44
Figure 1.41
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year prevalence) by parents’ birthplace in %, N=4042-405746
32.3
25.923.8
3.7 4.2 2.6
4.3 5.8 2.6
24.422.3
9.9 11.3
8.0 8.6
Both parents born NOT in Switzerland
3.1
15.1
6.8
9.6
7.2
2.4
1 of parents were born in Switzerland
Both parents born in Switzerland
Students with parents born abroad have higher victimization rates than those with both parents
born in Switzerland. As in Figure 1.25, children with one foreign-born parent seem to be more
exposed, for several types of victimizations, than those with two parents who arrived from
another country. Beyond this paradoxical finding, the differences are far more moderate in
Figure 1.41 than in Figure 1.25. Again, there is some indication that victimization and
delinquency are not as narrowly interrelated as often has been pretended. Further, offending and
victimization are by far not always intra-ethnic events. Indeed, it is not implausible that
offenders – whoever they are – may look out for victims of predatory crimes without caring
much about their socio-demographic profile.
The same observation is true with respect to countries of origin of victims. Although Swiss-born
respondents are less often victimized, the differences by country of origin are less important than
in connection with offending (see Figures 1.22, 1.24). With the exception of hate crimes, the
difference is largest with respect to maltreatment by parents.
46 Weighted data
45
Figure 1.42
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year prevalence) by birthplace in %, N=4116-413247
40.5
31.4
27.7
25.6
25.0
9.5
6.3 6.9
3.1 3.12.9 3.4 5.0
11.6
10.5
8.48.410.1
5.3 7.56.0
18.2
17.6
15.8
12.3
9.4
4.7 6.9
Switzerland
Ex-Yugoslavia
West Europe
The last item on migration included in ISRD-3 concerns the racial background of the respondent.
In Figure 1.26, we have seen that delinquency is strongly associated with racial minority status.
How does this relate to victimization?
47 Weighted data
46
Figure 1.43
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year prevalence) by minority in %, N=4114-412848
42.0 41.4
39.2
34.8 32.6
30.0
25.5
16.4
14.0
3.0
5.73.6
8.3
3.6
7.27.0
European
6.8 8.3
5.0
3.8
African
19.4
Asian
17.8
12.0
11.7
20.9
15.1
13.4
4.5
None of the above
Although racial minorities are more often victims of all sorts of offences – particularly of hate
crimes and parental maltreatment – the differences are by and large far less pronounced than in
Figure 1.26. In other words, a racial minority status seems more important for understanding
delinquency than victimization.
48 Weighted data
47
1.5.3 Different family configurations and delinquency
As we have seen in Figure 1.27, delinquency varies considerably across family constellation.
Juveniles brought up by two parents are better protected than those who are living in singleparent families or in other arrangements (home, foster parents etc.). How does this relate do
victimization?
Figure 1.44
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year prevalence) by “Who brought you up?” in %, N=4127413549
37.5
26.726.4
18.2
14.0
3.0 4.54.5
7.6 9.0
3.0
father and mother
10.0
4.9 4.5
one parent only
24.7
22.5
18.4
7.4
11.4
9.2
4.7
other situation
Students, who were brought up by both parents, are less victimized than those who grew up in
single-parent families or in other arrangements. However, the difference is minimal between
two- and one-parent families. Even for children growing up in other settings, the difference with
respect to victimization is by far not as large as it is for delinquency (Figure 1.26). Again, we see
that victimization is not distributed exactly in the same way as delinquency, and certain variables
may be important for delinquency that are not that crucial when it comes to victimization. It
might be that victimization, to some extent, is distributed more randomly, and that victims often
had the bad luck of being at the bad moment at the bad place.
49 Weighted data
48
1.5.4 Social standing and economic well-being
Respondents whose father is unemployed are considerably more often victims of parental assault
and maltreatment. Presumably unemployment goes along with domestic problems as well.
Figure 1.45
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year prevalence) by father’s employment in %, N=4093-410750
39.1
30.7
26.9
23.9
8.0
3.1 4.8
5.7 3.8 4.2
he is unemployed
20.7
5.2 6.1
10.68.5 9.7
he is working
19.0
15.1
11.5
5.3 7.8
other
Mother’s employment status, however, is clearly less important in this respect (not shown).
Similar results are found if the family’s main source of income is considered: families supported
by welfare payments are characterized by far more parental assault and maltreatment.
50 Weighted data
49
Figure 1.46
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year prevalence) by main source of income in %, N=4109412251
30.3
28.426.7
15.4
9.1
7.4
2.9
3.6
18.6
14.5
5.1
8.4
16.2
5.0
other sources of income (social wellfare, pension and so on)
earnings, wages or property of my parents
As the following Figure illustrates, this is largely true also for families who operate under
financial strain (Figure 1.47). Compared to Figure 1.32 where respondents whose families are
“much worse off” admitted to committing far more offences than those above the bottom, the
same extreme position does not seem to be associated with victimization to the same extent,
perhaps with the exception of cyber bullying and assault. Once more, it seems that variables that
are highly correlated to delinquency are not that much related to victimization.
51 Weighted data
50
Figure 1.47
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year) by “how well-off is your family compared to others” in
%, N=4100-410952
38.2
35.0
32.4
27.3
26.6
25.024.1
19.3
11.8
8.8
8.8
7.7
6.5
5.2
4.9
4.5
3.6
3.6
3.2
2.7
2.0
40.4
31.6
29.4
15.1
12.3
11.811.8 9.7
10.2
8.1
7.4
7.1
6.6
5.8
3.5
much better off
better off
somewhat better off
somewhat worse off
worse off
much worse off
33.3
20.8
20.6
18.2
17.7
17.3
19.3
12.7
9.4
9.1
5.3
4.0
2.6
the same
The same is true with respect to money respondents have at their disposal for their own needs.
Although students with much less resources than others are more often victims of all types of
offences, the association is clearly more gradual and continuous.
52 Weighted data
51
Figure 1.48
Victimization (last year prevalence) by own money compared to others in %,
N=4090-410153
45.0
38.8
38.5
40.0
33.6
32.0
31.1
35.0
30.2
29.1
28.0
30.0
22.8
22.6
25.0
18.7 20.8
18.6
16.8
16.6
20.0
15.2
12.7
11.2 11.1
10.3
15.0 10.2
10.1
10.1
10.0
9.5
9.5
9.0
8.9
7.8
7.1
6.5
6.3
6.3
5.6
10.0
5.2
4.8
4.7
4.6
4.3
4.3
3.5 4.1 3.9
3.5
3.3
3.3
2.2
2.1
2.1
5.0
0.0
much more
more
somewhat more
the same
somewhat less
less
much less
Compared to Figure 1.34, the distribution in Figure 1.48 is again far more continuous. If poor
people are far more involved in delinquency, they are not necessarily that much more often
victims of offences.
53 Weighted data
52
1.6 Conclusions: Factors of delinquency and victimization







Delinquency is committed disproportionally by boys.
The age of culmination is in the range of 16 years.
The number of students born abroad, or having parents born abroad is increasing.
The number of students born in Ex-Yugoslavia has decreased since 2006, but
delinquency of this group has increased. On the other hand, students from Western
European countries have increased, but they reported fewer offences in 2013 in
comparison with 2006.
Respondents with parents born abroad are more delinquent than their peers with parents
of Swiss origin. The difference is less strong than with many other variables and not
entirely consistent across offence types.
Students brought up by two parents are least often involved in delinquency and less often
victimized.
Unemployment among mothers and fathers has increased since 2006. It is associated with
higher delinquency rates. Students from poor families are far more often involved in
delinquency. With respect to victimization, the association is less strong.
53
Chapter 2
Family, parental control and delinquency
2.1 Overview
Module 2 of the questionnaire includes an expanded measure of family life and bonding
(parental control, parents’ supervision) with lots of variables. In this chapter we discuss only
issues of dinner with family and parental control as among the most influential for juvenile
delinquency.
2.2 Family life and parental control across regions
2.2.1 Dinner with family
“How many days a week do you usually eat an evening meal with your
parent(s)?” by main and subsamples in %54
Figure 2.1
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
72.0
18.7
9.3
Switzerland
(N=4'158)
77.1
85.4
68.7
63.9
24.5
21.3
10.0
14.1
8.7
11.3
3.2
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
never/1-2 times a week
11.6
SG
(N=625)
3-5 times a week;
68.2
20.4
11.4
AG
(N=555)
70.5
16.4
13.1
GE
(N=268)
67.1
23.7
9.2
ZH
(N=266)
6 times/week - daily
72% of respondents reported about eating an evening meal together with parents 6 times per
week or daily. This tradition is the most developed in Italian speaking (85.4%) and in French
speaking cantons (77.1%), particularly in the canton of Geneva it is 70.5%. Such level is the
lowest in German speaking cantons (68.7%), for instance in the canton of Zurich (67.1%). One
reason may be that juveniles attend in highly urbanized areas like Zurich often schools at some
distance from their homes.
More than 80% of respondents in age of 11-12 have a dinner with their families 6 times per week
or daily. This percentage is decreasing with age. For instance, 65% among the 15 years old
54 Weighted data
54
students eat dinner almost every day at home. By 16 years, this proportion drops to57%
(p=.000).
Among those reportingto eat dinner with their families “never or 1-2 times per week”, 7.4% have
mothers born in Switzerland, and 12.2% abroad. Among mothers born abroad, 18.2% were born
in Asia including Oceania, 20.5% in Eastern/Central Europe and 23.1% in the countries of South
and North Americas. 14.6% were born in Ex-Yugoslavia, except Kosovo. The lowest percentage
of mothers was born in Kosovo (4.4%) and Portugal (3.8%).
Figure 2.2
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
“How many days a week do you usually eat an evening meal with your
parent(s)?” in % for 2006 and 201355
76.1
72.0
18.7
16.9
9.3
7.0
ISRD-2 (N=3'643)
ISRD-3 (N=4'158)
3-5 times a week;
Having dinner at home has changed little since 2006. In 2013 slightly more students than in 2006
reported having dinner with parents once or twice per week or never.
55 ISRD-2 – not weighted data, ISRD-3 - weighted data
55
2.2.2 Parental control
The following Figures inform on how parents try to control their offspring.
“My parents know where I am when I go out” in %56
Figure 2.3
100.0
90.0
88.5
85.9
80.0
88.8
88.6
86.4
79.4
77.2
60.0
40.0
7.73.9
14.7
5.9
6.93.1
9.8
3.8
7.63.8
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
20.0
9.7
4.5
14.7
8.0
6.15.1
GE
(N=268)
ZH
(N=266)
0.0
always
sometimes
rarely
This is one of the best controlled fields by parents. Only 4.5% and of respondents reported that
their parents rarely know where they are when they go out. Such percentage is slightly higher in
French speaking cantons and in Zurich.
Figure 2.4
80.0
“My Parents know what I am doing when I go out” in %57
71.4
75.3
73.6
73.0
72.2
66.0
70.0
70.0
71.0
60.0
50.0
40.0
30.0
20.0
17.9
10.7
10.0
17.1
9.3
20.2
13.7
14.6
10.1
17.2
9.9
17.8
10.1
15.3
14.7
19.6
9.5
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
always
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
rarely
56 Weighted data
57 Weighted data
56
If parents usually know where their children spend time, they are obviously less well informed
about what they do when they go out.
Figure 2.5
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
“My parents know what friends I am with when I go out” in %58
83.7
81.9
83.4
77.7
82.3
81.2
84.6
80.2
11.5
4.8
13.7
8.6
10.9
5.8
13.3
5.5
14.1
3.6
10.98.9
10.0
5.4
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
12.1
6.0
always
sometimes
rarely
Most parents know friends of their children.
Figure 2.6
“My parents know friends I am with when I go out”. In % for ISRD-2 and ISRD359
100.0
81.9
80.0
60.7
60.0
33.9
40.0
20.0
12.1
6.0
5.4
0.0
ISRD-2 (N=3'643)
rarely/never
ISRD-3 (N=4'158)
sometimes
always
In 2013 compared to 2006, more parents always know whom their children spend time with
while going out. Cell phones obviously make control of the whereabouts of children much easier
for parents.
58 Weighted data
57
“If I have been out, my parents ask me what I did, where I went and who I spent
time with” by main and subsamples in %60
Figure 2.7
80.0
73.8
71.2
74.0
73.5
73.3
65.1
70.0
74.7
68.1
60.0
50.0
40.0
30.0
20.0
10.0
19.1
9.7
18.5
7.7
20.9
14.0
16.5
10.0
18.1
7.9
16.9
9.8
SG
(N=625)
AG
(N=555)
18.9
13.0
18.1
7.2
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
always
sometimes
GE
(N=268)
ZH
(N=266)
rarely
About one third of parents sometimes or rarely know where and whom their children spend
leisure-time with. This proportion does not vary much across regions.
Figure 2.8
100.0
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
"If I go out in the evening my parents tell me when I have to be back home" in
%61
85.6
86.1
89.8
83.9
85.7
84.0
87.7
84.7
9.0
4.9
9.07.0
6.43.8
10.3
4.0
8.97.2
7.25.1
11.9
3.4
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
8.95.5
always
sometimes
rarely
Most parents always tell their children when to come home after going out.
60 Weighted data
61 Weighted data
58
Has to let parents know if it gets late in %62
Figure 2.9
100.0
80.0
88.9
79.5
78.4
77.0
74.1
76.8
82.3
74.8
60.0
40.0
20.0
12.98.7
13.0
7.5
13.9
12.0
13.79.5
12.4
10.6
6.05.1
14.8
10.4
12.2
5.5
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
always
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
rarely
Most of students must always call their parents when they are returning later than planned. This
percentage is the highest in Ticino. Cell-phones make keeping parents informed much easier.
Parents check on homework in %63
Figure 2.10
60.0
50.0
40.0
30.0
48.9
54.0
52.1
52.1
50.2
55.2
51.0
38.8 41.3
29.7
21.4
23.8
22.2
20.0
27.9
20.0
19.8
32.7
30.5
25.7
22.1
19.3
16.4
24.7
20.1
10.0
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
always
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
rarely
Parents seem to exercise less control on school homework. About half of parents do not check if
their children did their homework. This percentage is the highest in the canton of Zurich where
55.2% of parents rarely check their homework. In Romandie and Ticino, more parents always
check their children’s homework. There is almost no correlation between delinquency and
checking homework by parents.
62 Weighted data
63 Weighted data
59
“I tell my parents who I spend time with” in %64
Figure 2.11
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
75.8
70.4
19.8
9.8
24.1
15.9
17.6
6.6
Switzerland
DE
(N=4'158) (N=2'560)
63.5
62.1
60.1
FR
(N=956)
23.3
14.7
ITA
(N=642)
always
78.8
75.8
74.5
16.6
8.8
16.7
7.5
SG
(N=625)
AG
(N=555)
sometimes
18.9
17.6
GE
(N=268)
12.09.2
ZH
(N=266)
rarely
This type of parental control is very different across regions. Children in Romandie keep their
parents less regularly informed about whom they spend time with. Roughly two in five students
keep their parents informed about what they during leisure-time in general, during afternoonhours or what they spend their money for (not shown). These habits hardly differ across regions.
Figure 2.11_1
Experiencing any of the following events in %65
60.0
50.0
20.0
10.0
41.3
38.0
40.0
30.0
49.9
46.6
41.7
25.9
20.6
10.2
7.7 9.7
30.7
21.6
19.4
15.5
4.4
2.4 4.1
3.7
7.8
7.1
43.0
41.5
40.5
32.3
20.6
20.0
4.3
3.7 4.3
23.6
14.9
3.6
2.0 2.0
22.7
19.4
18.0
17.3
14.1
6.5
5.5
4.5
3.5 4.7
2.4 3.8
1.7 4.2
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
death of father/mother
serious illness of parents
parents alcohol/drugs
violence between parents
serious conflicts bw parents
sep/divorce of parents
ZH
(N=266)
French speaking cantons have one of the highest levels of negative events that were reported by
respondents.
64 Weighted data
65 Weighted data
60
2.3 Family life, parental control and delinquency
2.3.1 Family life and delinquency
Among the many variables on family life collected in module 2 of the questionnaire, taking
evening meals with parents turned out to be particularly relevant.
Delinquency (last year prevalence) by “How many days a week do you usually
eat an evening meal with your parent(s)?” in %, N=4046-406266
Figure 2.12
25.0
20.1
20.0
15.0 13.0
10.0
16.4
14.2
8.7
5.4
5.0
16.2
10.8
7.1
4.8
11.5
10.1
10.9
8.2
5.4
1.21.1
14.9
12.4
6.4
2.41.6 2.72.12.2 2.41.8
1.2
1.1
14.4
10.8
10.1
8.7
7.6
6.3 7.2
5.9
3.9 4.13.2
3.9
2.5
0.0
3-5 times a week;
Frequency of having dinner with parents relates significantly to delinquency. Respondents who
rarely eat with their parents commit more offences of all types.
66 Weighted data
61
2.3.2 Parental control and delinquency
The following Figures all relate to parental control. The frequencies and the regional distribution
have been presented in the first part of this chapter.
Figure 2.13
50.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Delinquency (last year) by "My parents know where I am when I go out" in %,
N=4050-406767
45.1
34.6
29.7
25.9
13.5
4.9
24.4
16.0
7.2
9.6
23.8
11.4
2.0
0.8
14.9
4.5
30.4
20.3
14.6
10.3
8.6
7.6 5.4
5.7
3.3 1.4
2.3
0.9
0.8
always
sometimes
7.8
29.2
15.6
5.4
31.6
17.0
14.1
8.0
4.5
3.9
3.5
3.0
2.2
rarely
This Figure shows that respondents whose parents are rarely aware of their children’s
whereabouts are committing far more offences of all types. For instance, more than 11% of
students who rarely kept their parents informedof their whereabouts admitted having
committedburglary, in comparison to only less than 1.0% among those whose parents always
were informed about this. This difference is consistently strong for all serious offences.
67 Weighted data
62
Figure 2.14
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Delinquency (last year prevalence) by "My parents know what I am doing when
I go out" in %, N=4050-406868
35.7
27.3
25.1
20.2
19.0
12.9
10.1
7.4
6.1
4.1
8.5
5.2 4.4
1.5
0.8
22.6
20.8
16.7
11.8
7.1
6.1 4.7
4.8 3.8
1.0
0.8
0.7 1.1
0.5
always
sometimes
13.0
9.7
6.7
4.7
21.8
9.4
7.1
4.0
2.9
2.1
7.0
4.0
3.0
rarely
The association is precisely the same when we look at whether or not parents are informed about
what their children are doing when going out. For the following Figures, the findings are
basically showing always the same mechanism.
Delinquency (last year prevalence) by “My parents know what friends I am with
when I go out” in %, N=4047-406369
Figure 2.15
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
34.4
24.6
20.0 18.0
16.0
24.1
18.4
16.3 15.5
4.4
7.3
19.6
10.0
16.4
13.0
5.7
2.9 4.7
0.9
6.1
6.1 5.5
4.1 5.1
2.9
1.8
1.5
0.9
0.9
always
sometimes
7.8
22.5
13.8
5.4
23.2
12.7 11.5
8.2
5.5
3.5
3.2 5.1
1.8
rarely
68 Weighted data
69 Weighted data
63
Delinquency (last year prevalence) by “My parents know what friends I am with
when I go out” in % for ISRD-2 and ISRD-370
Figure 2.16
Vandalism Shoplifting Burglary
Car break
Robbery
rarely/never
sometimes
Caring Group fight
weapon
Assault
ISRD-3***
ISRD-2***
ISRD-3***
ISRD-2***
ISRD-3***
ISRD-2***
ISRD-3***
ISRD-2***
ISRD-3***
ISRD-2***
ISRD-3***
ISRD-2***
ISRD-3***
ISRD-2***
ISRD-3***
ISRD-2***
ISRD-3***
ISRD-2***
45.1
50.0
34.6
40.0
31.6
30.4
29.2
25.0
24.5
30.0
22.5 24.4
21.8
20.3
14.1 11.4 17.0
20.0 12.3 16.0 12.0 9.6
12.5 15.6
11.4
10.8
10.3
8.6
7.8
7.7
7.2
7.0
6.6
5.8
5.4 1.8 8.0
5.4
5.4
4.8
4.7
10.0
1.7 3.0
1.5
1.2
0.9
0.8 1.5
0.5 2.2 3.4
0.4 2.3
0.4 2.0
0.4 1.4 3.2
0.0
Drug
dealing
always
The association between parents’ control about their children’s whereabouts and delinquency has
remained unchanged from 2006 to 2013. Although parents may control better than a few years
ago their children’s night-time activities, this control, probably facilitated by the widespread use
of cell phones, may remain largely limited to geographic location but not really allow parents to
control what children actually do.
Figure 2.17
20.0
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Delinquency (last year prevalence) by "If I have been out, my parents ask me
what I did, where I went and who I spent time with" in %, N=4046-406471
17.8
14.0 14.5
11.7 11.8 11.5
8.3
5.6
13.8
12.5
11.2 11.2
9.1
8.5
7.8
7.1
6.6
12.7
8.0
7.4
5.3
2.3
2.1
1.1
4.6
3.6 2.7
2.3
1.3 1.8
1.3
1.2
1.0
always
sometimes
9.9
6.3
5.1 4.8
3.0
2.9
4.7
3.4 3.1
rarely
71 Weighted data
64
Apparently, parents of delinquent juveniles ask less about where, with what and with whom they
had spent time. This could indicate that the lack of parental information might be related to a
lack of parental active control, or a lack of parents’ interest for what their children are doing
during leisure-time and when going out.
Figure 2.18 Delinquency (last year prevalence) by "If I go out in the evening my parents tell
me when I have to be back home" in %, N=4041-405872
25.0
23.2
22.9
21.0
19.7
20.0
15.8
15.7
15.0
10.0
12.8
12.0
8.1
6.0
9.4
8.5
5.0
22.5
16.0
14.2
11.4
6.9
2.5
0.9
8.3
5.4
9.2
6.9
1.7
0.9
2.2
1.8
4.6
2.5
1.0
7.3
5.8
11.4
8.8
6.2
4.7
2.5
7.2
4.8
8.2
3.4
3.3
0.0
always
sometimes
rarely
Respondents whom the parents rarely or never tell the time they have to be back home are
committing more offences of all types. This again points to a possible lack of parental initiative
and involvement in how their children shape leisure-time activities.
72 Weighted data
65
Delinquency (last year prevalence) by “If I am out and it gets late I have to call
my parents and let them know” in %, N=4045-406073
Figure 2.19
30.0
25.0
20.0
15.0
10.0
24.2
24.2
19.8 20.2
16.2 16.1
10.6
5.0
19.7
14.2
10.3
10.1
7.0
5.3 4.9
1.5
1.0
5.0
4.5
3.3
3.3 3.1
2.5
1.8
1.3
1.1
0.9
9.9
5.9
18.9
8.6
8.3
7.5
6.2
16.4
8.7 8.2
5.6
3.9
2.2
5.8
5.0
3.1
0.0
always
sometimes
rarely
Again, juveniles who do not have to inform their parents about being late when returning home
are committing more offences of all kinds.
Figure 2.20
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Delinquency (last year prevalence) by "My parents check if I have done my
homework" in %, N=4048-406574
11.7
14.2
13.1
11.4
11.0
9.7
7.9
7.1
6.7
6.0
5.2
8.0 8.6
7.3
5.7
5.4
1.8
1.3
0.7
5.0
2.4
2.0
1.6 1.5 2.1
1.4
1.4
1.0
0.8
always
sometimes
7.2
8.3
7.2
6.5
8.1
4.3
3.2
3.2
2.7
1.4
4.0
3.4
2.9
rarely
73 Weighted data
74 Weighted data
66
Contrary to other forms of parental control, checking children’s homework is only weakly,
inconsistently and mostly not significantly related to delinquency.
Figure 2.21
Delinquency (last year prevalence) by "I tell my parents who I spent time with"
in %, N=4041-406175
35.0
29.0
30.0
22.9
25.0
20.0
15.0
10.0
5.0
18.5
18.3
9.6
4.3
20.7
12.6
11.5
11.9
6.6
8.7
6.3
1.8
0.6
4.1
11.9
6.3
5.3 4.7
4.5 3.5
1.9
1.5
1.3
0.7
0.7
23.0
20.5
16.8
13.9
11.1
7.1
4.8
9.8
4.1
2.1
8.5
3.3
4.1
3.8
3.5
0.0
always
sometimes
rarely
There is a significant relation between delinquency (last year prevalence) and informing parents
about whom respondents spend time with.
75 Weighted data
67
Delinquency (last year prevalence) by “I tell my parents how I spend my money”
in %, N=4047-406476
Figure 2.22
23.3
25.0
19.4
20.0
15.0
10.0
5.0
20.3
17.7
14.7
7.3
4.4
9.9
6.4
12.3
8.0
17.2
15.6
8.3
5.0
3.5
3.3 2.6
1.1 1.3
1.1
1.0
0.8
4.5 4.2
1.2
0.7
8.2
5.4
14.7
10.2
7.2
7.0
5.1
8.3
3.2
1.9
7.4
2.6
4.7
3.4
3.3
0.0
always
sometimes
rarely
Parental control over financial matters is also related to delinquency, although not as strongly as
control over leisure-time in general.
Figure 2.23
Delinquency (last year prevalence) by "I tell my parents where I am most
afternoons after school” in %, N=4047-406577
25.0
20.0
15.0
20.7
15.5
5.0
14.1
10.3
10.0
4.1
23.4
22.7
5.9
23.8
15.9
13.9
10.6
11.7
8.1
4.9 3.9
2.0
0.6
5.1
4.9
3.7 4.8
3.7
2.1 1.1
1.6
0.8
0.7
16.7
13.5
6.5
14.8
11.5
8.3
4.8
3.5
2.2
9.2
2.9
5.2
4.4
3.1
0.0
always
sometimes
rarely
76 Weighted data
77 Weighted data
68
Also control over afternoon-hours is somewhat related to delinquency. Respondents who always
keep their parents informed about where they spend after-school hours commit substantially
fewer offences of all sorts. This is in line with observations in other studies (e.g. Walser 2013)
that a non-trivial part of offending tends to occur in the later afternoon, after school hours.
2.4 Conclusions
Family life and parental control play an important role in students’ life. It is strongly related to
juvenile delinquency. For instance, children, whose parents do not know where and with whom
their children spend time when they go out, are more likely to commit any type of offences. At
the same time parental control like checking homework is only weakly associated with
delinquency.
Over time, parental control did not change that much since 1992 (ISRD-1). Parents of most
children still fixed hours for returning home and they were informed about their children’s
whereabouts at similar proportions. From this perspective, it is not easy to understand why
delinquency did increase that much over time, from 1992 to 2006 and from 2006 to 2013, as
shown in Chapter 7. Perhaps the relevant changes are not really measured through questions like
these, i.e. questions regarding hours and locations of going out, but more about what actually
occurs during these moments. This obviously is hard to measure, particularly since it is hard to
anticipate in advance what might be relevant in a few years.
69
Chapter 3
Attitudes towards and perceptions about the school, school performance and
delinquency
2.1 Overview
In this chapter, we shall analyse delinquency in the light of several school variables, namely

students' feelings about their school, i.e. whether they like their school, whether they
would miss their school in case they had to move, whether they like going to school in
the morning, whether they find classes interesting, whether they would miss their teacher
in case of a change, and how important it is to them what their favourite teacher thinks
about them,

how students perceive the school environment, i.e. whether they see there a lot of
stealing, vandalism, fighting or drug use, and

how students describe their own performance and behaviour at school, i.e. whether they
see themselves as good or rather poor students, whether they have repeated a grade
during their career, what their future plans are (in terms of education) and whether or not
they have engaged in truancy.
These school variables are measured by module 3 of the questionnaire.
In section 3.2, the distribution of these school variables across Switzerland’s several subsamples
will be presented. In the following section, we shall see how these several school variables relate
to self-reported delinquency. In the final section (3.4), the results will be summarized and
discussed.
70
3.2.1 Feelings about school
Question 3.1 (see appendix 9.1) was about the student’s attitude towards his/her school. We first
present the answers across the several subsamples.
“If I had to move, I would miss my school” by main and subsamples in %78.
Figure 3.1
100.0
80.0
60.0
40.0
20.0
0.0
85.4
85.1
14.9
14.6
Switzerland
DE
(N=4'158) (N=2'560)
85.3
80.7
14.7
19.3
FR
(N=956)
ITA
(N=642)
disagree
89.2
86.7
10.8
13.3
SG
(N=625)
AG
(N=555)
84.8
77.9
22.1
15.2
GE
(N=268)
ZH
(N=266)
agree
More than 80 per cent of students would miss their schools if they have to move. This proportion
holds constantacross language and regions. The attachment seems weakest among students in
Zurich.
“Most mornings I like going to school” by main and subsamples in %79
Figure 3.2
80.0
60.0
40.0
20.0
0.0
65.4
34.6
70.6
56.0
44.0
72.2
46.753.3
27.8
34.4
ITA
(N=642)
SG
(N=625)
AG
(N=555)
disagree
agree
29.4
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
65.6
56.7
43.3
72.2
27.8
GE
(N=268)
ZH
(N=266)
About one third of respondents do not like going to school in the morning. This proportion is
higher in French speaking cantons and particularly in the canton of Geneva than in German
speaking cantons and especially in the canton of St. Gall. The difference between Geneva and St.
Gall is rather high (43 vs. 72% liking to go to school in most mornings). Generally, the attitude
towards the school is less positive when concrete situations are being presented, as in Figure 3.2,
than in more abstract or hypothetical situations, as in Figures 3.1 and 3.2.
78 Weighted data
79 Weighted data
71
“I like my school” by main and subsamples in %80.
Figure 3.3
100.0
80.0
60.0
40.0
20.0
0.0
80.8
77.3
22.7
19.2
Switzerland
DE
(N=4'158) (N=2'560)
71.9
83.5
76.3
64.1
28.1
35.9
FR
(N=956)
ITA
(N=642)
disagree
82.8
73.5
16.5
23.7
26.5
SG
(N=625)
AG
(N=555)
GE
(N=268)
17.2
ZH
(N=266)
agree
As in Figure 3.1, the results do not differ much across regions in Figure 3.3. Schools seem most
popular in St-Gall and least so in Ticino.
The same differences, as in Figure 3.2., appear when the question turns to the interest students
have in following lessons (Figure 3.4). Apparently, students in Geneva and in Ticino find their
lessons less interesting than in the canton of St-Gall.
“Our classes are interesting” by main and subsamples in %81.
Figure 3.4
80.0
66.4
69.1
60.0
40.0
33.6
30.9
62.4
37.6
74.9
55.9
44.1
68.2
66.7
49.550.5
25.1
33.3
31.8
20.0
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
disagree
agree
AG
(N=555)
GE
(N=268)
ZH
(N=266)
The differences across regions are substantial, although nearly two students in three feel the
lessons at school are interesting.
The question whether or not students would miss their teacher in case they had to move allowed
to grade answers in six levels. Figure 3.5 gives the detailed replies. In Figure 3.6, the scope of
possible answers is reduced to a scale of three levels.
80 Weighted data
81 Weighted data
72
“If I had to move, I would miss my teacher” by main and subsamples in %82.
Figure 3.5
40.0
33.6
33.5
35.0
30.0
30.0
27.1
29.4
28.8
24.9
25.0
29.2
25.4
21.3
20.4
20.1 21.1
19.6
19.0 18.4 20.3
18.717.8
17.8
17.7
20.0 16.3
16.8
15.616.0
15.5 14.9
15.2
14.3
14.0 13.1
13.7
13.6
13.4
13.4
12.2
15.0
11.610.3
10.6
8.5
7.5
10.0
6.3
6.3
6.3
6.0
5.9
4.5
4.0
5.0
0.0
Switzerland
DE
(N=4'158) (N=2'560)
not at all
Figure 3.6
60.0
40.0
FR
(N=956)
not much
ITA
(N=642)
only a bit
SG
(N=625)
somewhat
AG
(N=555)
quite a lot
GE
(N=268)
ZH
(N=266)
very much
“If I had to move, I would miss my teacher” (same as Fig. 3.5, reduced to 3
categories) in %.83
45.9
30.0
24.1
46.0
28.9 25.0
45.3
33.9
20.8
47.0
31.1
21.8
FR
(N=956)
ITA
(N=642)
48.7
22.5
28.8
45.6
46.5
43.1
27.9 26.5
51.4
23.7 24.9
10.3
20.0
0.0
Switzerland
DE
(N=4'158) (N=2'560)
I will NOT miss my teacher
SG
(N=625)
A bit (neither/nor)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
I will miss my teacher
In all regions of Switzerland students would somewhat miss their teachers if they have to move.
Nearly one student in two would not miss their teacher in Geneva. In the other regions, however,
differences across subsamples are not as pronounced. Apparently, the popularity of teachers in
only moderately related to school attachment.
The following Figures 3.7 and 3.8 present the results concerning students’ attitudes towards their
image among teachers. Figure 3.7 gives the results in six, Figures 3.8 in three levels.
82 Weighted data
83 Weighted data
73
Figure 3.7
“It is important for me, how my favourite teacher thinks about me” by main and
subsamples in %84.
36.3
40.0
35.6
31.8
31.8
31.2
35.0
29.5
26.8
26.7
30.0
25.8
24.7
23.3
23.121.3
22.6
25.0
20.4
20.2
18.7
18.6
18.6
18.218.3
17.0
20.0 14.816.2
12.3
12.1
11.711.2
11.7
15.0
10.4
10.1
9.610.6 8.2
9.5 9.8 9.2 8.9 10.1 9.7 9.8
9.0
8.7
8.3
7.5 6.7 6.1
7.2
10.0
5.0
0.0
Switzerland
DE
FR
ITA
SG
AG
GE
ZH
(N=4'158) (N=2'560)
(N=956)
(N=642)
(N=625)
(N=555)
(N=268)
(N=266)
totally unimportant
quite unimportant
a bit unimportant
a bit important
quite important
very important
For most students, it is “a bit important” and “quite important” what their favourite teacher
thinks about them. In some regions, however, a sizeable proportion of students do not care what
their teacher thinks about them.
Figure 3.8
60.0
40.0
“It is important for me, how my favourite teacher thinks about me” (same as Fig.
3.7, reduced to 3 categories) in %85
45.7
24.2 30.0
49.8
20.9
29.3
38.8
32.7
28.4
20.0
48.1
33.4
18.5
48.8
35.0
16.2
ITA
(N=642)
SG
(N=625)
49.9
19.5
30.6
45.9
36.0
18.1
54.2
30.8
15.0
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
Not at all
A bit (neither/nor)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
Important
Overall and especially for the main sample, the distribution is almost perfectly normal. Most
students feel that their teacher’s opinion is “a bit important” or “a bit unimportant”. Notable
exceptions are Ticino and St-Gall where students care much more about their teacher’s opinion,
and Geneva at the opposite side of the distribution.
84 Weighted data
85 Weighted data
74
3.2.2 Perceptions about the school environment
Students have been asked whether stealing, fighting, drug use or vandalism is common or not at
their school. The results are given in the following Figures 3.9-3.12.
“There is a lot of stealing in my school” in %.
Figure 3.9
100.0
80.0
60.0
40.0
20.0
0.0
78.2
77.6
22.4
21.8
Switzerland
DE
(N=4'158) (N=2'560)
76.4
77.3
23.6
22.7
FR
(N=956)
ITA
(N=642)
disagree
84.9
76.3
78.7
23.7
18.6
21.3
AG
(N=555)
GE
(N=268)
ZH
(N=266)
15.1
SG
(N=625)
81.4
agree
For Switzerland as a whole,one respondent in four agrees with the statement that stealing is
common at his/her school. This proportion does not differ much across regions, with the
exception of St-Gall where only 15 per cent say that there is a lot of stealing at their school.
“There is a lot of fighting in my school” in %86
Figure 3.10
100.0
82.6
82.8
83.7
80.0
93.3
73.3
81.5
87.4
82.4
60.0
40.0
20.0
17.4
17.2
16.3
26.7
6.7
18.5
12.6
17.6
AG
(N=555)
GE
(N=268)
ZH
(N=266)
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
disagree
SG
(N=625)
agree
The prevalence of fighting seems to vary more across regions. More than one quarter of students
say fighting is common at their school in the canton of Ticino, but only 16 and 17 per cent in
German and French speaking cantons respectively; and less than 10 per cent in the canton of StGall.
With respect to vandalism at school, there is again a fairly constant proportion of students who
report this being common at their school, with Ticino and St-Gall being the exceptions.
86 Weighted data
75
“Many things are broken or vandalized in my school”by main and subsamples in
%.87
Figure 3.11
100.0
80.0
60.0
40.0
20.0
0.0
82.6
17.4
82.8
17.2
Switzerland
DE
(N=4'158) (N=2'560)
83.7
16.3
FR
(N=956)
73.3
93.3
26.7
6.7
ITA
(N=642)
disagree
SG
(N=625)
81.5
87.4
82.4
18.5
12.6
17.6
AG
(N=555)
GE
(N=268)
ZH
(N=266)
agree
In the case of Ticino, it might be that the high prevalence of vandalism at schools is influenced
by the presumably high prevalence of graffiti and broken objects in the public space in
neighbouring Italy. However, the rather even distribution across regions may also reflect a
nation-wide policy among schools to swiftly replace or remove broken items.
87 Weighted data
76
“There is a lot of drug use in my school” by main and subsamples in %.88
Figure 3.12
100.0
80.0
81.0
79.4
86.7
84.6
74.9
85.3
60.0
40.0
20.6
20.0
36.4
25.1
19.0
72.1
63.6
15.4
13.3
14.7
ITA
(N=642)
SG
(N=625)
AG
(N=555)
27.9
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
disagree
GE
(N=268)
ZH
(N=266)
agree
Drug use (presumably of cannabis) seems also to vary substantially across regions. In Frenchspeaking cantons, one respondent in four says drug use to be common at his/her school, whereas
only 19 and 15.4 per cent say so in the German and Italian speaking cantons. Noteworthy are the
high proportions in Geneva and in Zurich (36 and 28 per cent) and the low rate in St-Gall (13.3
per cent). There is a fairly strong association between perceived drug use among fellow-students
and respondents’ own drug use (see Figure 3.26).
3.2.3 Performance at school and truancy
Students have been asked whether they see themselves as good (or rather poor) students, whether
they ever have, during their school career, repeated a grade and whether or not they have stayed
away from school during an entire day (at least) during the last 12 months without any legitimate
excuse.
Figure 3.13
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
“How well do you do at school?” by main and subsamples in %.89
50.1
41.8
8.1
Switzerland
(N=4'158)
49.3
43.2
52.3
40.1
51.6
38.9
53.7
39.8
50.9
40.5
7.5
9.5
7.6
6.5
8.6
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
Bad
Average
58.3
38.4
55.8
39.2
3.3
5.0
GE
(N=268)
ZH
(N=266)
Good
88 Weighted data
89 Weighted data
77
One half of respondents in Switzerland identify themselves as good students. This percentage is
relatively stable across all regions. However, students in the canton of Geneva rank themselves
more often as “good students”. This strangely contrasts with the findings reported above where
students in Geneva often seem to have more problematic attitudes towards their school and
teachers.
Repeating grades by main and subsamples in %.90
Figure 3.14
100.0
80.0
60.0
40.0
20.0
0.0
84.0
16.0
85.4
14.6
Switzerland
DE
(N=4'158) (N=2'560)
79.7
20.3
FR
(N=956)
91.3
85.2
83.3
8.7
14.8
16.7
ITA
(N=642)
SG
(N=625)
AG
(N=555)
no, never
yes
87.7
71.7
28.3
12.3
GE
(N=268)
ZH
(N=266)
The percentage of respondents who report having ever (i.e. at least once), during their career,
repeated a grade is slightly higher in French speaking cantons (20.3%) and clearly lowest in
Ticino (8.7%). This suggests that policies seem to be rather similar across Switzerland in this
respect.
90 Weighted data
78
Figure 3.15
Plans for future educations, after the compulsory school by main and subsamples
in %.91
60.0
52.0
50.0
40.0
10.0
24.2
14.2 13.3
2.7
1.3
45.5
38.0
37.1
31.4
30.0
20.0
45.4
44.7
43.2
46.2
15.6
3.3
12.2
1.6
29.8
27.0
15.9
12.5
10.4
1.1
1.0
20.3
17.4
19.0
18.6
4.1
0.4
4.9
9.3
1.9
19.3 19.3
18.3
15.7
11.6 13.0
3.8
13.5 13.5
3.7
1.5
1.4
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
looking for a job
start apprenticeship
vocation school/learn trade
school to prepare acad. degree (University)
other
I do not know yet
Plans for future education after having finished the current (compulsory) school differ
considerably across regions and cantons. In French- and Italian-speaking cantons, higher
education (leading to University studies) clearly leads over other options, whereas nearly one in
two opts for an apprenticeship in German speaking cantons.
Immediately applying for a job after finishing the current school is not a popular option in the
country taken as a whole. Only 2.7 per cent envisage this option, with rather small differences
across regions and cantons. In Geneva, nobody has opted for this alternative, underlining the
high value attributed to higher education among students in this canton.
There are some correlations between attitudes towards school and performance at school.
Respondents who rate themselves as “good” students generally like their school more than
others, they would miss it more, like more going to school in the morning and find classes more
interesting.
91 Weighted data
79
Figure 3.16
100.0
80.0
60.0
40.0
20.0
0.0
Feelings about school, by performance as a student in %, N=4137.
86.0
85.0
80.8
49.7
37.0
30.2
19.2
15.0
14.0
disagree
agree
If I had to move, I would
miss my school*
81.2
74.4
68.1
69.8
63.0
50.3
disagree
agree
disagree
Most mornings I like
going to school***
Bad
44.8
37.7
28.2
31.9
25.6
18.8
agree
disagree
I like my school***
Average
71.8
62.3
55.2
agree
Our classes are
interesting***
Good
On the other hand, respondents, who see their own school less positively, usually have worse
school records than their peers.
Figure 3.17
50.0
40.0
30.0
20.0
10.0
0.0
Future plans (after current school), by performance as a student in %, N=4101.92
40.042.7
32.1
14.215.613.1
7.3 2.6 2.0
looking for a job
38.5
24.8
20.6
16.412.913.0
1.5 1.4 1.2
start
apprenticeship
vocation
school/learn
trade
Bad
school to
prepare acad.
degree
(University)
Average
other
I do not know
yet
Good
Respondents whosee themselves as good students envisagemore often continuing school to get
higher education. On the other hand, those who see themselves as rather poor students obviously
feel less well prepared for higher education and opt, as a result, predominantly for an
apprenticeship. This was to be expected. More noteworthy (and, eventually, a source of worry)
may be those who, although rating themselves as “bad students”, say continuing to higher
education. Provided the self-assessments among these students are realistic, there may be a lot of
frustration, due eventually to parental ambitions. A further source of concern must be the fact
that nearly one in five among the “poor” students has no clear idea about how to pursue
education after the current school.
92 Weighted data
80
Figure 3.18
100.0
80.0
60.0
40.0
20.0
0.0
Perception of problems at school, by performance as a student in %, N=4126413393
83.5
82.8
76.1
79.5
76.6
71.2
28.8
23.4
20.5
disagree
agree
83.5
82.8
76.1
23.9
17.2
16.5
disagree
agree
80.8
80.0
68.6
31.4
20.0
19.2
23.9
17.2
16.5
disagree
agree
disagree
agree
there are a lot of stealing there is a lot of fighting in a lot of things are broken there is a lot of drug use
in my school***
my scool**
or vandalized in my
in my school***
school**
Bad
Average
Good
Respondents, who see a lot of stealing, fighting, vandalized and broken items, as well as drug
use in their schools, tend to see themselves less often as “good students”. The association,
however, is not strong, particularly with respect to fighting at school, and the direction of the
causation is not entirely clear. It could simply reflect the fact that “poor students” tend to
concentrate in schools facing a lot of problems.
Figure 3.19
100.0
Staying away from school a whole day (truancy) during last 12 month by main
and subsamples in %.94
88.2
89.8
85.4
84.7
91.6
90.6
77.5
80.0
86.5
60.0
40.0
20.0
11.8
10.2
14.6
15.3
FR
(N=956)
22.5
8.4
9.4
ITA
(N=642)
SG
(N=625)
AG
(N=555)
no, never
yes
13.5
0.0
Switzerland
DE
(N=4'158) (N=2'560)
GE
(N=268)
ZH
(N=266)
The prevalence of truancy varies somewhat across the country, although not that many students
seem to stay away for one entire school day at least over the last 12 months. Truancy is more
common in French- and Italian-speaking cantons (14.6 and 15.1 per cent, respectively) than in
German-speaking regions and, once more, in St-Gall (8.4 per cent).
93 Weighted data
94 Weighted data
81
3.3 Association between school-related variables and delinquency
3.3.1 Attitudes towards school and delinquency
Given the many items on delinquency, we shall first summarize the delinquency scores by the
several independent (school-related) variables, as discussed before. Table 3.1 gives the scores
(i.e. the percentage of) respondents having admitted having committed any of the following
offences at least once over the last 12 months.
Table 3.1
Delinquency scores (last year prevalence), by attitude towards school in %,
N=4048-406795
If I have to move,
I would miss my
school
Most mornings I
like going to
school
I like
myschool
disagree
agree
p=
disagree
disagree
Graffiti
Vandalism
12.1
14.1
5.7
8.4
Shoplifting
Burglary
Bicyclethef
t
Motorbike/
cartheft
Car break
15.4
3.7
agree
p=
.000 10.3
.000 14.2
4.8
6.6
12.2
1.0
.026 18.0
.000 3.0
10.8
5.6
3.0
Ourclassesareinte
resting
agree
p=
disagree
agree
p=
.000 13.0
.000 15.5
4.8
7.4
.000
.000
11.5
15.5
4.2
6.1
.000
.000
9.8
0.6
.000 19.8
.000 3.5
10.5
0.8
.000
.000
20.2
2.4
8.8
0.9
.000
.000
.000 9.9
4.6
.000 12.9
4.5
.000
9.3
4.9
.000
1.1
.000 2.6
0.7
.000 3.0
0.9
.000
2.3
0.9
.000
4.3
1.8
.000 4.9
0.8
.000 5.4
1.3
.000
3.4
1.6
.000
Robbery
3.2
1.0
.000 2.3
0.8
.000 3.3
0.8
.000
2.5
0.8
.000
Theft
13.7
6.6
.000 11.7
5.6
.000 12.8
6.2
.000
13.4
4.7
.000
Weapon
Group
Fight
Assault
Drug
Dealing
AnimalCru
elty
18.0
8.6
.000 16.0
6.8
.000 17.4
7.8
.000
13.7
8.2
.000
10.5
7.0
.003 11.8
5.3
.000 13.8
5.7
.000
12.9
4.8
.000
8.1
2.4
.000 5.7
1.9
.000 6.4
2.3
.000
5.8
1.9
.000
10.9
4.6
.000 8.4
4.0
.000 10.6
4.1
.000
8.6
4.0
.000
5.5
3.3
.008 5.5
2.6
.000 5.4
3.1
.001
4.8
3.0
.005
Respondents with less positive feeling about their schools report more offence(s). In many
instances, the differences are even substantial. The following Figures will make this associations
more easily visible.
95 Weighted data
82
Delinquency (last year), by performance at school in %, N=4048-406796
Figure 3.20
25.0
20.0
15.0
10.0
17.6
14.3
7.0
5.0
5.0
9.7
7.6
20.4
15.2
14.6
12.5
9.2
4.6
1.2
1.1
7.3
4.7 4.0
4.0
3.3
1.8 0.8
1.5
1.4 2.4
0.8
10.4
8.4
6.6
9.6 10.1
9.5
8.2 7.3
6.5
3.2
2.6
12.2
6.2 4.9
4.1 3.3
3.7
0.0
Bad
Average
Good
Delinquency (last year prevalence) as a dependent variable is significantly related to school
performance. Students, who identify themselves as “bad students”, more likely admit to having
committed, at least once over the last 12 months, any of the offences included on the selfreported delinquency list.
Although school performance is, to some degree, related to future plans (Fig. 3.17), the
differences, in terms of offending, are not as substantial between the several educational
alternatives that respondents envisage, as one might have anticipated (Table 3.2/Figure 3.21).
96 Weighted data
83
Table 3.2
Delinquency last year prevalence by plans after compulsory school in %, N=40174034.97
Continue
school to
prepare
acad.
Start
degree
Lookingf apprentices Vocationschool/learnt (University
or a job
hip
rade
)
Other
I do not
know yet
p=
Graffiti
Vandalism
Shoplifting
Burglary
11.3
8.5
12.3
3.8
6.0
9.3
13.8
1.1
8.4
11.2
12.6
2.3
6.4
8.0
11.4
0.8
20.4
18.4
22.4
11.8
4.1
7.4
10.5
0.4
.000
.036
.076
.000
Bicycletheft
4.7
8.8
7.6
3.1
17.6
3.9
.000
Motorbike/cart
heft
Car break
Robbery
Theft
Weapon
2.9
1.2
1.1
0.8
9.8
1.1
.000
2.9
0.9
6.6
12.3
2.4
0.9
7.7
10.4
1.2
2.3
8.1
13.3
2.1
0.8
6.8
7.7
7.8
14.0
9.8
17.6
1.3
0.7
7.4
8.5
.022
.000
.875
.001
Group Fight
7.5
7.6
11.1
5.0
21.6
6.1
.000
Assault
3.8
2.7
5.8
1.8
14.3
2.6
.000
Drug Dealing
6.6
7.2
6.9
3.9
15.7
1.5
.000
AnimalCruelty
2.8
3.4
4.1
3.4
7.8
3.1
.583
The most delinquent group seem to be juveniles in the category of “other” plans, i.e. probably
juveniles without any clear plans for the future immediately following the current school.
97 Weighted data
84
Delinquency (last year) by plans after compulsory school in %m N=4017-4034.98
Figure 3.21
25.0
20.4
20.0
21.6
18.4
17.6
17.6
15.7
14.3
14.0 13.3
15.0 11.3
12.3
11.8
11.2
11.1
10.4
9.8
9.38.0
8.8
8.5
8.5
8.4
7.8
7.7 7.5
7.6
7.6
7.4
10.0
7.2
6.9
6.6
6.06.4
5.06.13.85.8
4.7 3.9
4.1
3.9
3.8
3.1 2.9
2.9
2.71.82.6
2.42.11.3 2.3
5.0
2.3
1.5
1.2
1.1
1.1
0.9
0.90.80.7
0.80.4
0.81.1 1.2
0.0
looking for a job
start apprenticeship
vocation school/learn trade
school to prepare acad. degree (University)
other
I do not know yet
Students who plan to continue with higher education after the current school are consistently less
delinquent. On the other hand, those in the category of “other” plans tend to be substantially
more delinquent with respect to most offences.
98 Weighted data
85
3.3.2 Problems in the school environment and delinquency
More even than with school performance, rather strong associations with delinquency have been
observed between the perceptions of problems in the school environment, such as frequent theft,
vandalism, fighting and drug use.
Figure 3.22
20.0
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Delinquency (last year) by the perception that stealing is common at school in %,
N=4042-4059.99
18.1
13.0
9.5 8.2
5.8
15.4
11.1
3.0
1.0
9.4
5.5
10.7
4.6
3.6
3.4
1.5
0.7
0.7
disagree
6.8
12.3
8.4
9.3
6.1
6.5
2.3
4.4
5.1
3.2
agree
Respondents, who say that “there is a lot of stealing in my school”, are more likely to admit
having committed, at least once during the last year, any of the offences included on the list.This
is particularly true for burglary, motorbike/ car theft, car break, and robbery. The explanation of
the association is not straightforward since juveniles who admit to these offences may, on one
hand, concentrate in schools with a lot of offences against property; on the other hand, the
presence of many fellow-students who engaging in such offences may operate also as a
facilitator of this kind of delinquency.
99 Weighted data
86
Figure 3.23
Delinquency (last year) by the perception that fighting is common at school in,
N=4045-4061 %.100
25.0
19.3
20.0
15.0
10.0
16.4
13.4
10.2
5.9
11.3
11.2
10.8
8.4
5.0
3.3
1.0
5.4
4.9
4.3
3.7
1.6
0.8
0.7
7.0
11.9
8.6
6.6
8.6
6.0
5.0 4.9
3.1
2.8
0.0
disagree
agree
Again, the same picture emerges. Students, who see a lot of fighting in their school, report
delinquency more often. The association is particularly strong for serious offences, such as
burglary, theft of/from cars, robbery, and assault.
100 Weighted data
87
Figure 3.24
Delinquency (last year) by the perception that vandalism is common at school in,
%, N=4043-4061.101
25.0
19.3
20.0
16.4
13.4
15.0
10.2
10.0
11.3
11.2
10.8
8.4
6.0
3.3
1.0
5.0
5.4
4.9
4.3
3.7
1.6
0.8
0.7
7.0
11.9
8.6
6.6
8.6
5.0 4.9
2.8
6.0
3.1
0.0
disagree
agree
Respondents, who report that broken and vandalized items are common at their schools, are
more likely to have committed, at least once over the last year, any offence included on our list,
especially burglary, theft if/from cars, and robbery.
Figure 3.25
Delinquency (last year) by the perception that drug use is common at school in %,
N=4038-4055.102
22.4
25.0
15.0
10.0
17.4
17.3
20.0
11.0
5.5
10.2
7.2
5.0
13.7
12.7
3.9 4.8
0.8
6.0
5.3
4.5
4.3
1.4
0.6
0.6
8.1
15.1
5.6
14.0
6.5
3.4
2.4
5.8
3.1
0.0
disagree
agree
101 Weighted data
102 Weighted data
88
Students who report that drug use is common at their schooladmit more often having committed,
at least once over the last year, any offence included on our list. The association is even stronger
than for the perception of other social problems in the school environment, particularly for drug
dealing.
Whereas Figure 3.25 is about delinquency at the individual level, we can also see how the school
environment affects behaviour among school populations. Figure 3.26 illustrates the association
between the perception that cannabis use is common at school and the percentage of students in
any of the 95 schools included in our survey that actually use cannabis.
Cannabis use (life time) by perception of drug use at school, at schools level (95
schools participating in the survey).
% who admit cannabis use (life time prevalence)
Figure 3.26
% who say that drug use is common in my school
Indeed, more students admit using cannabis at schools where they say drug use being common.
This supports the view that delinquency in the school environment may act as a facilitator rather
than as a simple correlate.
89
Figure 3.27 Delinquency (last year) by staying away from school a whole day (truancy) in %,
N=4045-4061.103
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
33.7
28.5
22.1
4.6
20.8
18.3
6.7
9.9
6.7 4.8
0.7
9.0
6.3
6.3 5.9
0.7 1.3 0.7
23.7
8.1
20.5
5.8
18.6
9.0
2.5
3.9
7.0
3.2
no, never
yes
Students, who stay away from school for least a whole day, are far more likely to commit an
offence. The association between these two variables is even higher than for the preceding
variables. This is noteworthy particularly for burglary, theft of/from cars, robbery, assault and
drug dealing.

French-speaking respondents have generally less positive feelings about their school.
This holds across the several measures of attachment to school, such as missing the
school or teachers in case of moving to a different area, or interest for classes. Germanspeaking respondents generally see their school environment more positively, especially
in the canton of St-Gall.

Overall, however, most Swiss students have positive attitudes towards school.

Students in Ticino are the most positively attached to their schools and teachers.

Students in French-speaking cantons report more often that there are social problems at
their school, such as widespread delinquency and drug use

Although truancy is fairly rare in Switzerland as a whole, it is far more common in
Geneva and in Zurich, and rare in St-Gall.

Despite the fact that students in French-speaking cantons and particularly in Geneva are
less attached to schools and/or teachers, and in contradiction with the fact that more
students have repeated a class there, an unusually high percentage see themselves as
103 Weighted data
90
„good“ students, in comparison with their peers in other regions. In line with this selfassessment, more students than in any other region plan to pursue education in higher
schools leading to academic studies. At the same time, less students than in any other
region plan to start an apprenticeship after their current school.

Delinquency is related to performance at school and attitudes towards school. Students
who plan pursuing with higher education report less self-reported offences. The highest
delinquency scores can be seen among students without clear or, eventually, unrealistic
plans for the future.

Students who report having missed school over more than one entire day during the last
12 months without legitimate excuse report having committed substantially more serious
and violent offences.

There is a significant, consistent and fairly strong association between delinquency and
the perception of social problems at school. Students are more likely to admit having
committed offences who report a lot of stealing, fighting and vandalized items at school.
The association is particularly strong for the perception that drug use is common at
school. This is especially true for more serious and violent offences.

School-related variables (as those discussed here) are particularly relevant for designing
policies of prevention. Truancy, vandalism at school as well as other social problems at
schools can be dealt with, at least to some extent, by school authorities. Although our
cross-sectional analyses cannot definitively determine the causal direction of the
observed associations, their size suggest, in some instances at least, that improving school
indicators might be a promising way to prevention.
91
Chapter 4
Victimization
4.1 Overview
In the ISRD-3, as well as during ISRD-2 (in 2006), respondents were asked whether they have
been victims of several kinds. The questionnaire included 7 questions about victimization (over
the entire life time and over last year). In case of any victimization (except parental violence and
parental maltreatment) that was experienced during last 12 month, respondents were asked
whether or not the incident had beenreported to the police.
In this chapter, findings will be presentedregarding victimization and reporting to the police.
Wealso shall compare rates of victimization in 2013, with those observed in 2006 (ISRD-2).
Further, rates of reporting to the police in 2013 and 2006 will be presented.
This chapter also includes information on demographic factors influencing the risk of
victimization and the decision to report an incident to the police.
4.2.1 The prevalence of victimization across regions
The following Table 4.1 gives the detailed rates on how many among the respondents have ever,
during their life, become victims of the offences listed, both nation-wide and in the several
subsamples.
Table 4.1
Victimization (life-time prevalence) by main and subsamples in %.104
Switzerland
(N=4'158)
Robbery
Assault
Personal theft
Hate
Cyberbullying
Parental violence
Parental maltreatment
5.1
5.0
35.1
7.4
15.5
28.4
7.9
DE
FR
ITA
SG
AG
GE
ZH
(N=2'560) (N=956) (N=642) (N=625) (N=555) (N=268) (N=266)
4.5
4.4
35.0
7.5
12.9
24.3
6.1
6.1
5.9
35.9
7.4
21.1
37.5
12.2
6.7
7.3
31.3
5.8
16.7
28.7
5.0
4.4
4.8
35.8
6.2
15.1
23.4
7.8
6.5
4.4
32.7
6.6
16.4
20.3
5.3
3.6
7.1
32.6
7.4
18.3
38.1
10.8
5.5
4.2
36.8
10.5
12.5
29.7
5.8
104 Weighted data
92
Figure 4.1 gives the same information in visualized form and for the three language regions as
well as for the country as a whole. As it seems, victimization is relatively evenly distributed
across the several regions of Switzerland.
Figure 4.1
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (last year prevalence) by main and subsamples in %.105
27.1 25.4
26.9
26.9
19.1
16.4
27.2
25.2
21.5
16.9
16.7
28.8
27.3
25.8
17.1
14.9
18.1
12.3
9.6
9.3
8.7
7.7
6.2
5.6 5.5
5.65.4 4.0 5.7
5.64.1 6.06.0
5.5
5.43.9 3.8
4.9
4.7
4.5
4.3
3.8
3.8
3.7 5.33.3
3.5
3.4
3.3
3.2
2.9
2.9
2.62.8
2.4
2.0
Switzerland
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
Robbery
Assault
Personal theft
Cyber bullying
Parental violence
Parental maltreatment
GE
(N=268)
ZH
(N=266)
Hate
However, respondents in German-speaking cantons are slightly less often victimized regarding
most offences. The difference is particularly marked for parental violence and parental
maltreatment that is almost twice as frequent in French-speaking cantons and especially in
Geneva (as shown in Table 4.1). The differences are similarly strong for cyber bullying.
4.2.2 More victimizations and less reporting?
Last year prevalence rates of victimization in 2013 can be compared with the data for 2006 and
for Switzerland as a whole. Exceptions are hate crimes, cyber bullying, parental violence and
maltreatment by parents that were not measured in 2006, as well as bullying in general that were
not asked in 2013.
105 Weighted data
93
Table 4.2
Percent victimized and reporting to the police in % for 2013 and 2006.106
ISRD-2*
Victimization
(last
Reported to
yearprevalenc
the police
e)
Robbery
Assault
Personal theft
Hate
Cyberbullying
Bullying
Parental violence
2.3
2.4
22.6
22.3
32.4
32.3
12.4
7.8
Victimization (last
yearprevalence)
Reported to the
police
3.3
3.8
26.9
5.6
8.7
17.4
30.6
22.9
15.1
15.8
19.1
Parental
maltreatment
N=
ISRD-3*
5.5
3‘648
4'158
* weighted data
The prevalence of victimization has increased from 2006 to 2013 for robbery, assault and
personal theft. The increase is significant (p ≤ .000).
Reporting to the police has been asked for the last incident (in case more than one incidence has
been reported for the last 12 months). Reporting to the police is not as unusual as one might have
expected. In general, reporting to the police has slightly decreased from 2006 to 2013. For the
interpretation of official counts of offending (such as police statistics), this means that a lower
level of reporting should be taken into account and that an eventual decrease might be overstated
if lower levels of reporting are not considered.
106 Weighted data
94
4.3 Association between demographic variables, victimization and reporting to the police
4.3.1 Gender, victimization and reporting to the police
Gender is an important variable in criminology. Table 4.3 shows,for boys and girls, the
prevalence rates of victimization (both over the last 12 months and the entire life time) as well as
the proportion of offences that were reported to the police.
Table 4.3
Victimization and reporting to the policein %.107
Victimization (life time prevalence) by gender (N=4121-4136)
Parental
Parental
Robbery Assault
Theft
Hate
Cyberbullying violence
maltreatment
male
7.6
6.2
39.4
7.7
10.4
27.3
8.0
female
2.7
3.9
31.0
7.0
20.5
29.4
7.7
Chi.000
.001
.000
.380
.000
.133
.719
squire
Victimization (last year prevalence) by gender (N=4129-4138)
Parental
Parental
Robbery Assault
Theft
Hate
Cyberbullying violence
maltreatment
male
5.0
4.4
29.1
6.0
5.9
18.6
5.6
female
1.6
3.3
24.6
5.3
11.3
19.5
5.3
Chi.000
.051
.001
.381
.000
.426
.690
squire
Reporting to the police by gender, last year (N=129-1096)
Robbery Assault
Theft
Hate
Cyberbullying
male
16.7
25.8
25.2
17.6
14.8
female
18.2
36.8
20.5
12.6
16.2
Chi.842
.141
.064
.288
.738
squire
Boysare more often victims of robbery, assault and personal theftthan girls. These differences
obviously relate to different life-styles and exposure to risk. On the other hand, girls more often
than boys experience cyber bullying. Hate crimes, parental assault and maltreatment (life-time
and last year prevalence) are relatively independent of gender.
4.3.2 Birthplace, victimization and reporting to the police
4.3.2.1 Country of birth and victimization
Birthplace has been measured in a way that promised to work in very different countries with
most diverse patterns of immigration. For this sake, respondents have been asked in which
country they were born themselves, and in which country their mother and their father had been
born. Table 4.4 presents how many respondents (in per cent) experienced any of the listed
107 Weighted data
95
offences over the last 12 months by whether they were born in Switzerland or in any other
country.
Victimization (last year prevalence) by respondents’ birthplace in %, N=41184132.108
Table 4.4
Robbery Assault
Born
abroad
born in
Switzerland
Theft
Cyberbull Parental
ying
violence
Hate
Parental
maltreatment
4.0
6.3
34.3
7.4
10.2
25.1
10.2
3.1
.247
3.4
.001
25.6
.000
5.3
.049
8.4
.171
18.2
.000
4.7
.000
In Figure 4.2, the same information is presented in a visualized form, but for offences
experienced over the last 12 months.
Figure 4.2
50.0
40.0
30.0
20.0
10.0
0.0
Victimization (life time prevalence) by respondents’ birthplace in %, N=41184132.109
43.6
33.7
6.0 4.9
8.2 4.5
34.7
27.4
9.8 6.9
not in Switzerland
18.315.1
13.0
7.0
Switzerland
Respondents who were born abroad experience offences of all kinds significantly more often,
than those who were born in Switzerland. This is true for the last twelve months (Figure 4.2) as
well as over the lifespan (Table 4.4). This difference may be related to different leisure-time
activities and life-styles (see chapter 5).
Whether or not the incident was reported to the police was asked for the last incident
experienced over the last 12 months.
Birthplace can also be defined in terms of parents’ country of birth. We first present the results
by mother’s birthplace.
108 Weighted data
109 Weighted data
96
Victimization (last year prevalence) by mothers’ birthplacein %, N=4092-4107.110
Table 4.5
Parental
Parental
Robbery Assault Theft Hate Cyberbullying violence maltreatment
Born
abroad
born in
Switzerland
3.9
4.1
32.0
8.4
10.8
23.5
8.7
2.8
.070
3.5
.300
23.5
.000
3.8
.000
7.3
.000
16.3
.000
3.3
.000
Respondents whose mother was born in Switzerland are less often victims of all listed offences
with the exception of robbery and assault (where the difference does not reach statistical
significance). Interestingly, mother’s country of birth seems to influence risks of victimization
more than whether or not the respondent had been born abroad or in Switzerland. This is
particularly true for maltreatment by parents.
The results are similar when, instead of the last 12 months, the entire life-time is considered
(Figure 4.4). In this case, the differences all reach statistical significance. Proportionately, they
become even more impressive, particularly with respect to parental maltreatment.
Figure 4.3
50.0
40.0
30.0
20.0
10.0
0.0
Victimization (life time prevalence) by mothers' birthplace in %, N=4093-4108.111
40.8
31.3
6.3 4.2
5.9 4.3
11.4
not in Switzerland
4.8
18.313.8
34.0
24.7
12.5
4.7
Switzerland
These differences can be observed, in similar proportions, in the national sample as well as in the
several subsamples (not shown).
When mothers’ country of birth is considered, some relevant differences emerge. Generally
speaking, children of mothers born in Switzerland, in Germany or in any other country of
Western or Eastern Europe have lower victimization rates than respondents whose mother was
born in Southern Europe or outside of Europe. Details are presented in Figure 4.4.
110 Weighted data
111 Weighted data
97
Victimization (life time prevalence) by mother’s birthplace in %, N=40974107.112
Figure 4.4
50.7
46.9
45.7
45.0
44.4
40.1
35.7
34.9
34.5
31.3 31.9
11.3
10.9
9.5
8.0 7.5
7.7 5.0 6.1
7.55.2
6.5
6.5
5.2
4.3
4.2 6.6
3.9
3.8
3.7
1.8 2.4 2.7
43.0
42.1
39.9
39.3
38.2
30.9
28.2
26.1
25.3
24.6 24.7
21.6
20.1
19.0
16.3
16.2
16.1
16.0
15.6
14.5
14.4
14.4
13.8 13.8
13.8
13.6
13.0
12.9
12.4
11.7
11.3
10.3
10.1
9.7
9.7
9.7
9.3
8.4 7.0 7.7
4.8
4.7 4.4
36.0
Switzerland
Italy
Kosovo
Germany
Portugal
West Europe
Africa
Asia/Oceania
The differences are particularly pronounced for cyber bullying, parental violence and
maltreatment by parents. They are visible in all linguistic regions (not shown).
Similar patterns appear when, instead of mother’s origin, the father’s country of birth is
considered.
Table 4.6
Born
abroad
born in
Switzerla
nd
Victimization (last year prevalence) by father’s birthplace in %, N=4058-4072.113
Cyberbull Parental
ying
violence
Parental
maltreatment
Robbery
Assault
Theft
Hate
3.8
5.3
30.1
7.9
9.7
24.0
9.3
2.9
.135
2.8
.000
24.6
.000
4.2
.000
7.8
.032
16.1
.000
3.1
.000
The same tendency can be observed if offences experienced over the entire lifespan are
considered (Figure 4.5).
112 Weighted data
113 Weighted data
98
Figure 4.5
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Victimization (life time prevalence) by father’s birthplace in %, N=4059-4073.114
38.6
32.7
6.2 4.4
6.5 3.9
33.8
24.7
9.8
not in Switzerland
17.214.4
5.8
12.8
4.7
Switzerland
In this case, all differences (with the exception of theft and cyber bullying) reach statistical
significance. They hold across regions and language rather consistently. Although both parents’
foreign origin seems to increase risks of victimization among their offspring, mother’s origin
seems to be slightly more important than father’s country of birth. In further analyses, we shall
try to disentangle whether this is directly related to mother’s origin. One possibility might be that
mothers of Swiss background are more successful at protecting their offspring from domestic
violence.
When we look at fathers’ country of birth, some interesting patterns emerge. As with mothers
(see Figure 4.4), respondents whose father was born abroad tend to be victimized more often,
particularly in the domain of domestic violence (Figure 4.6).
114 Weighted data
99
Figure 4.6
Victimization (life time prevalence) by fathers' country of birth in %, N=40584072115
60.0
50.0
40.0
54.8
51.1
44.7
44.4
39.1
36.4
35.7
35.5
34.6
32.7
31.7
30.0
20.0
11.3
10.58.28.5 9.3
7.59.1
7.1
6.13.9 3.6
5.66.2 6.8
5.6
10.0 4.47.1
3.0
2.8
1.9
0.9 2.2
0.0
45.1
40.2
40.1
36.8
36.7
33.8
30.3
30.0
25.8
25.3
24.725.0
23.9
22.1
18.7
18.4
17.3
17.2 17.5
16.1
14.9
14.7 12.3
14.413.3
12.0
11.6 11.7
11.6
11.2 10.0
11.1
11.0
10.9
10.3
8.6 9.1
8.0
6.2 6.5
5.8 4.5
4.7 5.5
Switzerland
Italy
Kosovo
Germany
Portugal
West Europe
Africa
Asia/Oceania
Domestic violence seems more common in families with fathers born in Asia and Oceania,
Portugal and countries of North and South America. No clear pattern emerges for the other
offences. The picture is similar in all regional subsamples (not shown).
4.3.2.2 Reporting to the police by country of birth
For all incidents mentioned during interviews that were experienced over the last 12 months, the
respondent was asked whether or the incident had been reported to the police. In case more than
one incident occurred during the last 12 months, the question was asked in relation to the last
one. The replies will be analysed here by respondents’ birthplace.
115 Weighted data
100
Figure 4.7
Reporting to the police by respondents' birthplace in %, N=130-1095.116
40.0
30.0
31.4 30.6
22.7
20.0
16.7
25.0 22.5
20.0
13.8
19.0
15.1
10.0
0.0
Robbery
Assault
Theft
not in Switzerland
Hate
Cyber bullying
Switzerland
Reporting to the police does not differ much along birthplace. Respondents who were born
abroad report offences to the police slightly more often than those born in Switzerland. The
differences arenot significant, however.
Reporting of experiences of victimization to the police is not significantly more frequent among
respondents whose mother was born abroad. This was true for the national sample as well as for
the several subsamples.
Figure 4.8
Reporting to the police by mother' birthplace in %, N=127-1088.117
40.0
26.6
30.0
20.0
13.8
29.9
23.6 22.7
18.8
13.6
16.8
15.6 16.0
10.0
0.0
Robbery
Assault
Theft
not in Switzerland
Hate
Cyber bullying
Switzerland
The following Figure 4.9 shows the proportion of offences reported to the police for subjects
whose father was born abroad vs. those whose father was born in Switzerland.
116 Weighted data
117 Weighted data
101
Reporting police by fathers' birthplace in %, N=127-1073.118
Figure 4.9
40.0
32.5
26.8
30.0
20.0
18.5
23.9
21.6
14.4 15.1
15.1
17.3
14.8
10.0
0.0
Robbery
Assault
Theft
not in Switzerland
Hate
Cyber bullying
Switzerland
For most offences, reporting is slightly more likely to occur if the respondent’s father was born
abroad. The difference is not significant, however.
4.3.3 Religion and victimization
The questionnaire contained, in a form that worked in many different nations, detailed
information about respondents’ religious affiliation. This variable turned out to be associated
with risks of victimization, both nation-wide and in the three linguistic regions of Switzerland.
Given the small size of some religious groups, we consider life-time experiences only in this
section.
Figure 4.10
Victimization (life time prevalence) by religious affiliation in %, N=4096-4105.119
50.0
43.2
39.9
36.6
34.4
33.9
33.2
40.0
30.0
20.0
10.0
5.54.75.23.95.46.6 4.95.04.55.94.86.2
39.3
31.4
31.2
30.1
26.9
25.8
23.3
19.2
16.1
14.7
14.0 14.6
13.7
13.0
12.7
11.9
8.38.1 5.5
7.56.64.97.5
4.6
0.0
do not belong to a religion/religion community
catholic
protestant
orthodox and other christian confessions
muslim
118 Weighted data
119 Weighted data
102
Whereas religion is not significantly associated with robbery and assault, theft of personal items,
cyber bullying and hate crimes are inconsistently related to religion. However, respondents of
Christian (i.e. protestant, catholic or orthodox/other) background experience all listed offences
slightly less often than Muslims and those without religious affiliation. The difference is, as far
as protestant respondents are concerned, particularly strong with respect to parental violence and
maltreatment.
In German-speaking cantons, the results match by and large the national pattern. In the French
and Italian-speaking regions, the differences are mostly non-significant, presumably because of
the smaller sample sizes and the small percentage of respondents belonging to certain religious
affiliations.
The findings in this chapter can be summarized as follows:

Victimization is fairly wide-spread. When we consider incidents experienced over the life
span, rates far above what one finds in national victimization surveys of the general
population can be observed. Obviously, juveniles are far more exposed to risks of theft,
assault and even robbery than the general population.

Juveniles report a lot of cyber bullying which seems to have replaced classical bullying to
a large extent.

Violence experienced at home, i.e. probably corporal punishment is relatively widespread. Roughly close to 20 per cent of respondents has experienced this. More
disturbing is the fact that 5.5 per cent report different forms of domestic assault that can
be considered as parental maltreatment.

Although one would not expect much variation within a small country like Switzerland, it
is noteworthy that such differences exist. Juveniles in the French-speaking part report
violence somewhat more often than those in the other regions. Particularly domestic
violence and parental maltreatment are more frequent in the French-speaking part. This
coincides with higher rates of domestic violence (between parents) reported by
respondents from that region (see chapter 2, Figure 2.11_1).

Offences that are typically experienced in the streets, such as assault, robbery and theft of
personal items have increased between 2006 and 2013.

Reporting to the police decreased. This should be kept in mind when police and other
official counts of offending are to be interpreted.

Girls experience street-level offences less often than boys, presumably due to their
different life-style (and, perhaps, the fact that, while going out, they are more often in the
company of boys). However, girls experience cyber bullying more often. Violence
experienced at home and theft of personal items are more evenly distributed across
gender.
103

Girls tend to report offences somewhat less often, although differences are not large.

Birthplace was measured, in the ISRD-3, in a way that promised to work during the
fieldwork in countries as diverse as Western European nations, the Americas and Asian
countries. It was decided to ask about the country of birth of the respondent and both of
his/her parents, rather than about his official nationality. In Switzerland, a very
substantial proportion of respondents had been born abroad, or have parents who were
born outside of Switzerland (see chapter 1).

In connection with victimization, the country of birth (of the respondent, his/her mother
or father) is somewhat associated with victimization. Generally, respondents born abroad,
or whose mother or father was born abroad, experience all offences somewhat more
often. For street crime, this may be due to different life-styles and in parts be related to
offending that is also more frequent among youths with origins in other countries (see
chapter 7).

The differences are particularly strong with respect to hate crimes. This is not unexpected
in the sense that the question was obviously shaped to identify incidents experienced by
respondents who were more exposed to such forms of harassment due to their origin. On
the other hand, it is interesting to observe that respondents from Swiss background report
also such incidents, although in lower proportions.

Parental (domestic) violence and, particularly, parental maltreatment are substantially
more frequent among youths from abroad. This matches findings (presented in chapter 2)
concerning the association between origin and domestic violence (between parents) that
is, again, more frequently reported by respondents whose parents were born abroad.
Interestingly, the mother’s origin seems somewhat more important in this respect than the
father’s, or the respondent’s own country of birth. Since these findings do not imply who
of the parents actually was responsible for the maltreatment, it could be that mothers born
in Switzerland are better in a situation to protect their child from domestic violence.

Reporting assault and hate crime to the police is somewhat more common among
respondents born abroad. This may reflect higher levels of seriousness of the attack. For
other offences, the differences are not large. Assault is also more often reported to the
police if parents are born abroad.

For the police, the “good news” about these findings is that reporting does not differ
much along ethnic lines. On attitudes towards the police see chapter 8.

Religion is weakly associated with victimization overall, especially with street-crime.
However, respondents of any Christian denomination and especially Protestants are less
often victims of all listed offences than those without any religious affiliation and
Muslims. The difference is largest in connection with parental maltreatment.
104
Chapter 5
Leisure time, life style, peers, happiness and delinquency
5.1 Overview
In this Chapter findings will be presented on leisure-time and other unsupervised activities, time
spent with friends (delinquents and/or non-delinquents), time spent within the family; level of
happiness, consumption of alcohol and other substances, and the relationship of all these
variables with several measures of delinquency. In the first part (section 5.2), we shall show the
frequencies of these variables in the national as well as across the regional subsamples.
Since consumption of substances in general and particularly of cannabis can be considered as
deviant behaviour, given the respondents’ age, we shall treat use of alcohol and cannabis as a
dependant as well as an independent variable. It should be noted that the sale of alcoholic
beverages to minors of 16 is illegal. For spirits, the age-limit is 18 years. In section 5.3, we shall
look at associations between alcohol/cannabis use in relation to leisure-time activities.
In section 5.4, we shall look at changes between 2006 (ISRD-2) and 2013 (ISRD-3) with respect
to several leisure-time activities.
As a truly innovative concept, the ISRD-3 instrument included questions concerning happiness.
This concept, developed by the Swiss economist Bruno Frey, has turned out to be particularly
helpful in the analysis of experiences of victimization (Staubli, Killias& Frey 2013). Happiness
can be considered as an outcome as well as a causal variable. We shall look both at how it is
associated with leisure-time activities, use of substances and delinquency (section 5.5).
In the final part (section 5.6), we shall analyse how all these leisure-time variables and happiness
are associated with the several forms of delinquency that were included in ISRD-3.
A summary and short discussion (section 5.7) will conclude this chapter.
5.2 Frequencies in the national and the regional samples
Leisure-time activities
Several questions addressed the use of leisure-time, i.e. whether respondents go out during the
week and on weekends, when they return and whom and how otherwise they spend time with.
105
“How often do you go out a week?” by main and subsamples in%.120
Figure 5.1
60.0
50.0
40.0
30.0
20.0
10.0
0.0
48.0
45.2
38.1
50.1
45.1
38.2
35.5
16.7
16.5
CH
(N=4'158)
DE
(N=2'560)
31.4
FR
(N=956)
never
ITA
(N=642)
1-2 times per week
45.8
33.6
18.6
18.5
16.7
53.9
49.3
44.5
36.9
SG
(N=625)
29.6
24.6 27.7
17.2
AG
(N=555)
GE
(N=268)
18.4
ZH
(N=266)
3-6 times per week, daily
More than half of respondents go out during the week up to 2 times, whereas more than one third
nevergoes out. Going out varies somewhat across region. In the French speaking part, two
students in five never go out in the evening. Geneva is the region with the most active evening
and night life. Presumably, these differences also reflect opportunities since Geneva obviously
has the most extensive offer of night-time activities.
Figure 5.2
Time of coming back after going out on weekend evenings by main and
subsamples in %.121
60.0
53.0
50.0
37.2
34.0
40.0 36.8
43.6
39.3
37.0
32.0
30.0
20.0
10.0
12.8
14.2
35.132.8
38.8
32.0
44.1
10.3 12.9
4.1
1.1
12.3
9.2
1.9.5
29.1
23.2
17.0
12.8
5.6 8.4
3.31.32.3
.8
SG
(N=625)
AG
(N=555)
GE
(N=268)
18.7
9.6
2.7.9
10.6 11.8
3.5.7
7.9
1.01.2
6.2
1.61.4
CH
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
43.2
0.0
I do not go out in the evening
00:00 - 2:45
3:00 - 6:30
7:00 - 9:30
10:00 - 19.45
20:00 - 23:45
ZH
(N=266)
Most students either do not go out in the evening or come back home before midnight even on
weekends. Nearly one respondent in five say returning way after midnight, i.e. during early
morning hours or the following day. It can be assumed that these students are the least controlled
by parents. In the canton of Zürich, about 30% regularly return back home after midnight or the
following day.
120 Weighted data
121 Weighted data
106
Spending time with family and friendsby main and subsamplesin %.122
Figure 5.3
60.0
48.3
44.4
50.0
40.0
30.0
20.0
10.0
22.0 24.3
9.3
21.2 21.4
37.2
30.0
22.9
9.8
9.1
36.7
26.1 28.4
8.8
23.2 25.7
7.2
50.2
47.3
43.9
34.3
28.3
21.7 23.2
21.7 19.9 22.2
15.7
7.8
7.7
0.0
CH
(N=4'158)
DE
(N=2'560)
on my own
FR
(N=956)
ITA
(N=642)
with my family
SG
(N=625)
AG
(N=555)
with 1-3 friends
GE
(N=268)
ZH
(N=266)
with more than 4 friends
Nearly half of respondents spend time mostly with 1-3 friends; and nearly one in four with other
family members and about an equal proportion with a larger group. There is not much variation
across regions
Figure 5.4
Leisure time: going to coffee bars or pop concerts by main and subsamples in
%.123
80.0
60.0
40.0
20.0
74.9
64.8
55.1
39.8
68.5
49.3
44.7
48.347.3
50.9
41.8
31.8
25.1
22.4
5.1
6.0
CH
(N=4'158)
DE
(N=2'560)
3.4
44.947.0
4.4
2.8
7.3
6.4
8.1
0.0
FR
(N=956)
never
ITA
(N=642)
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
often
More than half of respondents never go to coffee bars or pop concerts. There is not that much
variation across regions, with the exception of Zurich where more peoplego often to coffee bars
or pop concerts.
122 Weighted data
123 Weighted data
107
Figure 5.5
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Leisure time: doing something creative (theater, music, drawing, writing, reading
books) by main and subsamples in %.124
41.4
39.336.1
37.736.4
35.8
25.9
24.6
22.8
CH
(N=4'158)
DE
(N=2'560)
47.9
41.841.1
39.638.3
38.6
37.336.3
34.1
27.3
26.4
22.2
18.0
17.1
34.2
FR
(N=956)
ITA
(N=642)
never
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
often
In the whole Switzerland 39% of respondents said never doing anything creative, such as playing
theatre or music, drawing, writing and reading books. This percentage is the highest in Italian
speaking cantons. Otherwise, there is not much variation across regions in this respect.
Leisure time: engaging in fights with others by main and subsamples in %.125
Figure 5.6
100.0
87.4
87.6
87.6
89.7
84.2
86.6
84.1
84.8
50.0
9.6 2.9
9.8 2.6
CH
(N=4'158)
DE
(N=2'560)
8.8 3.6
11.84.1
9.3 1.0
10.52.9
9.3 6.6
11.53.6
0.0
FR
(N=956)
never
ITA
(N=642)
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
often
Only a minority of respondents admit engaging, during leisure-time, often or sometimes in fights
with others. There is obviously only limited variation across regions.
124 Weighted data
125 Weighted data
108
Leisure time: doing sportsby main and subsamples in %.126
Figure 5.7
80.0
54.4
60.0
40.0
20.0
31.5
14.1
53.8
34.1
12.1
60.5
54.8
26.1
19.1
56.7
32.2
29.5
33.1
12.8
11.1
10.1
54.0
55.6
53.4
25.9
20.7
33.9
10.5
0.0
CH
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
never
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
often
Again, very little variation across regions can be observed. However, at closer inspection, it turns
out that respondents more often say never practicing any sports in Geneva and in Frenchspeaking regions.
126 Weighted data
109
Figure 5.8
%.127
Leisure time: school-related studies or homework, by main and subsamples in
80.0
20.0
35.1
34.6
40.0
54.6
54.6
54.4
60.0
11.0
37.0
32.2
13.2
10.3
32.5
47.9
36.1
16.1
8.7
8.1
6.9
58.7
54.9
51.2
41.8
47.3
41.2
11.6
0.0
CH
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
never
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
often
The highest proportion of respondents who say never studying or doing homework during
leisure-time can be found in Geneva and other cantons in the Romandie, as well as in the canton
of Zurich. Ticino and St. Gallen have the most disciplined students, apparently.
Figure 5.9
Leisure time: hanging out in shopping centers, parks, streets etc. for fun, by main
60.0
50.0
40.0
30.0
39.6
34.6
39.141.2
25.7
45.6
35.237.3
27.5
19.7
20.0
47.9
44.8
36.2
35.4
19.8
18.3
42.3
34.7
36.8
33.4
30.4
29.8
23.1
21.7
10.0
0.0
CH
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
never
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
often
Hanging out in shopping centres, parks, streets etc. for fun is the least popular among
respondents in German speaking cantons and particularly in St. Gallen. On the other hand, such
unstructured leisure-time activities are fairly wide-spread in Ticino Geneva and other Frenchspeaking cantons in general.
127 Weighted data
128 Weighted data
110
Figure 5.10
%.129
Leisure time: doing something illegal to have fun, by main and subsamples in
100.0
80.0
73.9
84.0
74.5
72.8
73.5
78.8
72.4
71.9
60.0
40.0
22.2
21.2
20.0
20.2
5.0
4.9
CH
(N=4'158)
DE
(N=2'560)
13.2
5.4
22.0
21.7
5.9
4.4
2.8
12.4 8.8
22.6
5.6
0.0
FR
(N=956)
ITA
(N=642)
never
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
often
Variation is less pronounced than one might have expected, although doing illegal things for fun
is more popular among respondents in Zurich and Geneva.
Figure 5.11
100.0
Leisure time: drinking alcohol or take drugs, by main and subsamples in %.130
80.0
86.6
86.1
79.8
79.7
85.5
82.5
80.0
75.8
60.0
40.0
20.0
15.0
5.0
15.2
5.1
15.4
4.8
10.2
10.0 3.9
3.2
14.0
3.4
10.2 4.3
15.8
8.4
0.0
CH
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
never
SG
(N=625)
sometimes
AG
(N=555)
GE
(N=268)
ZH
(N=266)
often
Drinking alcohol or taking drugs during leisure-time “often” is more common in French
speaking cantons and particularly in Geneva and in Zurich, and relatively rare in the cantons of
St. Gallen and Aargau. Presumably, opportunities – i.e. the availability of substances and places
to consume – may play an important role in this respect.
129 Weighted data
130 Weighted data
111
Figure 5.12
100.0
80.0
60.0
40.0
20.0
0.0
Leisure time: frightening and annoying people just for fun, by main and
subsamples in %.131
70.7
66.9
24.0
5.3
27.1
6.0
CH
(N=4'158)
DE
(N=2'560)
78.4
83.7
75.0
17.7
3.8
FR
(N=956)
never
65.7
29.2
20.2
4.8
ITA
(N=642)
5.2
SG
(N=625)
sometimes
67.5
64.6
28.3
7.2
AG
(N=555)
13.2
3.1
GE
(N=268)
24.3
8.2
ZH
(N=266)
often
It seems that in the Swiss context this question, designed for a multitude of cultures included in
this project, measured “teasing”, being noisy or making jokes (“Streiche”) rather than activities
that might be proxies of delinquency. Anyhow, these sorts of activities are the most common in
fairly rural areas, such as St. Gallen and Aargau, and least common in Geneva and in the
Romandie in general.
5.2.1 Peers and friends
The questionnaire included several questions regarding friends and peers. Table 5.1 gives an
overview on how many respondents say belonging to a group of friends (peers). Further, this
section of the instrument included questions regarding deviant behaviour among peers, such as
using illicit substances, shoplifting and several other offences
Table 5.1
“Some people have a friend or a group of friends to spend time with, doing
things together or just hanging out: do you belong to such a group?” by main and
subsamples in %.132
CH
DE
FR
ITA
SG
AG
GE
ZH
(N=4'158) (N=2'560) (N=956) (N=642) (N=625) (N=555) (N=268) (N=266)
no
21.8
22.5
20.3
21.2
22.6
21.4
27.3
21.5
yes
78.2
77.5
79.7
78.8
77.4
78.6
72.7
78.5
Most of students have a friend or group of friends to spent time with, doing things together or
just hanging out. However, about one student in five seems to be somewhat socially isolated.
There is almost no difference across regions.
131 Weighted data
132 Weighted data
112
Figure 5.13
80.0
60.0
Having friends who use drugs by main and subsamples in %.133
73.1
62.8
58.4
41.6
37.2
40.0
46.1
71.5
60.9
53.9
39.1
28.5
26.9
48.9 51.1
58.3
41.7
20.0
0.0
CH
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
no
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
yes
In the whole Switzerland 41.6% of respondents know at least one friend who uses drugs. This
level is the highest in French speaking cantons and in Geneva where a majority of respondents
know such a friend. The lowest proportion can be found in the cantons of Ticino and St. Gallen.
Figure 5.14
80.0
60.0
40.0
20.0
0.0
Having friends who committed shoplifting, by main and subsamples in %.134
63.8
63.6
75.8
62.0
36.2
36.4
CH
(N=4'158)
DE
(N=2'560)
38.0
FR
(N=956)
70.7
67.6
32.4
24.2
ITA
(N=642)
no
SG
(N=625)
71.7
29.3
AG
(N=555)
64.0
28.3
GE
(N=268)
36.0
ZH
(N=266)
yes
The highest proportions of respondents who say knowing at least one among their friends/peers
who had committed shoplifting can be found in Zurich and St. Gallen. Otherwise, knowing of
somebody who has committed such an offence is fairly widespread and evenly distributed across
region.
133 Weighted data
134 Weighted data
113
Figure 5.15
100.0
Having friends who committed burglary, by main and subsamples in %.135
93.0
81.1
89.9
93.1
95.1
90.3
54.7
53.5 46.5
50.0
18.9
10.1
7.0
6.9
4.9
SG
(N=625)
AG
(N=555)
45.3
9.7
0.0
CH
(N=4'158)
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
no
GE
(N=268)
ZH
(N=266)
yes
Interestingly, there is far more variation with respect to knowing at least one friend among one’s
peers who had committed burglary. This is fairly common in Geneva and other French-speaking
cantons, but exceptional in other regions.
Figure 5.16
120.0
100.0
80.0
60.0
40.0
20.0
0.0
Having friends who committed robbery by main andsubsamples in %.136
94.7
94.6
5.4
CH
(N=4'158)
5.3
DE
(N=2'560)
96.0
95.7
94.2
97.4
94.0
92.6
5.8
4.3
4.0
6.0
2.6
7.4
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
no
yes
Knowing somebody who had committed robbery is very uncommon in all subsamples. This
obviously reflects the fact that this offence is not frequently committed (see Chapter 7) and
perhaps even less often admitted, even among friends.
135 Weighted data
136 Weighted data
114
Figure 5.17
120.0
100.0
80.0
60.0
40.0
20.0
0.0
Having friends who committed assault by main and subsamples in %.137
90.3
95.2
88.0
9.7
CH
(N=4'158)
12.0
DE
(N=2'560)
92.2
90.4
4.8
7.8
9.6
FR
(N=956)
ITA
(N=642)
SG
(N=625)
no
94.7
88.6
11.4
AG
(N=555)
86.8
5.3
GE
(N=268)
13.2
ZH
(N=266)
yes
The same holds, although to a lesser extent, for assault. Again, little variation across regions can
be observed, with the exception of Zurich.
Having deviant (or law-abiding) friends obviously is one thing, and another is how intense such
bonds may be in a series of hypothetical situations, such as moving to another city.
“If I had to move to another city, I would miss my friends”, by main and
subsamples in %.138
Figure 5.18
100.0
90.2
91.2
88.6
90.9
87.5
92.9
84.5
91.4
80.0
60.0
40.0
20.0
8.6
1.2
7.5
1.4
10.3
1.1
12.0
0.6
2.36.8
1.16.0
14.2
1.3
2.26.4
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
0.0
Switzerland
not at all/not much
abit/somewhat
quite a lot/very much
Most of students reported that they would miss their friends “quite a lot or very much” if they
had to move to another city. There is virtually no difference across regions and cantons.
137 Weighted data
138 Weighted data
115
“It is important what friend/group of friends thinks”, by main and subsamples in
%.139
Figure 5.19
100.0
75.1
80.0
73.7
77.8
77.3
77.9
75.6
71.1
74.1
60.0
40.0
20.0
21.0
3.8
23.0
18.7
25.5
21.2
19.5
23.4
3.3
17.1
5.0
4.1
3.3
3.2
2.6
2.5
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
0.0
Switzerland
totally unimportant/quite unimportant
neither/nor
quite importamt/very important
For most respondents in all regions, it is quite important or very important what their friends
think about them. The highest percentage is in French-speaking cantons.
5.3 Consumption of alcohol and cannabis
5.3.1 Leisure-time and use of substances
The instrument allowed to measure with some precision the use of several substances. The
question was, in a first round, whether or not respondents ever consumed alcohol in general
(beer, wine or spirits) and cannabis (and other drugs). Whereas only a small minority indicated
using any other illegal substances, the use of cannabis and alcohol has been admitted in
sufficient proportions to warrant detailed analyses. Beyond life-time prevalence, the actual use
(i.e. over the last 30 days) has also been measured.
139 Weighted data
116
Figure 5.20
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
55.3
Going out in the evening by substance use, life time (ltp) and last month
prevalence (lmp) in %, N=4026-4028.140
57.5
52.5
47.7
39.4
34.0
26.7
41.1
20.8
10.6
25.2
17.3
21.1
12.9
54.9
54.2
43.5
45.9
24.7
15.3
42.7
41.7
34.7
29.5
15.7
12.4
50.5
44.1
14.8
13.2
Never 1-2
3-6 Never 1-2
3-6 Never 1-2
3-6 Never 1-2
3-6 Never 1-2
3-6
times time
times time
times time
times time
times time
per per
per per
per per
per per
per per
week week;
week week;
week week;
week week;
week week;
every
every
every
every
every
day
day
day
day
day
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp) ***
No alcohol/cannabis
Spirits (lmp) ***
Cannabis (ltp) ***
Yes alcohol/cannabis
Consumption of substances (alcohol in general, beer, wine, spirits and cannabis) is associated
with going out in the evening. The association is particularly strong with respect to cannabis.
The use of legal as well as illegal substances goes along with extreme forms of going out. It is
much more common among respondents who go out more than three times a week (Figure 5.20)
and those who, on weekends, return home after midnight (Figure 5.21) or in the early morning
hours only.
140 Weighted data
117
Figure 5.21
60.0
Time of coming back home after going out in the evening by alcohol/cannabis,
life time(ltp) and last month prevalence (lmp) in %, N=3783-3785.141
51.2
50.0
43.9
41.6
40.0
31.1
30.0 24.0
20.0
10.0
16.0
13.1
13.0
4.2
2.8 0.9
1.1
1.0
42.4
39.6
36.8
41.4
38.1
35.3
22.0
16.7
39.5
37.8
37.0
26.2
37.2
37.1
29.1
20.620.6
13.7
12.8
5.3 5.6
1.5 1.3
0.6
8.6
13.2
12.4
6.1
2.2 1.1
0.7
13.8
13.1
13.1
8.3
5.3
1.0 1.2
0.7
12.0
11.3 10.0 13.3
7.3
1.5 1.2
0.5
I do not go out in the eve
00:00 - 2:45
3:00 - 6:30
7:00 - 9:30
10:00 - 19.45
20:00 - 24:00
00:00 - 2:45
3:00 - 6:30
7:00 - 9:30
10:00 - 19.45
20:00 - 24:00
00:00 - 2:45
3:00 - 6:30
7:00 - 9:30
10:00 - 19.45
20:00 - 24:00
00:00 - 2:45
3:00 - 6:30
7:00 - 9:30
10:00 - 19.45
20:00 - 24:00
00:00 - 2:45
3:00 - 6:30
7:00 - 9:30
10:00 - 19.45
20:00 - 24:00
0.0
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp) ***
No alcohol/cannabis
Spirits (lmp) ***
Cannabis (ltp) ***
Indeed, alcohol and cannabis use is relatively infrequent among those who never go out or who
return home before midnight, but clearly most frequent among those who return later or even
after 3 AM. Again, the difference is stronger for hard liquor and cannabis than for beer and wine.
141 Weighted data
118
Spending time with friends and family by alcohol/cannabis, life time (ltp) and
last month prevalence (lmp) in %, N=4055-4058.142
48.4
42.6
48.1
50.0
39.1
40.0
32.6
34.4
29.5
30.0
16.7
20.0 11.7 14.6
7.7
10.0
48.2
43.8
26.4
11.2 11.9
5.2
9.6
7.9
12.5
47.9
43.3
31.4
23.1
23.5
19.7
w/ family
60.0
on my own
Figure 5.22
46.7
44.0
37.8
26.2
24.5
19.7
10.8 9.3
5.0
39.9
21.3
10.2 8.6
4.8
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp) ***
No alcohol/cannabis
Spirits (lmp) ***
w/ larger group of friends
w/ 1-3 friends
w/ family
on my own
w/ 1-3 friends
w/ family
on my own
w/ 1-3 friends
w/ 1-3 friends
w/ family
on my own
w/ 1-3 friends
w/ family
on my own
0.0
Cannabis (ltp) ***
Spending one’s leisure-time alone or with other family members goes along with less use of
alcohol and/or cannabis. Particularly those who spend time mostly with groups of four friends or
more tend to use substantially more hard liquor and cannabis.
142 Weighted data
119
Figure 5.23
60.0
Friends with parents of foreign origin by alcohol/cannabis, life time (ltp) and last
month prevalence (lmp) in %, N=4041-4043.143
54.4
48.7
50.0
52.0
48.6
37.3
30.4
36.0
40.0
27.3
30.0
20.0 14.3
10.4
10.0
5.0
3.9
53.1
51.3
49.3
13.2
9.3
44.8
36.1
31.9
4.8
4.4
52.2
41.1
30.9
29.7
13.5
6.3 7.5
4.2
12.6
8.3
44.7
40.8
13.1
6.9 5.9
3.7
8.3
3.8
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp) ***
No alcohol/cannabis
Spirits (lmp) ***
all of them
many of them
a few
none at all
all of them
many of them
a few
none at all
all of them
many of them
a few
none at all
all of them
many of them
a few
none at all
all of them
many of them
a few
none at all
0.0
Cannabis (ltp) ***
Interestingly, there is a moderate association between having mostly or exclusively friends of
immigrant background on one hand and consumption of substances, especially of cannabis. We
suspect this to be related to a life-style that implies going out frequently and during late hours.
143 Weighted data
120
Figure 5.24
80.0
70.0
60.0
50.0
40.0
Leisure time: going to coffee bars or pop concerts by alcohol/cannabis use, life
time (ltp) and last month prevalence (lmp) in %, N=4031-4036.144
69.5
62.7
45.6
61.7
58.0
50.9
47.7
38.7
39.0 37.9
34.6
58.8
52.5
50.4
50.5
36.5 37.6
36.0 35.4
27.9
30.0
20.0
13.0
3.6
11.4
2.9
10.6
4.1
10.4
2.7
6.8
2.6
10.0
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp) ***
No alcohol/cannabis
Spirits (lmp) ***
often
sometimes
never
often
sometimes
never
often
sometimes
never
often
sometimes
never
often
sometimes
never
0.0
Cannabis (ltp) ***
There also seems to be a fairly strong association between going to coffee bars or pop concerts
and the use of substances.
144 Weighted data
121
Figure 5.25
Leisure time: doing something creative (theater, music, draw, write, reading
books) by alcohol/cannabis use, life time (ltp) and last month prevalence (lmp) in
%, N=4030-4034.145
60.0
50.0
40.0
55.6
53.5
44.7
31.7
46.5
40.1
33.2
36.2
28.2
22.1
30.0
39.7
38.1 36.2
34.8
37.8
32.1
34.7
27.0
24.1
26.0
21.4
38.0
29.9
36.3
27.3
25.8 25.7
18.6
16.6
20.0
38.0
10.0
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp)
No alcohol/cannabis
Spirits (lmp) ***
often
sometimes
never
often
sometimes
never
often
sometimes
never
often
sometimes
never
often
sometimes
never
0.0
Cannabis (ltp) ***
145 Weighted data
122
Figure 5.26
Leisure time: studying at school, doing homework by alcohol/cannabis, life time
(ltp) and last month prevalence (lmp) in %, N=4032-4036.146
70.0
58.9
52.5
58.6
60.0
48.4
50.0
20.0
10.0
56.8
54.1
45.7
39.6
40.0
26.9
30.0
59.2
53.0
57.0
54.1
17.1
10.0
7.8
5.9
25.9
23.0
18.1
14.5
39.5
35.9
37.8
26.3
21.3
19.5
16.9
8.1
7.6
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp)
No alcohol/cannabis
Spirits (lmp) ***
often
sometimes
never
often
sometimes
never
often
sometimes
never
often
sometimes
never
often
sometimes
never
0.0
Cannabis (ltp) ***
Respondents, who do not drink alcohol and who do not smoke cannabis, are more likely doing
homework and studying at school in their free time.
On the other hand, socially well accepted leisure-time activities, such as arts, reading and the like
are going along with less drinking beer and spirits as well as with less smoking cannabis. Wine
stands out as an exception, probably because drinking wine is often related to conformist
activities.
146 Weighted data
123
Alcohol (ltp) ***
Beer (lmp) ***
No alcohol/cannabis
90.5
76.4
72.1
20.7
Wine (lmp)
Spirits (lmp) ***
never
7.3
2.1
sometimes
7.4
2.25.2
often
sometimes
6.5
2.65.1
often
18.4
often
13.9
8.8
2.63.8
often
never
sometimes
14.8
7.1
2.73.1
often
sometimes
11.3
6.9
91.3
88.6
80.9
never
90.2
81.4
sometimes
90.4
85.5
never
100.0
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Leisure time: engaging in fights with others by alcohol/cannabis, life time (ltp)
and last month prevalence (lmp) in %, N=4030-4032.147
never
Figure 5.27
Cannabis (ltp) ***
Aggressive behaviour is associated with drinking. Surprisingly but in line with earlier work in
connection with ISRD-2, the association is even stronger among cannabis users.
147 Weighted data
124
43.2
39.0
35.1 36.3
40.0
Alcohol (ltp) ***
Beer (lmp) ***
24.7
43.9
38.8
40.5
No alcohol/cannabis
Spirits (lmp) ***
often
15.6
sometimes
sometimes
Wine (lmp)
22.9
21.3
19.0
never
24.8
never
often
21.4
sometimes
often
sometimes
18.9
22.6
38.6 38.3
32.0
30.4
28.1
42.3
38.7
often
42.3
38.4
sometimes
40.2
never
41.4
37.0
never
44.2
never
50.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Leisure time: hanging out in shopping centers, parks, streets etc. for fun by
alcohol/cannabis use. life time (ltp) and last month prevalence (lmp) in %,
N=4034-4039.148
often
Figure 5.28
Cannabis (ltp) ***
Hanging out in shopping centres, parks, streets and similar locations (just for having fun) goes
along with more frequent use of substances. The difference is more substantial for spirits and
cannabis.
148 Weighted data
125
Figure 5.29
87.4
82.6
82.8
77.1
80.7
64.8
55.6
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp)
No alcohol/cannabis
16.9
11.9
2.5
Spirits (lmp) ***
18.4
2.3
sometimes
never
never
often
sometimes
never
often
14.6
11.3
3.9
42.4
39.2
often
19.0
9.3
2.9
sometimes
never
6.6
2.5
often
sometimes
14.4
40.2
33.1
sometimes
35.7
28.6
10.0
47.9
often
55.0
never
100.0
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Leisure time: doing something illegal to have fun by alcohol/cannabis use, life
time (ltp) and last month prevalence (lmp) in %, N=4028-4033.149
Cannabis (ltp) ***
Doing something illegal just for fun is far more common among users of spirits and cannabis.
Beer (lmp) ***
57.9
32.1
21.3
Wine (lmp)
No alcohol/cannabis
31.1
22.7
sometimes
never
never
Spirits (lmp) ***
often
11.0
4.2
4.48.0
4.87.9
often
often
sometimes
never
often
sometimes
32.9
22.6
4.57.0
4.06.1
Alcohol (ltp) ***
59.8
59.1
30.8
21.0
73.1
often
62.2
28.5
17.5
74.3
72.6
sometimes
74.5
65.3
sometimes
78.5
never
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Leisure time: frightening and annoying people just for fun by alcohol/cannabis,
life time (ltp) and last month prevalence (lmp) in %, N=4028-4033.150
never
Figure 5.30
Cannabis (ltp) ***
149 Weighted data
150 Weighted data
126
Frightening and annoying people just for fun is, once more, associated with use of substances
and, in particular, with consuming spirits and cannabis.
5.3.2 Peers, friends and the use of substances
Contrary to leisure-time behaviour, having ties to friends is only weakly associated with the use
of alcohol or cannabis. This holds true for missing one’s friends in case of moving to a different
city, or having a group of friends to spend time with (Figure 5.31). This means that using alcohol
or cannabis does not necessarily help to make friends.
Figure 5.31
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Having a group of friends to spend time with, by alcohol/cannabis use, life time
(ltp) and last month prevalence (lmp) in %, N=4037-4043.151
85.4
74.7
82.5
71.6
28.4
17.5
25.3
14.6
84.2
77.0
84.8
75.8
24.2
15.2
23.0
15.8
84.7
76.8
23.2
15.3
No group Group of No group Group of No group Group of No group Group of No group Group of
of friends friends of friends friends of friends friends of friends friends of friends friends
Alcohol (ltp) ***
Beer (lmp) ***
Wine (lmp)
No alcohol/cannabis
Spirits (lmp) ***
Cannabis (ltp) ***
On the other hand, knowing friends who use drugs is strongly associated with use of all
substances, but particularly of cannabis.
151 Weighted data
127
Figure 5.32
100.0
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Having friends who use drugs by alcohol/cannabis, life time (ltp) and lastmonth
prevalence (lmp) in %, N=4056-4058.152
86.3
77.6
45.5
68.9
54.5
35.4
22.4
No
friends
using
drugs
64.6
Having
friends
using
drugs
Alcohol (ltp) ***
31.1
62.0
37.5
62.5
38.0
70.6
68.3
67.1
32.9
31.7
29.4
13.7
No
friends
using
drugs
Having
friends
using
drugs
Beer (lmp) ***
No
friends
using
drugs
Having
friends
using
drugs
Wine (lmp)
No alcohol/cannabis
No
friends
using
drugs
Having
friends
using
drugs
Spirits (lmp) ***
No
friends
using
drugs
Having
friends
using
drugs
Cannabis (ltp) ***
Students, who drink alcohol and consume marihuana, are more likely to know friends who use
drugs. This association is especially strong with cannabis use (life time prevalence).
Wine (lmp)
No alcohol/cannabis
27.2
Spirits (lmp) ***
27.2
72.8
29.2
Having friends
committed
shoplifting
36.8
70.8
No friends
committed
shoplifting
Having friends
committed
shoplifting
No friends
committed
shoplifting
Beer (lmp) ***
53.5
33.4
27.4
17.4
Alcohol (ltp) ***
46.5
63.2
Having friends
committed
shoplifting
56.0
44.0
No friends
committed
shoplifting
49.2
72.8
66.6
Having friends
committed
shoplifting
50.8
72.6
No friends
committed
shoplifting
82.6
No friends
committed
shoplifting
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Having friends who committed shoplifting by alcohol/cannabis use, life time
(ltp) and last month prevalence (lmp) in %m N=4056-4058.153
Having friends
committed
shoplifting
Figure 5.33
Cannabis (ltp) ***
The role of qualitative aspects of leisure-time activities and peer networks is further underlined
by Figure 5.33 and the following figures. Indeed, respondents who know friends who have
committed offences such as shoplifting, burglary, robbery and assault, are all more likely to have
152 Weighted data
153 Weighted data
128
used also substances. The associations are particularly strong for spirits and cannabis (see the
following Figures 5.34-5.36).
Beer (lmp) ***
Wine (lmp)
No alcohol/cannabis
61.4
38.6
32.3
14.3
Spirits (lmp) ***
Having friends
committed
burglary
15.0
No friends
committed
burglary
26.5
17.5
Having friends
committed
burglary
No friends
committed
burglary
Having friends
committed
burglary
Alcohol (ltp) ***
85.0
Having friends
committed
burglary
27.9
14.7
23.9
11.5
85.7
67.7
82.5
73.5
No friends
committed
burglary
85.3
72.1
No friends
committed
burglary
88.5
76.1
No friends
committed
burglary
100.0
80.0
60.0
40.0
20.0
0.0
Having friends who committed burglary by alcohol/cannabis use, life time(ltp)
Having friends
committed
burglary
Figure 5.34
Cannabis (ltp) ***
Students, who have already tried alcohol/cannabis or drank alcohol last 30 days, are more likely
to know friends, who committed burglary.
Beer (lmp) ***
Wine (lmp)
No alcohol/cannabis
97.3
81.7
Spirits (lmp) ***
No friends
committed
robbery
Having friends
committed
robbery
18.3
2.7
13.1
2.7
Having friends
committed
robbery
Having friends
committed
robbery
No friends
committed
robbery
Having friends
committed
robbery
Alcohol (ltp) ***
13.1
3.9
3.39.8
2.07.6
97.3
86.9
96.1
86.9
No friends
committed
robbery
96.7
90.2
No friends
committed
robbery
98.0
92.4
No friends
committed
robbery
120.0
100.0
80.0
60.0
40.0
20.0
0.0
Having friends who committed robbery by alcohol/cannabis use, life time (ltp)
Having friends
committed
robbery
Figure 5.35
Cannabis (ltp) ***
154 Weighted data
155 Weighted data
129
Wine (lmp)
No alcohol/cannabis
Spirits (lmp) ***
92.8
70.4
29.6
Cannabis (ltp)
***
Having friends
committed assault
7.2
No friends committed
assualt
Having friends
committed assault
27.7
6.0
assualt
Having friends
committed assault
Having friends
committed assault
assualt
Having friends
committed assault
Alcohol (ltp) *** Beer (lmp) ***
94.0
72.3
21.2
5.6
19.4
7.9
16.5
6.4
13.9
3.3
94.4
78.8
92.1
80.6
assualt
93.6
83.5
assualt
96.7
86.1
assualt
120.0
100.0
80.0
60.0
40.0
20.0
0.0
Having friends who committed assault by alcohol/cannabis use, life time (ltp)
and last month prevalence (lmp) in %, N=4056-4058.
Having friends
committed assault
Figure 5.36
Cannabis (lmp)
***
As one can see, the association with hard liquor and cannabis use is particularly strong for
robbery which is, presumably, considered the most “criminal” offence.
130
5.4 Computer games as other types of leisure-time activities
This part of Chapter 5 includes some results of the module (13) that was about computer games
and its impact on delinquency. It includes a lot of variables and 7 types of computer games. We
discuss only 3 of them:
-
-
-
Ego-shooter (a computer video game genre centered on gun and projectile weapon-based
combat through a first player; the player experiences the action through the eyes of
the protagonist, and in some cases, the antagonist);
Fighting/violence (in which the player either (a) controls an on-screen character and
engages in close combat with an opponent, or (b) is involved in controversial video
games, some of them have been banned or censored because of rudeness, violence, etc.)
Strategy (emphasizes skillful thinking and planning with strategic, tactical, and
sometimes logistical challenges).
Figure 5.36_1
100.0
80.0
77.1
“Do you play computer games?” In %156.
73.6
84.6
87.1
79.4
72.7
74.4
65.6
60.0
40.0
22.9
26.4
20.0
15.4
20.6
FR
(N=956)
ITA
(N=642)
27.3
34.4
25.6
12.9
0.0
Switzerland
DE
(4'158)
(N=2'560)
No
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
Yes
The highest percentage of those, who play computer games, is among Swiss-German
respondents, particularly in the canton of Zurich.
156
Results are on the base of the available cases. The level of missing cases is between 1.0% -13.9%.
131
Ego-shooter as a favorite genre of computer games in %157.
Figure 5.36_2
100.0
80.0
60.0
40.0
20.0
0.0
87.0
68.6
67.4
68.1
32.6
31.4
72.6
31.9
Switzerland
DE
(N=2'560)
FR
(N=956)
36.4
27.4
13.0
78.0
63.6
ITA
(N=642)
SG
(N=625)
Not quoted
Quoted
AG
(N=555)
72.3
22.0
27.7
GE
(N=268)
ZH
(N=266)
Genre of Ego-shooter computer video games is evenly popular in most regions of Switzerland,
except Ticino.
“How long do you play ego-shooter per day?” In %158.
Figure 5.36_3
80.0
71.2
69.2
65.5
62.5
67.1
65.4
67.4
67.1
60.0
40.0
20.2
20.0
10.6
21.1
19.8
9.0
13.5
21.0 16.6
24.5
21.3
8.4
13.3
18.8
24.3
13.9
8.7
0.0
Switzerland
DE
(N=2'560)
FR
(N=956)
never, <15 min. per day
ITA
(N=642)
SG
(N=625)
15 min.-3 h. per day
AG
(N=555)
GE
(N=268)
ZH
(N=266)
more than 3 hours per day
Again with the exception of Ticino, time invested in ego-shooter games is about equal across the
country.
157
158
132
Fighting/violence as a favorite genre of computer game genre in %159.
Figure 5.36_4
100.0
83.6
81.8
80.0
79.1
84.0
76.8
78.2
88.3
77.9
60.0
40.0
18.2
20.0
20.9
23.2
FR
(N=956)
ITA
(N=642)
SG
(N=625)
Not quoted
Quoted
16.4
21.8
22.1
AG
(N=555)
GE
(N=268)
16.0
11.7
0.0
Switzerland
DE
(N=2'560)
ZH
(N=266)
This type of games is slightly more popular in French and Italian speaking regions, as well as in
the cantons of Aargau and Geneva.
Figure 5.36_5 “How long do you play fighting/violence per day?” In %160.
73.9
80.0
70.0
60.0
64.7
59.2
50.0
40.0
54.7
20.6
10.0
14.7
7.8
17.3
14.9
8.7
6.1
ITA
(N=642)
SG
(N=625)
53.6
36.5
31.9
30.3
10.4
57.8
39.0
38.2
30.4
30.0
20.0
54.9
54.0
10.3
9.9
0.0
Switzerland
DE
(N=2'560)
FR
(N=956)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
Intensive players of fighting/violence games are in German speaking cantons. It is specially
visible in the canton of Zurich.
159
160
133
Strategy/puzzle as favorite genre of computer game in %161.
Figure 5.36_6
100.0
71.0
50.0
69.7
73.7
30.3
29.0
79.8
72.9
71.5
70.2
26.3
29.8
28.5
27.1
20.2
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
Not quoted
Quoted
62.0
38.0
0.0
Switzerland
DE
(N=2'560)
ZH
(N=266)
Strategy/puzzle is the second popular genre of computer video games among those selected here.
It is slightly more popular in the canton of Zürich.
“How long do you play strategy/puzzle per day?” In %162.
Figure 5.36_7
80.0
60.0
40.0
20.0
59.0
59.0
38.2
37.6
3.4
59.6
35.6
55.6
41.0
64.7
68.9
65.4
53.4
44.0
2.8
4.8
3.4
2.6
DE
(N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
33.7
28.1
25.6
9.7
3.0
0.9
GE
(N=268)
ZH
(N=266)
0.0
Switzerland
AG
(N=555)
Strategy/puzzle genre of computer video games is not only the least harmful, but it also takes
less time than the two previously mentioned computer games.
More information about influence of these computer games on juvenile delinquency, see 5.7.5
“Delinquency by computer games”.
161
162
134
5.5 Changes in leisure-time activities between 2006 and 2013
It has been observed in Chapter 7 that offending seems to have increased since ISRD-2
conducted in 2006. Therefore, the question remains whether this increase can be attributed to
changes in leisure-time activities such as going out in the evenings, substance use and other
possibly explanatory factors. The following Figures present the main findings regarding several
aspects of leisure-time activities.
Figure 5.37_1 Substance use in % for 2006 and 2013, last month prevalence.163
50.0
40.0
39.1
39.1
38.8
34.6
30.0
25.0
16.2
20.0
7.2
10.0
10.1
0.0
Alcohol lmp
Either beer or wine*
ISRD-2
Spirits*
Cannabis lmp*
ISRD-3
Cannabis and alcohol did not increase over the life-time. However, recent consumption of spirits
and cannabis (last month prevalence) increased in 2013 in comparison with 2006. These
substances are very popular during night-time activities. The following figure illustrates this
further and explains rising percentage of those, who go out 3-6 times per week and consume
more alcohol in general and more spirits.
163 Weighted data
135
Figure 5.37_2
74.6
69.8
Alcohol (ltp)
Beer and/or wine
(lmp)
never
10.6
Spirits (lmp)
1-2 times per week
Cannabis (lmp)
ISRD-3***
13.1
4.0
34.0
31.2
24.6
18.4
15.0 11.5
13.2
6.4
3.3
2.8
0.84.2
ISRD-2***
18.2
27.8
45.2
31.3
ISRD-3***
ISRD-2***
ISRD-3***
12.6
50.8
44.3
ISRD-2***
36.5
ISRD-3***
41.9
ISRD-2***
55.2
40.5
ISRD-3***
82.1
68.3
ISRD-2***
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Going out in the evening (IV) and substance use (DV) in 2006 and 2013,
life time (ltp) and last month prevalence (lmp) in %, N=4039-4042.164
Cannabis (ltp)
Use of all substances is associated with going out at night. Those who go out more frequently
also use alcohol and cannabis more often. However and as Figure 3.57a illustrates, the
association has remained stable, from 2006 to 2013, between going out and using substances, but
the level of recent use of spirits and cannabis has increased substantially.
136
Going out in the evening in % for 2006 and 2013.165
Figure 5.38_1
60.0
50.0
40.0
30.0
20.0
10.0
0.0
48.3
38.1
45.2
32.9
ISRD-2
18.8
never
16.7
1-2 times per week
ISRD-3
Contrary to what one might have expected, the frequency of going out has decreased rather than
increased. Particularly the group of students who never go out in the evening has substantially
increased. Several reasons may help to explain this surprising observation. It could be, as several
other surveys suggest, that more juveniles spend time nowadays on the Internet rather than in the
company with others. Unfortunately, there was no such measure in the instrument of ISRD-2.
Second, the question did not specify, in 2006, at what hour students returned home most of the
time. Given the very strong association between returning at late-hours and consumption of
substances (see above, Figure 5.21) as well as with delinquency (see below, Figure 5.69), a shift
to staying out longer may have occurred that cannot be identified with the two instruments.
Third, the questionnaires of neither of the two surveys asked more precisely what kind of activity
was the reason for going out in the evening. Given the increasing popularity of Internet and the
difficulties of many organizers of traditional leisure-time activities, such as sports, to recruit and
keep new members, the lower frequency of going out may have gone at the expense of more
traditional activities rather than late-hour outdoor and other high-risk activities. Given the
absence of data to corroborate these possibilities, we present these ideas only under the form of
speculative hypotheses.
137
Figure 5.38_2
“With whom do you spend most of your free time?” in % for 2006 and
2013.166
50.0
43.1
44.4
40.0
25.6
30.0
24.7
22.0
24.3
20.0
10.0
6.6
9.3
0.0
by my own
With my family
ISRD-2
With 1-3 friends
with more than 4 friends
ISRD-3
In 2013, more respondents spend time by their own, compared to 2006. On the other hand,
spending time with the family has become slightly less popular.
138
Figure 5.39
“Do you have friends with parents of foreign origin?” in % for 2006 and 2013.167
60.0
51.3
50.8
40.0
32.6
24.7
17.4
20.0
12.1
6.6
4.5
0.0
none at all
a few
many of them
ISRD-2
all of them
ISRD-3
The proportion of students who do not socialize with peers of foreign origin has decreased, and
more respondents say having many friends with origins abroad. This certainly reflects the
increasing proportion of the immigrant population in Switzerland and particularly at schools. At
the other extreme, there are less respondents indicating that they have only friends from abroad –
a sign that “segregation” may have decreased.
Figure 5.40
60.0
Leisure time: goingto coffee bars or pop concerts in % for 2006 and 2013.168
50.4
55.1
50.0
38.8
40.0
39.8
30.0
20.0
9.2
10.0
5.1
1.6
0.0
never
sometimes
Going to coffee bars or pop concerts ISRD-2
often
always
Going to coffee bars or pop concerts ISRD-3
In 2013, fewer respondents say going to discos or pop concerts in 2013, in comparison with
2006.
139
Figure 5.41
Leisure time: drinking alcohol and taking drugs in % for 2006 and 2013.169
100.0
80.0
80.0
69.4
60.0
40.0
20.2
20.0
15.0
7.3
5.0
3.1
0.0
never
sometimes
Drinking beer/alcohol/taking drugs ISRD-2
often
always
Drinking beer/alcohol/taking drugs ISRD-3
Consuming substances (alcohol and/or drugs) seems to have decreased during leisure-time spent
outdoors. (A slight change in the wording of the relevant items in the instruments, from ISRD-2
to ISRD-3, should be noted.) Since, according to the direct questions regarding use of alcohol
and cannabis, the recent use (over the last 30 days) of spirits and cannabis seems to have
increased, the apparent contradiction with the findings presented here might point to a possible
shift in the use of substances to indoor settings.
Figure 5.42
Leisure time: doing sports in % for 2006 and 2013.170
54.4
60.0
50.0
36.9
40.0
31.5
34.1
30.0
20.0
15.6
14.1
13.4
10.0
0.0
never
sometimes
Doing sports, athletics, exercise ISRD-2
often
always
Doing sports, athletics, exercise ISRD-3
Further evidence that conformist activities may have increased comes from Figure 5.42
suggesting that sports may have gained in popularity over the past years.
140
Figure 5.43
80.0
Leisure time: frightening and annoying people just for fun in % for 2006 and
2013.171
67.5
70.7
60.0
40.0
24.7
24.0
20.0
4.9
5.3
2.9
0.0
never
sometimes
Frightening other people just for fun ISRD-2
often
always
Frightening other people just for fun ISRD-3
Harassing people (presumably in the streets) seems also to have decreased.
Figure 5.44
Having friends who use drugs in % for 2006 and 2013.172
80.0
60.0
59.2
58.4
41.6
40.8
40.0
no
yes
20.0
0.0
ISRD-2
ISRD-3
The same proportion of respondents reported in 2013 (compared to 2006) knowing friends who
use drugs. This is not in line with the trend of self-reported (actual) drug use (see Figure 5.37_1).
141
Figure 5.45
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Having friends who committed shopliftingin % for 2006 and 2013.173
63.8
56.0
44.0
36.2
no
yes
ISRD-2
ISRD-3
Fewer students report knowing friends who have committed shoplifting. Since shoplifting has
increased between 2006 and 2013 (see Chapter 7), this finding is not entirely plausible. It could
be, however, that shoplifting has become a more individual and less a group offence over time.
Figure 5.46
100.0
Having friends who committed burglary in % for 2006 and 2013.174
90.9
81.1
80.0
60.0
no
40.0
20.0
18.9
9.1
yes
0.0
ISRD-2
ISRD-3
Again in line with self-report measures of burglary (that suggest that this offence has increased
since 2006, see Table 7.2), more students report knowing peers who had committed this.
Figure 5.47
100.0
Having friends who committed assault in % for 2006 and 2013.175
90.3
89.4
80.0
60.0
no
40.0
10.6
20.0
9.7
yes
0.0
ISRD-2
ISRD-3
174 Weighted data (ISRD-3, N=4158), not weighted data (ISRD-2, N=3643).data
142
Figure 5.48
100.0
Having friends who committed robbery in % for 2006 and 2013.176
94.6
93.1
80.0
60.0
no
40.0
yes
20.0
6.9
5.4
0.0
ISRD-2
ISRD-3
Although self-reported measures of robbery and assault suggest that these offences may have
increased between 2006 and 2013, the proportion of respondents who say knowing peers who
have committed these offences is perfectly stable. Given the relative rarity of these offences,
fewer people among peers may come to know about it. Further, burglary requires often some
cooperation from others, including fences, which increases the probability that more people will
learn about it.
Overall, the results about changes in leisure-time activities do not offer plausible explanations
for increasing trends of self-reported offending (see Table 7.2). This is not the say that the selfreport measures are not “true”, but that the causes of the observed trends must be looked for in
other areas that are not reflected in the questionnaires of ISRD-2 and ISRD-3. On the other
hand, the results on peers are more mixed, some being in line with trends in self-reported
delinquency.
143
5.6 Happiness, leisure-time, peers and substance use
We begin the presentation of the findings on happiness with the basic frequencies in the national
and the several regional samples.
“Would you say that most of the time you have been happy during last 6
months? by main and subsamples in %.177
Figure 5.49
70.0
60.1
58.9
60.0
63.7
59.3
56.2
63.1
57.6
55.3
50.0
40.0
35.4
35.3
35.0
34.3
36.4
31.8
33.4
33.1
30.0
20.0
10.0
5.8
4.4
8.8
6.4
4.5
5.9
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
11.6
3.5
0.0
Switzerland
DE
(N=2'560)
unhappy
neither/nor
GE
(N=268)
ZH
(N=266)
happy
The level of happiness is approximately the same in different regions. The highest percentage of
(very) unhappy students can be found in French speaking cantons, the lowest in the cantons of
Zurich and St. Gallen.
Figure 5.50
Happiness by doing sports in leisure time in %, N=4096.178
80.0
65.2
60.0
42.3
30.3
40.0
20.0
45.9
40.6
54.1
11.8
5.3
4.5
0.0
(very) un(very) happy
neither/nor
never
sometimes
(very) happy
often
Respondents who often practice sports during leisure time are more often happy than their peers.
This may be due to a better body-feeling and (perceived) higher attractiveness.
177 Weighted data
178 Weighted data
144
Figure 5.51
Happiness by studying at school and doing homework in leisure time in %,
N=4096.179
45.3
40.5
50.0
40.0
28.630.8
22.9
30.0
20.0
10.0
13.8
6.4
5.2 3.1 2.8
2.2 1.7
31.5
19.9
14.513.6
9.7 7.4
0.0
very unhappy
unhappy
more unhappy
than happy
never
more happy
than unhappy
sometimes
happy
very happy
often
Investing leisure-time for school-related homework and studies is only weakly associated with
happiness. Students devoting much of their leisure-time to such activities are slightly happier,
probably because they resent more satisfaction at school and in their environment.
Figure 5.52
Happiness by doing something creative in %, N=4084.180
80.0
58.2
60.0
35.4
40.0
20.0
6.4
4.5
33.7
61.7
56.7
36.8
6.6
0.0
neither/nor
never
sometimes
(very) happy
often
Students who, during leisure-time, are often doing something creative (such as playing theatre or
music, or reading) are more often unhappy. Although the difference is not large, this result is
rather unexpected and, at first sight at least, hard to explain. Could social isolation be the factor
behind this association?
179 Weighted data
180 Weighted data
145
Figure 5.53
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Happiness by going to coffee bars or pop concerts in %, N=4085.181
42.741.9
33.5
28.226.8
24.8
22.5
17.316.2
5.3
2.7 1.9
very unhappy
9.1 8.7 9.1
3.4 3.1 2.9
unhappy
more unhappy
than happy
never
more happy
than unhappy
sometimes
happy
very happy
often
On the other hand, no clear pattern emerges with respect to going to coffee bars and pop concerts
during leisure-time. Respondents who often go to such places are somewhat more often “very
unhappy”, but they are also more often “very happy”.
Figure 5.54
Happiness by engaging in fights with others in leisure time in %, N=4082.182
50.0
42.342.1
40.0
26.328.6
30.0
20.0
10.0
14.9
29.8
16.915.3
14.0
8.9 9.7 9.1
2.1 2.3
28.9
3.4 2.0 3.3
0.0
very unhappy
unhappy
more unhappy
than happy
never
more happy
than unhappy
sometimes
happy
very happy
often
Respondents who said often engaging in fighting with others during leisure-time can be both
very happy and very unhappy. Overall, however, students who say never engaging in fights with
others are more often happy.
181 Weighted data
182 Weighted data
146
Figure 5.55
Happiness and hanging out in shopping centers, parks and streets for fun in
leisure time in %, N=4089.183
80.0
61.9
60.0
34.2
40.0
20.0
4.0
4.1
36.2
59.7
54.2
35.1
10.7
0.0
neither/nor
never
(very) happy
sometimes
often
Students, who are hanging out in shopping centres, parks and streets for fun are more likely to be
(very) unhappy than their peers.
Figure 5.56
Happiness by doing something illegal for fun in leisure time in %, N=4081.184
80.0
61.2
60.0
34.3
40.0
20.0
39.3
53.6
51.5
31.4
17.2
4.6
7.1
0.0
neither/nor
never
sometimes
(very) happy
often
Respondents who report doing something illegal for fun are 3 times more likely to be (very)
unhappy than their peers.
183 Weighted data
184 Weighted data
147
Figure 5.57
Happiness by drinking beer/alcohol and taking drugs in leisure time in %,
N=4076.185
80.0
60.2
60.0
34.7
40.0
20.0
5.1
7.4
36.0
41.7
56.6
47.1
11.3
0.0
neither/nor
never
sometimes
(very) happy
often
Students who consume alcohol and drugs during their free time, are 3 times more likely to be
(very) unhappy than their peers.
185 Weighted data
148
Alcohol (ltp)***
Wine (lmp)*
No alcohol/cannabis
Spirits (lmp)***
(very) happy
5.08.7
neither/nor
(very) happy
neither/nor
neither/nor
Beer (lmp)*
40.3
34.3
4.97.8
5.36.5
(very) unhappy
(very) happy
neither/nor
5.36.5
(very) unhappy
3.77.0
60.7
51.0
41.3
33.1
37.4
34.2
(very) happy
37.4
34.2
neither/nor
37.5
31.8
62.0
50.9
60.5
56.1
(very) unhappy
60.5
56.1
(very) unhappy
64.5
55.5
(very) unhappy
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Happiness by alcohol/cannabis (life time prevalence) in %, N=4050-4051.186
(very) happy
Figure 5.58
Cannabis (ltp)***
When the several substances are considered individually, it turns out that there is almost no
difference, in terms of happiness, among those who admit drinking beer or wine and those who
do not. However, the differences are larger among those who use spirits and cannabis.
Figure 5.59
Happiness by frightening and annoying people in leisure time in % N=4082.187
70.0
59.7
60.0
58.3
54.2
50.0
34.7
40.0
37.2
31.9
30.0
20.0
10.0
13.9
5.6
4.5
0.0
neither/nor
never
sometimes
(very) happy
often
Those who admit often frightening and annoying people during their free time are almost 3 times
more (very) unhappy than those who say never or only occasionally doing this.
186 Weighted data
187 Weighted data
149
Figure 5.60
Happiness by group of friends to spend time with in %, N=4093.188
50.0
39.5
40.0
24.8 26.7
30.0
18.3 16.9
20.0
10.0
42.4
10.7 8.5
3.7 2.2
2.9 3.3
very unhappy
unhappy
0.0
more unhappy more happy than
than happy
unhappy
no
happy
very happy
yes
There is only a very week association between having friends to spend time with and happiness.
Those who say having such friends are slightly happier than those who do not. This suggests that
those who prefer spending time on their own may make a deliberate choice, or at least not feel
unhappy because of their relative social isolation.
Figure 5.61
Happiness by having friends with parent(s) of foreign origin in %, N=4112.189
70.0
61.3
54.8
60.0
50.0
40.0
33.7
38.1
30.0
20.0
5.0
10.0
7.1
0.0
(very) unhappy
neither/nor
none at all/a few
(very) happy
Many of them/all of them
Although having friends to spend time with does not seem to increase happiness, having friends
of foreign origin apparently does add to feelings of well-being. Having friends across ethnic lines
might be related to popularity among peers, but it must be admitted that this explanation remains,
for the time being and in the absence of more complete data, rather speculative.
188 Weighted data
189 Weighted data
150
Figure 5.62
Happiness by "it is important, what my friend thinks about me” in %, N=3217.190
50.0
43.6
40.0
24.9 26.7
30.0
25.6
15.9
20.0
10.0
31.6
4.9
10.2 8.4
2.0
2.8 3.4
0.0
very unhappy
unhappy
more unhappy
than happy
totally/quite/a bit unimportant
more happy
than unhappy
happy
very happy
a bit/quite/totally important
Respondents who attribute much importance to what their friends think about them are
somewhat more often (very) unhappy than those who do not care that much. Although the
difference is, overall, not large, stress related to the self-imposed need to meet peers’
expectations may be the driving force behind this finding.
190 Weighted data
151
Figure 5.63
Happiness by having friends, who use drugs in %, N=4111.191
50.0
43.8
40.0
25.1 27.6
30.0
20.0
10.0
39.0
1.2
4.5
3.1 3.5
7.1
19.8
13.6
11.7
0.0
very unhappy
unhappy
more unhappy
than happy
no
more happy
than unhappy
happy
very happy
yes
Respondents who have friends using drugs are less happy than those, who have so such friends.
Figure 5.64
Happiness by having friends, who committed shoplifting in %, N=4111.192
50.0
44.3
37.4
40.0
30.0
25.1
19.0
20.0
10.0
27.9
14.0
12.0
1.8 4.0
2.4
4.7
7.3
0.0
very unhappy
unhappy
than happy
unhappy
no
happy
very happy
yes
Respondents whose peers have committed shoplifting are less happy than those who have so
such friends.
191 Weighted data
192 Weighted data
152
Figure 5.65
Happiness by having friends, who committed burglary in %, N=4110.193
50.0
43.4
40.0
34.8
26.0 26.8
30.0
17.7
20.0
10.0
1.8
5.7
2.6
6.1
8.4
11.6
15.0
0.0
very unhappy
unhappy
than happy
unhappy
no
happy
very happy
yes
Respondents whose friends have committed burglary are less happy than those who have so such
peers.
Figure 5.66
Happiness by having friends, who committed robbery in %, N=4111.194
50.0
42.6
40.0
26.4
30.0
20.0
10.0
10.5
2.1
27.7
21.8
17.0
14.5
3.2 5.0
20.5
8.7
0.0
very unhappy
unhappy
more unhappy
than happy
no
more happy
than unhappy
happy
very happy
yes
Respondents whose friends have committed robbery are less happy than those who have so such
peers.
193 Weighted data
194 Weighted data
153
Figure 5.67
Happiness by knowing friends, who committed assault in %, N=4110.
50.0
42.7
40.0
33.3
26.3 25.0
30.0
20.0
10.0
2.2
5.8
3.0
6.1
8.6
17.2 17.4
12.4
0.0
very unhappy
unhappy
more unhappy
than happy
no
more happy
than unhappy
happy
very happy
yes
Respondents with friends who committed assault are less happy than those who have so such
peers.
Overall, it seems that happiness is not much related to conventional activities. However, it
definitively is to deviant activities, or to being integrated in deviant networks.
154
5.7 Leisure-time, life style, peers, happiness and delinquency
5.7.1 Leisure-time and delinquency
Life-style and leisure-time activities have been identified as key variables in the explanation of
offending many years ago (Hindelang, Gottfredson and Garofalo 1978; Felson and Boba 2010).
Changes in the organisation of leisure-time and particularly of night-time activities have also
been suggested as key-factors in the explanation of changes in crime rates (Killias et al. 2012). In
the present section, we shall begin, therefore, with presenting some findings on the association
between several forms of self-reported delinquency and leisure-time activities.
Figure 5.68
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Delinquency (last year prevalence) by going out in the evening in %, N=40444052.195
22.4
25.0
19.5
18.4
14.5
7.3
2.5
9.8
3.0
19.0
13.9
12.9
6.9
19.3
5.6 5.6
0.7 1.9
0.5
Never
7.6
5.9
4.9 5.0
4.4
1.5 0.4
0.9 1.4
0.8
0.3
1-2 times per week
9.8
6.1
10.5
7.7
2.2
2.8
0.6
4.8
0.7
5.5
3.5
2.9
3-6 time per week; every day
There seems to be a fairly linear association between the frequency of going out in the evening
and all self-reported offences listed in the instrument. However, respondents who say going out
five times and more a week have far higher rates of offending. This underlines that extreme
leisure-time activities may be more important than just going out as such.
195 Weighted data
155
Figure 5.69
Delinquency (last year prevalence) by time of coming back home after going out
at night in %, N=3785-3793.196
40.0
34.0
30.4 28.4
35.0
30.0
24.2
23.3 21.7
20.6 18.7
25.0 18.4 19.0
18.2
17.8
17.6
17.1
16.8
20.0 15.0
14.9
14.3
12.6
11.9
10.5
15.0
10.0 9.1
9.7
9.1
7.9
7.8
7.56.29.1
6.7
6.7
6.6
6.6 5.2
6.4 5.1
6.1
5.9 4.36.1
5.8 5.1
5.7
5.5
10.0
4.9
4.9
4.9 6.2 2.9 3.2
4.3
4.0
3.8
3.2
2.9
2.9
2.7
2.7
2.4
2.4
2.3
2.1
1.9
1.7
1.5
1.3
0.9
0.8
0.8 0.8 0.40.0
0.6
0.50.0
0.50.0
5.0
0.2
0.0
0.0 1.20.0
0.0
0.0
I do not go out in the evening
00:00 - 2:45
3:00 - 6:30
7:00 - 9:30
10:00 - 19.45
20:00 - 24:00
This is further illustrated by Figure 5.69. Those who return after midnight, and particularly after
3 AM, have far higher rates of offending in every respect than those who never go out or who
return before midnight. This variable largely explains also risks of victimization (see Chapter 4,
e.g. Table 4.1).
196 Weighted data
156
Figure 5.70 Delinquency (last year prevalence) by spending time with family and friends in %,
N=4047-4065.197
20.0
15.0
10.0
5.0
15.7
11.0
8.1 8.7
7.6
6.3
4.9
4.4
2.5
7.9
3.3
1.8 2.4
1.6
0.3
2.5
1.7
1.6
1.5 1.6
1.1
1.0
0.5
0.4
8.7
5.5
5.2
12.6
10.8
6.3
9.4
3.9
2.4
7.5
4.1
3.8
3.7
3.6
2.9
2.4
0.5
0.3
0.0
On my own
With my family
With group of friends
Students who spend most of their leisure-time with friends have the highest rates of delinquency.
The second delinquent group includes respondents who spend leisure-time primarily by their
own. Finally, the least delinquent are those who spend a lot of time with their families.
As Figure 5.71 illustrates, it is not just spending time with friends, but rather being with larger
groups (of four or more people) that is important. Larger groups are not only larger, but often
they may be qualitatively different and entail, therefore, different kinds including more risky
kinds of activities.
Figure 5.71
Delinquency (last year prevalence) by spending time with family and groups of
friends of different sizes, in %, N=4037-4065.198
25.0
20.0
15.0
20.3
15.8
13.1
9.6 8.78.3
7.6
10.0 6.37.2
4.9
4.4
2.5
5.0
16.6
15.0
12.6
12.0
11.8
11.1
8.5
7.5 6.3
6.4 5.2
5.7
5.5
5.4
5.2
4.0
3.9
3.7
3.7
3.6
3.5 2.4
3.5
3.3
3.2
2.9
2.9
2.5
2.4
2.4
1.9 0.5
1.6
1.6
1.1
1.0
0.9
0.9 1.6
0.8
0.5
0.4
0.3
0.3
0.0
on my own
w/ family
w/ 1-3 friends
197 Weighted data
198 Weighted data
157
As one would have expected, students who spend their leisure-time mostly on their own are
rarely involved in group fights. Similarly, drug dealing is next to never reported by respondents
who spend a lot of time with their families.
Motor
bike/M
otorbik
Caring
Vandali Shoplif Burglar Bicycle e/car Car Robber Person weapo Group
Drug Animal
Graffiti sm
ting
y
theft theft break
y al theft n
fight Assault dealing cruelty
Figure 5.72
Delinquency (last year prevalence) among respondents who spend leisure-time
with a larger group (of 4 or more friends) by whether or not it is considered a
gang in %, N=361-364.199
Not gang
3.2
Gang
5.8
Not gang***
8.1
Gang***
26.0
Not gang*
2.5
Gang***
22.6
Not gang***
12.3
Gang**
31.0
Not gang***
10.8
Gang***
34.2
Not gang**
8.9
Gang
16.8
Not gang*
1.4
Gang*
11.0
Not gang
2.6
Gang
5.2
Not gang
1.0
Gang
7.7
Not gang***
9.1
Gang
22.6
Not gang***
2.1
Gang
10.3
Not gang***
16.4
Gang**
32.3
Not gang***
11.2
Gang**
29.0
Not gang***
6.8
Gang
19.4
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
As one would have expected, respondents who are spending time with a group that is considered
as a gang admit at far higher rates committing offences across almost the entire list, than those
199 Weighted data
158
who say their group is not considered a gang. This suggests that the high rates of delinquency
among those spending their leisure-time with a group of four or more people are largely
attributable to the fact that, among these larger groups, quite a few can be considered as gangs.
Gang members have indeed, in Switzerland and abroad (HaymozPantillon, Maxson, Killias
2014), far higher delinquency rates than similar juveniles who happen not to belong to such a
group.
The issue of gangs has been studies in this survey in some detail (questionnaire 11.1-11.8). The
findings usually confirm earlier work done on this theme (HaymozPantillon 2010). In the
following Figures, we shall see more in detail what impact may have the kind of leisure-time
activities.
Figure 5.73
Delinquency (last year prevalence) by hanging out in shopping centers, parks,
streets etc. for fun in %, N=4028-4045.200
23.4
25.0
20.0
15.0
10.0
5.0
15.4
12.5
9.5
5.6
3.7
4.6
11.8
5.8
14.9 15.9
11.9
11.5
11.0
9.9
7.7 6.5
7.0
6.2 5.3
5.9
4.8
3.7
3.7
3.7
3.5 2.3
3.4
3.2
3.2
2.5
2.2 1.3
2.1
1.5
1.4
1.2
1.1
0.9
0.7
0.7
0.6
0.0
never
sometimes
often
Respondents who often hang out in public places are at higher risk of committing offences of all
sorts. The following Figures illustrate this further.
200 Weighted data
159
Figure 5.74
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Delinquency (last year prevalence) by going to coffee bars or pop concerts in %
N=4024-4041.201
24.5
18.3
20.2
19.7
12.5
12.0 10.2 12.2
9.2 7.9
4.4
13.9
13.0
11.6
9.7
8.9
8.7
8.7
8.4
7.7
7.6
7.2
6.4
5.8
4.0
1.9 0.6
1.6
1.4 1.8
1.2
1.1
0.7
never
sometimes
16.4
3.7
1.6
19.4
6.4
3.8
9.2
3.6
3.1
often
Students who attend coffee bars and pop concerts often rather than never or only occasionally are
more likely to commit offences of all kinds. The association is strongest with robbery, stealing
cars/motorbikes or breaking into cars, burglary, assault and drug dealing.
These offences are typically street-crimes. They can be efficiently prevented by removing young
people from the streets, or by reducing leisure-time that is being spent in the streets. The
following Figures offer further illustration to that effect.
201 Weighted data
160
Figure 5.75
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Delinquency (last year prevalence) by doing something creative in %, N=40234041.202
16.9
13.8
8.2
6.1
5.5
7.1
5.3
10.4
9.4
10.3
2.0
1.5
0.8
4.7
2.9
2.7 1.6
1.6 2.1
1.2
1.2 1.9
1.2
0.6
never
sometimes
9.7
7.3
5.0
12.0 12.2
9.4
9.3
8.3
4.9
4.6 3.4
3.9 3.9
3.1 2.8
2.9
2.7 3.3
often
Students who never engage in creative leisure-time activities (such as playing theater or music,
drawing, writing, reading books etc.), are more likely to commit an offence.
Figure 5.76
Delinquency (last year prevalence) by spending leisure-time on school-related
studies or homework in %, N=4026-4041.203
30.0
25.9 24.5
25.0
20.0
17.4
16.2
20.0 17.8
16.0
15.4
15.2
15.0
10.1
9.5
8.4
7.0
6.7 5.2
6.6 8.0 8.5
10.0
6.1
5.6
5.5 6.2
5.0
4.5
4.0
3.9 2.6
3.7
3.0
2.8
2.7
2.5
2.1 3.7
1.9
1.4
1.2
5.0
1.0
0.9
0.9
0.9
0.5
0.0
never
sometimes
often
Respondents who invest often leisure-time for school-related studies or homework are far less
involved in delinquent activities. The difference is again strongest for offences that are typically
committed in the streets.
202 Weighted data
203 Weighted data
161
A similar effect can be might be expected with respect to sports. Although not really an indoor
activity, it offers juveniles an opportunity to spend leisure-time in a structured way. The
following Figure illustrates, however, that with sports the findings are more complex and do not
allow a straightforward interpretation.
Figure 5.77
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Delinquency (last year prevalence) by doing sports in %, N=4033-4049.204
16.3
7.2 7.1
5.9
10.2
9.7
8.6
12.1
12.0
9.6
8.3
5.7
7.4 6.6
5.6
3.0
1.3
1.0
2.8
1.6
1.5 1.6
1.5 1.4
1.4
1.1
0.8
never
sometimes
10.510.4
9.0
8.9
6.1
5.8
10.1
4.1
2.8
1.8
5.6
4.5 3.7 3.8
3.2
often
Although students who say practicing sports “often” rather than occasionally or never commit
over all less offences, the differences are not as strong as in the preceding Figures and not always
significant. Group fights are even slightly more frequent among those practicing sports “often”.
This matches observations made by Walser (2013) in a similar survey in the canton of St. Gallen
where the effect of several kinds of sports has been studied in detail. As it turned out, some
sports go along with reduced delinquency, whereas other have an opposite effect, leading for
sport activities overall to an effect that is, as here, closed to zero or inconsistent at least.
5.7.2 Peer-networks and delinquency
Before we look into the effects of deviant peer activities, we begin with a look on the importance
of peer-networks as such.
204 Weighted data
162
Figure 5.78
Delinquency (last year prevalence) by "I would miss my friends if I move to
another city" in %, N=3170-3182.205
32.4
35.0
30.0 24.3
25.7 25.7
24.3
22.2
25.0
18.9
16.7
16.7 16.2
15.9 16.7
20.0
14.8
14.3
13.9
13.3
12.1
11.1
15.0
10.4 11.5
10.1
9.6
8.1
8.0
7.9
7.4
7.4
7.1
6.7
6.1 4.4
10.0
3.4
3.3
3.0
3.0
2.6
2.3
1.8
1.2
1.2
1.2
1.1
5.0
0.0
not at all/not much
neither/nor
quite a lot/very much
Respondents who do not have strong ties with their friends and who would not miss them if they
had to move to another city are more likely to commit offences of all sorts. This association is
strongest for burglary and robbery. In other words, delinquents are less integrated in peernetworks than more pro-social youths. It means that social networks should not be seen as a
source of problem behavior – the effects are the other way around.
Figure 5.79
Delinquency (last year prevalence) by "It is important for me, what my friend(s)
think(s)” in %, N=3169-3179.206
25.0
20.5
20.0 16.7
15.0
10.0
7.4
7.1
16.7
14.0
12.4
10.7
9.210.1
5.0
16.9
7.6
1.4
1.1
8.6 8.5
6.5
1.2
1.1
9.3
2.3
1.8
9.2
1.5
1.2
13.6
13.6
9.9
8.8
8.4
7.2
8.7
8.5
8.0 8.3
7.7 6.7
5.9
4.4
4.2
3.2
2.9
0.0
totally unimportant/quite unimportant
neither/nor
quite importamt/very important
205 Weighted data
206 Weighted data
163
Figure 5.79 confirms this impression. Students who do not care what their peers think about
them tend to commit more offences and particularly more street crimes.
Figure 5.80
Delinquency (last year prevalence) by friends with parents of foreign origin in %,
N=4038-4056207
30.0
24.9
21.7
25.0
19.9
19.7
19.7
19.1
17.7
20.0
16.2
15.0
13.3
12.4 10.7
15.0
11.2 10.3
9.8 8.8 9.0
9.4
9.4 9.4
9.4
9.3 7.6
8.7
7.1
6.5 6.0
6.4
10.0
5.3
5.0
4.9 4.3
4.8
4.5
4.2
3.8
3.6
3.3
3.0
2.1
2.0 0.4
1.9 3.3
1.9
1.7
1.6 3.1
1.4 1.5
5.0 2.7
0.8
0.8
0.7
0.7
0.6
0.0
none at all
a few
many of them
all of them
With respect to the ethnic composition of peer-networks, two interesting observations can be
made. First, respondents with exclusively Swiss networks, or with only few immigrants among
their friends, commit clearly less offences than those whose network consists predominantly or
exclusively of immigrant youths. This reflects probably the higher delinquent involvement
among immigrant youths in general that has been observed in Chapter 7. Second, it is interesting
to note that respondents with ethnically mixed networks report clearly fewer offences than those
from ethnically homogeneous groups. Integrating juveniles from immigrant backgrounds seems,
therefore, to go along with reduced delinquent involvement.
Figure 5.81
“Do you consider your group of friends to be a gang?” by ethnic composition of
the group (i.e. having or not friends with parents of foreign origin in one’s
group), in %.208
15.0
12.4
8.3
10.0
5.2
5.0
0.0
none at all
a few
many or all of them
207 Weighted data, N= 4158
208 Weighted data, N=4158
164
Essentially the same can be observed in Figure 5.81. Less than 5 per cent of respondents with
ethnically homogeneous (Swiss-based) networks say their group can be considered a “gang”.
Among those with homogeneous (immigrant-based) networks, only 12 percent say their group is
a “gang”. In other words, belonging to a gang is clearly a minority phenomenon and, apparently,
only moderately related to ethnic background.
5.7.3 Problem behaviour and delinquency
In the following Figures, we look at the association between several kinds of problematic
behaviour among juveniles and delinquency.
Figure 5.82
50.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Delinquency (last year prevalence) by engaging in fights with others in %,
N=4035-4040.209
40.7
30.5
26.2
38.7
26.7
17.2
4.8
6.4
35.7
10.3
22.9
16.4
4.4
0.7
3.6
18.1
5.7
0.3
never
20.9
4.9
1.3
25.9
22.2 19.6
4.4
0.3
sometimes
5.8
47.0
36.8 34.4
30.6
31.5
14.2
6.9
3.3
1.2
28.7
17.2
3.7
21.3
5.4
2.9
often
Respondents who often engage in fights with other people are more likely to commit all types of
offences. As one might have expected, the association is particularly strong for assault and group
fights, but by no means limited to these offences. This observation points to the possibility that
frequent involvement in physical confrontations is a symptom of a broader personality disorder.
209 Weighted data
165
Figure 5.83
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Delinquency (last year prevalence) by doing something illegal to have fun in %,
N=4023-4039.210
39.9
30.8
14.8
2.8
39.7
39.8
35.0
33.7
27.5
27.5
19.9
13.9 13.0
4.3
6.7
34.0
2.3
0.3
2.6
13.4
2.0
0.4
never
16.4
15.9
4.2
0.7
10.1
3.9
2.1
0.5
sometimes
21.3
15.8
5.2
3.4
20.6
7.0
1.0
11.6
1.7
11.0
4.7
2.8
often
Students who admit doing often something illegal “for fun” report more offences than their
peers. Again the difference is large for all offences. It is slightly more modest for shoplifting,
vandalism, graffiti, caring weapons and personal theft, pointing to the possibility that these
offences are somewhat more “normal”, committed by more “normal” people.
210 Weighted data
166
Figure 5.84
Delinquency (last year prevalence) by frightening and annoying other people just
for fun in %, N=4022-4039.211
30.0
24.6
25.0
20.0
15.0
10.0
26.4
22.3
21.7
17.5 16.8
12.7 12.9
15.6 16.1
9.7
5.1
5.9
12.1
9.9
8.4
5.0
28.0
26.1
1.3
0.9
3.3
10.4
7.1
3.0
2.5 1.4
1.5
0.5
0.4
6.6
5.2
14.9
12.7
4.8
1.9
4.3
16.2
8.4
3.9
15.6
6.2
1.9
0.0
never
sometimes
often
Those who often frighten or annoy other people for fun more often report having committed all
sorts of offences. The difference is particularly strong with respect to street offences like
robbery. The findings presented in Figures 5.83 and 5.84 underline the great importance of need
of excitement (looking for the “kick”) in the explanation of offending.
Figure 5.85
40.0
Delinquency (last year prevalence) by substance use (last month prevalence) in %,
N=4040-4048.212
39.9
35.0
30.0
25.0
27.2
21.3
20.0
16.2
13.1
15.0
10.0
36.8
Cannabis (last month)
Hard alcohol (last month)
Beer and/or wine (last month)
26.4
Abstinent
10.3
5.2
5.0
4.33.3
0.3
7.7
3.82.6
0.4
17.3
12.8
12.5
7.8
6.1
3.4
1.1
0.3
0.0
Shoplifting***
Burglary***
Robbery***
Personal theft***
Assault***
Drug dealing***
211 Weighted data
212 Weighted data
167
Respondents, who said having consumed alcoholic beverages or cannabis over the last 30 days,
report far more often committing offences of all sorts. Particularly impressive are the low
delinquency rates among abstinent youths. This underlines the preventive potential of policies
designed to reduce substance abuse among junior high-school populations.
5.7.4 Are delinquents happy?
Former research has shown that victims of offences tend, overall, to be less happy than people
who never have gone through this kind of experience (Staubli, Killias, Frey 2014).
The question now is whether offenders are happier than non-offenders. The following Figure
gives an answer.
Figure 5.86
Delinquency (last year prevalence) by happiness in %, N=4044-4064.213
25.0
21.7
20.0
15.0
10.0
13.5
7.2
5.6
16.5
11.3
7.4
5.0
13.8
11.0
4.3
1.3
1.2
10.0
6.5
5.7
3.5 2.3 4.8
3.4
1.3 1.9
1.2
1.0
1.0
14.3
11.1 10.8
10.4
8.9
8.8 7.5
7.2
6.6
10.3
5.0
3.6
2.8
5.4
5.3 4.9
3.6
3.4
0.0
unhappy
neither/nor
happy
As one can see, unhappy people commit far more often offences of all sorts. The association
holds throughout the list of offences, but it is strongest for street crime and other more serious
offences, and smallest for relatively “normal” offences. Given the cross-sectional nature of our
research design, the question of the causal order cannot be determined based on our data. It
might be that unhappy people are more prone to commit offences, and that offending is for them
a search for goods that might provide happiness. On the other hand, offending may make people
unhappy, among other things perhaps because delinquents live less stable social relationships
and may even be more isolated, as some findings presented above (Figures 5.78, 5.79) suggest.
213 Weighted data
168
5.7.5 Delinquency by computer games
Figure 5.86_1
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Delinquency (last year prevalence) by playing computer games in %,
N=3924-3930 214
12.8
10.7
9.8
10.7
8.3
6.9
5.6
5.0
6.46.1
4.8
6.2
7.4
6.4
1.41.2 1.62.3 1.91.1
1.21.4
no
5.45.4
3.3
2.2
3.8
2.4
yes
Respondents, who play computer games regardless its genre, are significantly more likely to
commit vandalism, personal theft and caring weapon. For the other offences, the difference is not
significant and obviously moderate at best.
Delinquency (last year prevalence) by playing “ego-shooter” as a favorite
genre of computer game in %, N=4053-4072 215
Figure 5.86_2
25.0
19.2
20.0
15.0
10.0
18.5
14.7
10.7
5.3
7.7
5.0
10.8
7.2
7.1
10.3
10.0
0.92.4
4.3
3.4
0.91.9 1.7
0.71.9
10.3
6.1
10.3
5.8
3.2
2.2
3.83.7
0.0
Not quoted
Quoted
Respondents, who play ego-shooter games are more likely to commit almost all types of
offences.
214 Weighted data
215 Weighted data
169
Delinquency (last year prevalence) by playing “fighting/violence” as a
favourite genre of computer game in %, N=4053-4071.216
Figure 5.86_3
25.0
21.8
20.0
15.0
10.0
17.1
16.8
12.3
5.9
8.4
11.9
10.9
3.6 4.8
0.9
5.0
13.8
4.7
2.9 1.8
2.3
0.8
0.8
7.0
12.8
9.4
6.2
12.0
8.0
2.3
4.0
3.64.7
0.0
Not quoted
Quoted
Students, who reported playing computer video games from the fighting/violence genre, are
more likely to have committed offences of all types than their peers.
Delinquency (last year prevalence) by playing “strategy/puzzle” as a
favourite genre of computer game in %, N=4054-4070.217
Figure 5.86_4
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
14.7
11.8
7.6
5.8
9.2
8.4
7.1
5.3
5.9
3.7
1.60.9
11.5
9.1 9.0
1.30.8
2.42.0
1.4
0.2
Not quoted
3.4 3.9
1.9
5.7
4.8 4.1
3.2
Quoted
In comparison with the previous results, playing strategy/puzzle games is only moderately
associated with delinquent behaviour.
216 Weighted data
217 Weighted data
170
Students, who are playing computer games 3 to 5 hours per day are more delinquent than those
who play less or never, regardless the genre of game.
Figure 5.86_5
Delinquency (last year prevalence) by spending time in social nets,
N=2880-2890218
25.0
22.8
19.2
20.0
15.0
10.0
5.0
12.8
9.2
6.6
3.9
4.3
15.4
14.6
13.1
10.4
15.1
12.5
6.2
4.2 3.2
1.2
0.1
4.4
0.8
0.7
3.9
3.1
1.9
1.0
0.4
0.0
7.3
5.3
9.6
8.6
6.7
3.3
13.9
5.1 5.2
3.0 2.9
1.4
3.5
3.2
3.2
0.0
I do not spend time in social net, less than 15 min.
15 min. - 3 h.
more than 3 h. per day
Students, who spend more time in social networks, are more likely to commit offences of all
types.
5.8 Summary and discussion

Leisure-time activities do not differ much across regions within Switzerland, although
some noteworthy exceptions appeared. In general, respondents in French-speaking
cantons tend to spend time more often in shopping centers, in the streets or parks.
Usually, respondents in larger urban areas, such as Geneva and Zurich, share this pattern.
In Zurich especially, going out in the evenings and returning home at very later hours is
particularly common.

On the other hand, students in French- and Italian-speaking cantons share more of their
leisure-time with their families. This does not necessarily point to contradictions in the
answers to our questionnaire, but could reflect the fact that whenever deviance is more
common in certain areas, a certain proportion of students in such environments stick to a
more traditional pattern of leisure-time activities.
218 Weighted data
171

Students in French-speaking cantons are more often doing illegal things just for fun,
while at the same time they pursue less often sports and other conventional leisure-time
activities.

Drinking and using cannabis is also more wide-spread in French-speaking cantons and
particularly in Geneva and in Zurich. In these cantons and regions, more respondents
know friends who use drugs or commit several offences. There is a clear association (at
the level of schools) between having friends who use drugs and consumption of cannabis
(see Figure 3.26).

In practically all these respects, respondents in the canton of St. Gallen tend to have the
most conventional life-styles.

Going out at night, going to coffee bars, pop concerts, as well as using alcohol have
become less popular between 2006 and 2013, whereas more students practice sports
when going out. On the other hand, respondents in 2013 spend less time with their
families, and more among them have peers who use drugs or who committed offences
such as burglary. Further, recent use of hard liquors and cannabis has increased (see
Chapter 9). This somewhat contradictory picture could mask important, but unmeasured
shifts in the organization of leisure-time, namely increasing use of Internet (and time
spent behind computers), on one hand, and a night-life that is extending more into early
morning-hours.

Peer-networks do not differ much across the country. Particularly in French-speaking
cantons, respondents care a lot about what their peers think about them. Ethnically
homogeneous peer networks seem to be less common nowadays (compared to 2006), and
more students have friends of different backgrounds. Students who have friends of
different origins among their peers express more feelings of satisfaction with life
(happiness) than others.

The level of happiness is approximately the same in different regions. Respondents with
problem behaviour (such as doing illegal things, having problematic use of substances) or
who know friends with problem behaviour are substantially less happy than others. On
the other hand, students who practice sports are somewhat happier. Although leisure-time
activities do not seem to influence a lot life satisfaction, the association is strong with
delinquent behaviour. Respondents who report having committed offenses of all sorts are
substantially less happy than those with more conventional behaviour. As for
victimization where the impact on happiness is well documented, this variable seems to
be a strong associate of delinquency.

Delinquency is strongly associated with leisure-time. Respondents who stay out beyond
mid-night, who hang out in streets and shopping malls or with problem behaviour admit
far more often having committed delinquent acts listed on our self-report instrument. On
the other hand, students with conventional leisure-time activities, such as school-related
work, creative activities (hobbies) and spending time with their families, have far higher
rates of offending. The same is true for juveniles who abstain from using substances. In
172
line with these findings and as shown in Chapter 3, students who missed school (truancy)
have far higher offending rates.

Playing computer games is not always associated with delinquency. There are
noteworthy differences by type of games, the violent games going along with stronger
associations.

All these findings point to one basic conclusion: preventive efforts should focus on
juveniles’ leisure-time activities. “Time” is the crucial factor in prevention.

Interestingly, delinquent respondents are less attached to their peers and socially more
isolated. This is encouraging in the sense that delinquent behaviour is not “normal”, but
clearly problem behaviour that is concentrated among youths with problematic leisuretime activities.
References:
HaymozPantillon, S. (2010) Les gangs en Suisse: délinquance, victimisation et facteurs de
risque. Doctoral dissertation.University of Lausanne (School of Criminal Justice).
HaymozPantillon S., Maxson C., Killias M. (2014) “A Comparison of Correlates with Street
Gang Participation in Europe”, European J. of Criminology 11/6, 659-681
Killias M., Lanfranconi B. (2012) “The Crime Drop Discourse – or the Illusion of Uniform
Continental Trends: Switzerland as a Contrasting Case”, in J. van Dijk, A. Tseloni& G.
Farrell (Eds.), The International Crime Drop. New Directions in Research, Basingstoke
(Hampshire, UK): Palgrave-Macmillan, 268-278
Staubli S., Killias M., Frey B.S. (2014) “Happiness and victimization: An empirical study for
Switzerland”. European J. of Criminology 11/1, 57-72
Walser S. Freizeitverhalten und Gewalt bei Jugendlichen: eine situative Perspektive.
Abhandlung zur Erlangung der Doktorwürde der philosophischen Fakultät Universität
Zürich. Dissertation. Prof. Dr. Rainer Hornung und Prof. Dr. Martin Killias. Zürich,
2013. 237p.
173
Chapter 6.
Perception of right and wrong
6.1 Overview
The questionnaire contained many questions regarding moral judgements, perceptions of one’s
own reactions, egocentrism vs. altruism, hedonistic attitudes vs. risk control and neighbourhood
characteristics (particularly regarding symptoms of decay and social cohesion). In general, moral
condemnation and shame regarding offences is broad. The same is true for almost all items in
this part of the questionnaire. In this chapter, we shall focus on variables where there was no
universal consensus across regions and little variation across time (in comparison to the results
obtained in 2006).
6.2 Moral judgements across regions
6.2.1 Perception of right and wrong
Moral condemnation is almost universal. Few students feel that serious offending (violence,
robbery, racist attacks or burglary) is morally acceptable. With minor offences, such as
shoplifting, vandalism and “illegal” downloading (which, according to Swiss law, is “legal”
indeed) moral condemnation is clearly weaker, but still a majority of respondents consider this as
very or somewhat wrong. Even lying to a teacher is not approved by the majority. Although
these judgements are universal, they have some impact on delinquency, as the following Figures
show.
174
Figure 6.1
Delinquency (last year prevalence) by lying, disobeying or talking back to adults,
such as parents and teachers in %, N=4036-4055.219
28.8
26.4
22.8
14.4
9.2
4.7
4.6
19.5
17.0
13.7
13.4
6.2
4.7
18.5
18.1
10.1
10.1
7.9
7.9 7.16.9
5.7
5.2
4.0
2.3 2.4
1.8 1.1
1.7
1.5
1.3
1.1
1.0
0.6
0.4
0.4
12.1
11.9
11.1
8.2 9.0 7.5
7.3
6.5
5.0 4.0 3.6 4.6 4.0
3.4
2.8 2.5
1.4
not wrong at all
very wrong
9.5 9.7
7.6
a little wrong
wrong
Respondents who challenge adults’ authority tend to admit more often having committed all
sorts of offences.
Figure 6.2
Delinquency (last year prevalence) by purposely damaging or destroying
property that does not belong to you in %, N=4031-4046.220
46.7
50.0
45.0
45.0
38.3
40.0
35.0
35.0
33.3
33.3
31.1
35.0
29.5
28.4
28.3
27.2
26.7
30.0 25.4
21.9 21.7
21.7
25.0 21.7
19.8
17.6
17.1
17.0
16.6
20.0
12.0
12.0
10.4
15.0
10.0
8.6
8.3
7.9
7.9 9.1
6.2
6.0
6.0 4.2
5.3
10.0
5.2 3.2
4.4
4.2
4.1
3.5 5.0
3.2
2.6
2.6
2.2
2.0
1.6
1.5
1.0 1.1
0.7
0.6
0.4
5.0
0.0
not wrong at all
a little wrong
wrong
very wrong
Respondents, who think that purposely damaging or destroying somebody’s property is not
wrong at all, are more likely to commit an offence regardless its type.
219 Weighted data
220 Weighted data
175
Figure 6.3
Delinquency (last year prevalence) by stealing something small, such as a
chocolate bar from a shop in %, N=4035-4048.221
46.0
50.0
45.0
36.4
40.0
34.5
33.7
32.3
35.0
28.2
25.3
25.3
30.0 23.2
25.0
16.1
20.0
14.8
13.4
12.5
11.8 13.9
11.3
15.0 10.0
9.7 11.7
9.7
9.2
8.8
7.8 9.8
7.2
6.1
6.1
6.0
5.7
5.1 5.4
5.0
10.0
3.8 4.3
3.3
3.1 1.2
3.1
3.0
3.0
2.6
2.5
2.2
2.0 3.2
1.9
1.8
1.1
1.0
0.9
0.9
0.8
0.6
0.6
0.5 1.3
5.0
0.0
not wrong at all
a little wrong
wrong
very wrong
Respondents, who think that shoplifting is not wrong at all, are more likely to commit an offence
regardless its type. Together, the findings shown in Figures 6.1-6.3 illustrate the importance of
moral standards in shaping human behaviour. Of course, given the cross-sectional design of our
study, we cannot rule that that, actually, moral judgements are being shaped by (preceding)
deviant behaviour, rather than the other way around.
221 Weighted data
176
6.2.2 Feelings of shame
Beyond one’s own moral judgement, the fear of moral condemnation by others, i.e. shame, is
another powerful factor in shaping human behaviour. In our questionnaire, several questions
were included on this issue. For a number of offences, respondents were asked how much they
would feel ashamed if their best friend, their teacher or their parents came to know about a
(hypothetical) offence committed by them. In general, feelings of shame are anticipated for all
these hypothetical situations. However, shame of parents and teachers is more evenly distributed
across regions than the fear of one’s best friend reaction. As we shall see later, fear of parents is
also less clearly associated with offending than the fear of friends’ reaction. In other words,
parents may be feared and shame may go along with their knowledge about one’s offences, but
they count clearly less than best friends.
As the following Figures show, the anticipation of feeling ashamed of friends is not evenly
distributed across the country.
“Imagine you were arrested by the police for committing a crime, would you feel
ashamed if your best friend found out about it” by main and subsamples in%.222
Figure 6.4
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
60.3
23.2
16.5
62.6
23.0
14.4
Switzerland
DE
(N=4'158) (N=2'560)
55.0
23.6
21.4
FR
(N=956)
no, not at all
69.0
61.9
23.8
14.3
ITA
(N=642)
60.3
15.8
15.3
SG
(N=625)
yes, a little
25.5
14.3
AG
(N=555)
58.4
20.9
20.8
GE
(N=268)
61.5
25.2
13.2
ZH
(N=266)
yes, very much
Apparently, friendship networks operate differently across the country. Fear of shame in the
hypothetical situation of being arrested by the police for a crime is stronger in German speaking
regions and particularly in the canton of St-Gall. At the other end of the distribution is Geneva.
222 Weighted data
177
“Imagine you were arrested by the police for committing a crime, would you feel
ashamed if your parents found out about it” by main and subsamples in%.223
Figure 6.5
100.0
87.7
90.1
86.5
88.3
87.7
88.6
87.7
88.1
80.0
60.0
40.0
20.0
4.68.9
4.38.0
3.66.3
4.67.7
5.76.0
4.18.3
4.37.1
5.06.9
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
0.0
Switzerland
DE
(N=4'158) (N=2'560)
no, not at all
yes, a little
yes, very much
As Figure 6.5 illustrates, parents’ reaction is well anticipated and feared, but little variation
appears across regions.
In the following figures 6.6-6.9, we shall see how the fear of shame about friends’ vs. parents’
reaction goes along with behavior, namely a more trivial offence like shoplifting and a more
serious event (being arrested by the police for a crime).
Delinquency (last year prevalence) by “Imagine you were caught shoplifting,
would you feel ashamed if your best friend found out about it” in %, N=40404060.224
Figure 6.6
28.5
30.0
25.0
20.8
20.0 14.8
15.0
10.0
5.0
5.7
2.5
16.2
15.7
11.4
7.6
3.6
3.8 4.4
0.70.3
5.5
4.8 3.8
4.2
2.0 0.60.5 2.0
0.3 0.60.2
6.5
3.3
18.9
16.6
13.1
9.4
4.8
5.9
3.3
7.9
2.50.9
4.5 5.73.5
2.4
1.9
0.0
not at all
a little
very much
223 Weighted data
224 Weighted data
178
Respondents, who would not feel ashamed at all if caught shoplifting and even if their friends
find out about it, are more likely to commit an offence regardless its type. As the following
Figure 6.7 illustrates, the effect of shame is far weaker if the parents find out about.
Figure 6.7
Delinquency (last year prevalence) by “Imagine you were caught shoplifting,
would you feel ashamed if your parents found out about it” in %, N=40374057.225
30.0
25.0
19.8
20.0 17.5
17.0 18.3
15.0
10.0
25.1
22.2
10.6
4.9
5.0
7.5
18.5
17.2
15.8
15.1 13.9
14.2
13.1
11.2 9.9
9.9
9.0
8.67.8 7.9
6.8 7.5
6.6
6.4
5.1 3.8
4.2 4.43.3
2.9
2.4
1.2
0.9
0.7
15.9
13.6
7.9
5.6
0.6
0.0
not at all
a little
very much
When we turn to a more serious event, such as being arrested by the police for a crime, the same
difference appears (Figures 6.8 and 6.9).
225 Weighted data
179
Figure 6.8
Delinquency (last year prevalence) by “Imagine you were arrested by the police
for committing a crime, would you feel ashamed if your best friend found out
about it” in %, N=4040-4060.226
35.0
29.3
30.0
23.9
23.4
25.0 19.7
21.0
19.3
19.0
18.8
20.0
15.5
11.5
15.0
10.8
10.2
8.3
8.2
7.5 6.0
7.0 6.0
7.0
6.7
6.2 6.5
10.0
5.7
5.2
4.7
4.4
4.32.6
3.5 3.4
3.5
3.0
2.5 0.8
1.7
1.3
5.0
1.1
1.00.4
0.5
0.4
0.2
0.0
not at all
a little
very much
Respondents, who would feel much ashamed if they were arrested by the police for committing a
crime and their friends find out, are less likely to commit an offence regardless its type.
Figure 6.9
Delinquency (last year prevalence) by “Imagine you were arrested by the police
for committing a crime, would you feel ashamed if your parents found out
about it” in %, N=4037-4057.227
30.0
24.7
24.7
24.1
22.1
25.0
19.1
18.5
17.9
17.8
17.4
16.9
20.0
16.2
15.6
15.0
13.8
13.5
12.9
15.0
11.3
11.010.9
8.7
8.0
8.08.3 8.6
8.0
6.9
6.9
10.0
6.4 7.0
5.2
5.1 4.6
4.6
4.2 5.53.3
2.8
2.4
5.0
1.4
0.8
0.7
0.7
0.0
not at all
a little
very much
226 Weighted data
227 Weighted data
180
Compared to Figure 6.8, those who would feel much ashamed in case their parents find out about
their being arrested by the police (Figure 6.9) are, apparently, less retained from committing
offences of any kind. This means that, although students anticipate being ashamed, they are less
influenced by their parents compared to their best friends’ reaction.
181
Delinquency (last year prevalence) by “what would the best friend feel if
he/she finds out that respondent sold an old cell phone to classmate as a
new one” in %, N=3978-3984.228
Figure 6.9_1
30.0
22.8
25.0
20.0
15.0
10.0
5.0
16.2
16.0
12.4
7.2
4.4
2.1
25.6
24.3
9.1
4.8
4.3
22.4
20.7
19.3
18.6
16.9
15.8
14.3
10.4
8.6
7.0
7.9 8.6
6.0
1.4
1.30.4
0.1
3.0
2.9
11.3
8.6
7.4
4.3
2.0 1.4
1.4
0.8
0.5 1.1
0.5
0.4 0.8
0.0
0.0
10.5
7.6
4.9
4.1
5.5
5.4
12.2
9.7
8.4 8.3
5.6 5.2
5.0
3.9 3.5
3.6 4.5
3.2
2.7
1.2 2.2
0.8
0.4
7.7
0.0
would admire me
rather admire
neither/nor
rather critique
critisize a lot
As in the previous Figure (6.9), students, who in case of unfair behavior anticipate criticism by
their favorite mate, are less likely to commit offences of all types than those who would expect
being admired by them.
228 Weighted data
182
6.3 Self-control, risky behaviour and altruistic vs. egocentric attitudes
6.3.1 Risk taking and accidents
Derived from the well-established concept of self-control, the questionnaire contained a series of
items regarding one’s anticipated reaction while making decisions. Most variables turned out to
vary only moderately across time and space. We shall focus here on a few that turned out to be
particularly relevant in connection with delinquency.
“I act on the spur of the moment without stopping to think”by main and
subsamples in %.229
Figure6.10
60.0
50.0
48.4
45.7
42.4
40.0
10.0
28.5
27.3
30.0
19.1
17.0
12.9
7.2
46.0
46.6
45.5
34.5
30.2
20.0
47.1
42.3
10.1
13.0
27.8
27.6
16.1
20.9
19.3
13.5
6.0
5.1
29.3
26.1
14.9
18.8
5.3
5.3
0.0
Switzerland
DE
(N=4'158) (N=2'560)
agree fully
FR
(N=956)
ITA
(N=642)
agree somewhat
SG
(N=625)
AG
(N=555)
disagree somewhat
GE
(N=268)
ZH
(N=266)
disagree fully
In German-speaking cantons, roughly two students in five disagree fully or somewhat to “act on
the spur of the moment without stopping to think”. In French-speaking cantons, in Geneva and in
Ticino, the distribution is more normal-shaped, as if the population there were more divided.
There is surprisingly little variation across regions within linguistic regions.
229 Weighted data
183
“I am more concerned with what happens to me in the short run than in the long
run”by main and subsamples in %.230
Figure 6.11
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
41.6
40.9
40.2
32.6
28.0
22.3
29.7
25.8 25.3
25.7
16.3
8.7
11.0
agree fully
FR
(N=956)
27.7
26.0 26.8
ITA
(N=642)
agree somewhat
SG
(N=625)
30.9
28.9
24.8
16.4
14.2
9.4
37.6
35.8
19.2
7.3
Switzerland
DE
(N=4'158) (N=2'560)
39.9
37.2
36.9
18.9
7.3
AG
(N=555)
disagree somewhat
6.7
GE
(N=268)
ZH
(N=266)
disagree fully
Regarding considering the short vs. the longterm perspective, some differences across regions
become visible. Generally, German-Swiss respondents, even in urban areas like Zurich, are more
long-term oriented than French- and Italian-speaking respondents.
230 Weighted data
184
“I like to test myself every now and then by doing something a little risky” by
main and subsamples in %.231
Figure 6.12
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
41.6
36.7
34.0
32.6
32.6
23.5
30.9
29.2
25.0
34.3
26.5
20.0
23.3
16.0
Switzerland
DE
(N=4'158) (N=2'560)
agree fully
FR
(N=956)
ITA
(N=642)
agree somewhat
13.4
10.1
10.8
10.7
9.3
SG
(N=625)
AG
(N=555)
disagree somewhat
34.9
27.8
22.6
23.8
21.5
33.6
33.3
32.0
15.9
14.9
11.2
34.1
33.7
GE
(N=268)
ZH
(N=266)
disagree fully
In line with the finding presented in Figure 6.11, German-Swiss juveniles (even in Zurich) are
less inlcined to take risks than respondents in other areas.
Figure 6.13
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Having an accident that was so serious that it was necessary to see a doctor by
52.3
43.5
36.8
19.7
39.0
38.3
53.4
51.0
33.7
34.1
23.3
22.7
Switzerland
DE
(N=4'158) (N=2'560)
39.5
37.2
14.0
FR
(N=956)
never
40.8
33.8
25.4
once
39.4
38.0
22.6
15.3
14.9
ITA
(N=642)
31.3
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
more than once
Surprisingly, having experienced accidents of some seriousness (necessitating medical
assistance) are rather more common in German-speaking cantons than in Ticino and in the
Romandie. A possible explanation might be the lower prevalence of sports as a major leisuretime activity in Latin cantons (see Chapter 5, Figure 5.7).
231 Weighted data
232 Weighted data
185
Delinquency (last year prevalence) by “I act on the spur of the moment without
stopping to think” in %, N=4027-4050.233
Figure 6.14
25.0
20.3
20.0
15.0 13.7
13.6
9.9
10.0
5.0
15.8
15.2
5.8
5.0
3.4
6.5
5.4
13.0
12.4
10.9
10.2
8.0
7.57.27.6
7.17.6
6.9
6.9
6.05.8
5.8
5.6
5.3
4.7
4.1
4.1
3.6 3.7 3.8
3.5 3.33.1
3.13.8 2.7
3.02.4 3.4
2.3
2.1
1.7
1.3
1.1
0.9
0.9
0.8
0.5
0.3
0.2
12.7
12.7
0.0
fully agree
agree somewhat
disagree somewhat
fully disagree
Respondents, who act on the spur of the moment without stopping to think, are more likely to
commit an offence regardless its type.
233 Weighted data
186
Delinquency (last year prevalence) by “I am more concerned with what happens
to me in the short run than in the long run” in %, N=4011-4036.234
Figure 6.15
25.0
19.5
17.8
20.0
14.4
12.2
15.0 13.3
10.0
5.0
8.2
6.4
11.5
12.4
8.9
2.6
3.7
8.9
5.4
3.4
2.3
0.7
0.7
13.8
12.4
11.3
9.8
9.6
9.3 10.2
8.2
7.2
7.1
5.4 4.5
4.5
4.0
3.0
2.9
2.0 1.2
1.6
0.9 1.0
0.8
0.8
0.6
3.6
10.7
7.9
5.6
5.1
3.9
2.6
0.9
5.9
4.3 3.5
3.3
2.4 3.3
0.0
fully agree
agree somewhat
disagree somewhat
fully disagree
Students, who are more concentrated on the short than on the long run, are more likely to commit
any type of offence.
234 Weighted data
187
Delinquency (last year prevalence) by “I like to test myself every now and then
by doing something a little risky” in %, N=4022-4044.235
Figure 6.16
35.0
31.6
30.4
30.0
25.1
23.3
25.0 22.2
20.0
12.8
15.0
10.0
5.0
9.4
17.2
12.0
10.8
7.2
4.7
1.4
3.1
20.3
19.9
19.1
12.9
8.5
5.1
3.6
1.7
0.8
0.5
6.9
5.3
4.3 5.6
3.3
2.4 1.2
0.8 1.8
0.6
0.6 1.3
0.5
0.5
4.3
3.5
11.0
7.1
3.4
12.4
4.2 3.9
2.6 2.1
0.5
7.3
4.8 5.8
4.6
3.9
1.7
0.8
0.0
fully agree
agree somewhat
disagree somewhat
fully disagree
Students, who like doing something a little risky, are more likely to commit any type of offence.
Delinquency (last year prevalence) by “having an accident that was so serious
you had to see a doctor, such as during sports or a traffic accident” in %,
N=4045-4066.236
Figure 6.17
20.0
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
17.3
16.8
15.3
10.6
5.56.0
13.0
11.7
11.4
10.6
8.18.5
7.06.9
10.4
8.4
7.3
5.05.9
2.8
1.11.0
4.0
2.8 2.0
2.4
0.81.3
0.71.3 1.5
never
once
7.0
5.3
7.9
6.5 6.3
5.5
4.2
3.9
2.8
2.3
2.2
more than once
235 Weighted data
236 Weighted data
188
Students, who had a serious accident with the necessity to see a doctor, are more likely to
commit any type of offence. The association between having experienced accidents and
offending has been observed in several studies over the last years (Killias/Kuhn/Aebi 2011, 248).
6.3.2 Egocentrism
Figure 6.18
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
“If things I do upset people, it is their problem, not mine”by main and
subsamples in %.237
34.4
25.0 25.1
33.6
28.5
21.3
15.5
16.6
Switzerland
DE
(N=4'158) (N=2'560)
agree fully
36.8
36.6
31.6
18.2
13.6
FR
(N=956)
30.9
19.7
25.0 23.4
18.6
12.7
ITA
(N=642)
agree somewhat
SG
(N=625)
38.9
34.2
36.8
33.0
32.9
27.3
27.0
20.7
15.5
AG
(N=555)
disagree somewhat
16.1
10.8
GE
(N=268)
23.9
15.8
ZH
(N=266)
disagree fully
Most respondents do not accept this statement. Egocentric acting is the most clearly rejected in
Italian and French speaking regions. Interestingly, the two urbanized cantons of Geneva and
Zurich are particularly different in this respect. There may be a cultural underpinning at work
that is hard to understand without further data.
237 Weighted data
189
Delinquency (last year prevalence) by “If things I do upset people, it is their
problem, not mine” in %, N=3998-4021.238
Figure 6.19
25.0
20.9
20.0
16.9
15.0 13.5
10.0
5.0
16.1
11.6
6.6
5.9
3.7
7.5
4.3
20.5
16.0
15.9
14.9
13.1
9.7
9.5
9.0 8.5
8.7
8.4
8.4
8.3
5.9 7.0
5.5
5.2 5.0
4.7
4.5
4.2
4.2
4.2 3.1
3.9
3.3
3.3
3.2
3.0
2.93.5
2.4
2.1
2.0
1.6
1.4
1.4
1.2
1.1
1.1
1.0
0.9
0.7
0.5
0.4
0.4
0.0
fully agree
agree somewhat
disagree somewhat
fully disagree
Students, who do not care if they make upset other people by their own behaviour, are more
likely to commit any type of offence.
These and a few more questions have been asked also during the preceding ISRD-2 conducted in
2006. As figures 6.20 and 6.21 show, attitudes have remained fairly stable over time, but
students may have become slightly more egocentric.
Figure 6.20
50.0
40.0
“I try to look out for myself first, even if it means making things difficult for
other people” in % for 2006 and 2013, N=3987-4011.239
41.5
37.7
41.3
32.5
30.0
19.5
20.0
14.6
6.3
10.0
6.7
0.0
disagree fully
disagree somewhat
ISRD-2
agree somewhat
agree fully
ISRD-3
238 Weighted data
190
Figure 6.21
“If things I do upset people, it is their problem, not mine” in % for 2006 and
2013.240
40.0
30.0
32.3
27.7
34.4
25.1
23.1
25.0
16.9
20.0
15.5
10.0
0.0
disagree fully
disagree somewhat
ISRD-2
agree somewhat
agree fully
ISRD-3
These changes seem insufficient, however, to explain the substantial increases in offending
between 2006 and 2013 (see Chapter 7, Figure 7.2). The other attitudes seem to have changed
even less.
6.4 Good and bad neighbourhoods
Several questions in our instrument referred to the neighbourhood. In this connection, it should
be kept in mind that the same questionnaire was to be applied in some 30 countries. The several
items related to neighbourhood characteristics had, therefore, to work in very different social and
economic backgrounds.
191
Figure 6.22 “There is a lot of crime in my neighbourhood” by main and subsamples by main
100.0
80.0
74.6
74.5
74.8
71.7
71.8
80.4
70.2
68.2
60.0
40.0
20.0
18.0
4.53.0
17.8
4.63.0
CH
(N=4'158)
DE
(N=2'560)
18.4
4.02.8
17.8
5.35.2
20.0
6.12.0
13.4
3.03.1
20.4
5.44.1
23.4
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
4.44.0
0.0
1 disagree fully
2 disagree somewhat
3 agree somewhat
4 agree fully
Only few respondents live in neighbourhoods where crime is fairly common. More respondents
in Geneva and Zurich report higher crime rates in their neighbourhood. This corresponds to the
observations during several crime surveys that crime is relatively evenly distributed across
Switzerland (Killias et al. 2011).
Figure 6.23
100.0
80.0
“There is a lot of graffiti in my neighbourhood” by main and subsamples in %.242
82.1
78.7
73.3
81.5
83.0
79.5
65.3
55.2
60.0
40.0
20.0
12.5
5.63.3
11.1
4.22.6
CH
(N=4'158)
DE
(N=2'560)
14.5
8.04.2
18.5
9.96.3
12.5
4.02.0
FR
(N=956)
ITA
(N=642)
SG
(N=625)
8.64.83.7
11.7
4.74.1
20.6
14.1
10.2
0.0
disagree fully
disagree somewhat
AG
(N=555)
agree somewhat
GE
(N=268)
ZH
(N=266)
agree fully
Most of neighbourhoods do not have a lot of graffiti. The highest percentage of those, who have
it is in the canton of Geneva.
241 Weighted data
242 Weighted data
192
“People around here are willing to help their neighbours” by main and
subsamples in %.243
Figure 6.24
60.0
44.8
37.6
44.2
50.0
33.8
40.0
30.0
20.0
10.0
43.2
20.7
15.3
6.7
12.7
5.0
43.7
39.5
42.9
49.9
43.6
42.0
25.9
19.2
11.1
18.9
10.2
11.5
5.3
7.8
35.2
34.5
33.7
30.5
12.2
4.3
11.0
3.4
0.0
CH
(N=4'158)
DE
(N=2'560)
FR
(N=956)
disagree fully
ITA
(N=642)
disagree somewhat
SG
(N=625)
AG
(N=555)
agree somewhat
GE
(N=268)
ZH
(N=266)
agree fully
Respondents in French-speaking cantons perceive less solidarity between people living in their
neighbourhood than in German-speaking regions.
“There is a close-knit neighbourhood” by main and subsamples in %.244
Figure 6.25
50.0
40.0
40.2
33.1
36.5
33.6
30.0
20.0
16.7
13.1
10.0
34.2
29.8
38.0
28.6
21.2
20.6
17.6
15.4
12.2
9.2
39.6
35.1
17.1
36.6
30.6
15.8
39.1
33.8
17.0 18.3
32.1
26.4
23.8
17.7
8.9
8.2
0.0
CH
(N=4'158)
DE
(N=2'560)
disagree fully
FR
(N=956)
ITA
(N=642)
disagree somewhat
SG
(N=625)
AG
(N=555)
agree somewhat
GE
(N=268)
ZH
(N=266)
agree fully
On the other hand, replies to the question about helping eachother out is only moderatly
associated with another aspect of solidarity, namely whether or not one’s neighbourhood is seen
as “close-knit”. In this respect, German Swiss respondents see their neighbourhood more
positively than those in French-speaking cantons.
243 Weighted data
244 Weighted data
193
Figure 6.26
Delinquency (last year prevalence) by “There is a lot of crime in my
neighbourhood” in %, N=4014-4037.245
37.2
40.0
34.4
32.0
35.0
28.9
27.9
27.3 27.3
30.0
25.4
24.2
22.1
21.3
25.0
20.5 19.8
19.3 21.0
18.6
17.0 19.0
20.0
15.7
13.0
11.9 13.3 11.2
11.7
11.0 11.9 10.0
15.0 10.1
9.5 7.8
9.0
8.4 9.4
7.3
6.3
10.0 4.4
4.5
4.5
4.4
4.3
3.4
3.4
3.2
3.0
2.8
2.3 1.22.8 0.4
1.9
1.7
1.7
1.5
1.2
5.0
0.5
0.4
0.0
fully disagree
disagree somewhat
agree somewhat
fully agree
Students, who perceive a lot of crime in their neighbourhood, are more likely to commit an
offence.
Figure 6.27
Delinquency (last year prevalence) by “There is a lot of graffiti in my
neighbourhood” in %, N=4010-4034.246
40.0
34.4
35.0
31.1 30.3 32.6
30.3
28.2 26.7
30.0
23.7
23.0
21.8
25.0
20.4
19.7
19.1
18.9
18.7
18.6
16.8
20.0
15.9 15.9
15.5
15.3
12.9
15.0 10.1 11.0 10.1
10.9
10.8
9.8 8.6
9.8
7.7
7.4
7.1 7.6
10.0
6.2
6.2
6.1
4.9
4.6
4.4
4.4
4.0
3.9
3.6
3.5 2.6
3.2
2.9
2.2
2.1
1.6
5.0
1.0 1.0
0.5
0.5
0.4
0.0
fully disagree
disagree somewhat
agree somewhat
fully agree
245 Weighted data
246 Weighted data
194
Respondents, who see a lot of graffiti in their neighbourhood, are more likely to commit an
offence.
Figure 6.28
Delinquency (last year prevalence) by “People around here are willing to help
their neighbours” in %, N=4015-4037.247
26.9
30.0
25.0
20.0
14.9
14.0 13.3
13.0
12.8
12.1
15.0 11.9
11.4
11.0 11.99.4
11.0
10.9
10.0
9.2
9.2 8.8
8.3
7.3
7.3
7.2
6.9
10.0
6.2
6.2
6.2
6.2
5.9
5.8
5.7
5.7
5.1
5.04.5
4.9
4.2
4.0
3.53.9
3.5
3.4
3.0
2.7
2.6
2.4
1.8
1.6
5.0
1.4
1.4
1.3
1.2
1.1
1.1
0.9
0.9
0.9
0.0
fully disagree
disagree somewhat
agree somewhat
fully agree
Respondents, who live in neighbourhood where people are not willing to help each other, are
more likely to commit an offence.
247 Weighted data
195
Figure 6.29
Delinquency (last year prevalence) by “This is a close-knit neighbourhood” in
%, N=4006-4028.248
20.0
18.1
18.0
16.0
13.4
13.3
13.2
14.0
10.9
10.6
10.5
12.0
9.7 10.2 9.710.4
9.4
9.2 9.8
9.2
8.7
8.5
10.0 7.6
7.2
7.1
7.1
7.1
6.7
6.4
6.4
6.3
8.0
6.2
5.8
5.1
4.7
4.7
4.6
6.0
4.1
4.13.3
3.8
3.6
3.6
3.4 4.1
3.1
3.0
2.8
2.7 2.8
2.6
2.3
4.0
1.8
1.7
1.0
0.9 1.3
0.9
0.8
0.6
0.5
2.0
0.0
fully disagree
disagree somewhat
agree somewhat
fully agree
Students, who live in a close-knit neighbourhood, commit fewer offences. In the first situation it
can be explained by committing offence in a group, in the second one – is because of absence of
bonding with own neighbourhood. Among exceptions are vandalism and shoplifting.
Some of the variables here have also been measured in the 2006 survey. The following Figures
show how neighbourhood perception has developed over the last years.
Figure 6.30
80.0
“There is a lot of crime in my neighbourhood” in % for 2006 and 2013.249
74.5
62.9
60.0
40.0
24.8
20.0
18.0
8.2
4.5
4.1
3.0
0.0
disagree fully
disagree somewhat
ISRD-2
agree somewhat
agree fully
ISRD-3
Percentage of respondents, who declined a lot of crimes in their neighbourhoods, decreased.
248 Weighted data
196
Figure 6.31
“There is a lot of graffiti in my neighbourhood” in % for 2006 and 2013.250
100.0
80.0
72.3
78.7
60.0
40.0
17.0
20.0
12.5
6.6
5.6
4.1
3.3
0.0
disagree fully
disagree somewhat
ISRD-2
agree somewhat
agree fully
ISRD-3
Percentage of respondents, who live in neighbourhood without graffiti, slightly increased
Figure 6.32
“People around here are willing to help their neighbours” in % for 2006 and
2013.251
50.0
42.3
44.2
40.0
31.0
30.0
19.7
20.0
10.0
7.1
33.8
15.3
6.7
0.0
disagree fully
disagree somewhat
ISRD-2
agree somewhat
agree fully
ISRD-3
Percentages of respondents, who want or do not want helping their neighbours, remained stable.
251 Weighted data (ISRD-3, N=4158), not weighted data (ISRD-2, N=3643).data
197
Figure 6.33
“This is a close-knit neighbourhood” in % for 2006 and 2013.252
50.0
36.5
40.0
41.4
33.6
25.9
30.0
23.1
16.7
20.0
13.1
9.5
10.0
0.0
disagree fully
disagree somewhat
ISRD-2
agree somewhat
agree fully
ISRD-3
The results are somewhat difficult to interpret. On one hand, fewer respondents say there is “a lot
of crime” (or a lot of graffiti) in their neighbourhood. At the same time, judgements about
solidarity among neighbours (Figures 32 and 33) are less optimistic than in 2006. Overall, the
safest way of interpreting changes over time would be to say that they are not contributing much
to understand changes in crime rates, as observed in Chapter 7 (Figure 7.2). However,
differences in the prevalence of social problems in the neighbourhood were among the strongest
variables explaining different levels of crime rates in an international perspective, i.e. across
countries (Junger-Tas, Steketee, Jonkman 2012, 266).
References:
Killias M., Kuhn A., Aebi M. Grundriss der Kriminlogie. Eine Europpeische Perspektive. Zweite
Auflage. Bern: Stämpfli Verlag AG, 2011. 568 p.
Junger-Tas J.J.T., Steketee M., Jonkman H.The nneighbourhood context.Chapter 10.The many
faces of Youth crime.Contrasting theoretical perspectives on juvenile delinquency across
countries and cultures. New York: Springer,2012, 367 p. P. 257-284.
Killias M., Staubli S., Biberstein L., Bänziger M., Iadanza S.International Crime Victimization
Survey (ICVS) 2010/2011.
http://krc.ch/de/index.php?a=Research&b=Forschung&c=AbgeschlosseneForschungsprojekte
198
Chapter 7
Delinquency over space and time in various degrees of seriousness
7.1 Overview
In this Chapter, we shall first present the prevalence rates over the last year and over the entire
lifespan for the entire country as well as for the several regional subsamples. In the second part,
we shall look at trends in offending since ISRD-1 (in 1992) and ISRD-2 (in 2006). In the final
section, we shall look at the so-called “versatility”, i.e. the extent to which respondents admitting
having committed one particular offence have been involved also in other forms of delinquency.
7.2.Delinquency across Switzerland’s several regions
Table 7.1 gives an overview of how many respondents (in per cent) admitted having committed
any of the listed offence types at least once over the last 12 months.
Tabelle 7.1
Graffiti
Vandalism
Shoplifting
Burglary
Bicycle theft
Car theft
Car break
Robbery
Personal theft
Weapon
Group fight
Assault
Drug dealing
Animal
cruelty
Delinquency (last year prevalence) by main and different subsamples253
Switzerland
254
(N=4'158)
DE
(N=2'560
)
FR
(N=956
)
ITA
(N=642
)
SG
(N=625
)
AG
(N=555
)
GE
(N=268
)
ZH
(N=266
)
6.7
9.3
12.6
1.4
6.4
1.3
2.2
1.3
7.7
10.0
7.5
3.2
5.6
5.1
7.8
10.1
1.4
7.1
1.4
1.7
1.4
5.1
9.8
5.8
3.4
5.9
9.3
12.8
18.9
1.4
5.1
1.3
3.1
0.9
13.3
10.6
11.2
3.1
5.0
12.0
7.8
9.2
2.1
4.5
1.5
3.0
2.1
7.9
7.6
8.1
2.1
5.0
4.6
6.9
9.7
1.2
7.0
0.6
0.8
0.5
5.5
8.4
5.5
3.3
3.7
5.3
8.1
9.0
1.6
6.9
2.1
2.0
1.4
5.1
11.4
7.4
2.1
4.0
11.9
15.0
14.4
1.4
3.0
2.6
2.8
1.4
13.1
9.9
11.0
5.9
4.4
3.8
7.1
8.9
1.2
5.3
1.8
2.2
1.8
3.3
10.0
4.5
4.1
6.2
3.6
3.9
2.7
5.3
3.5
3.4
3.6
1.4
Among the most frequent offences are vandalism, shoplifting, personal theft, caring weapons and
group fights. The highest prevalence rates can be observed in French speaking cantons including
Geneva as well as in Zurich. Shoplifting and theft of personal items are particularly frequent in
253 Weighted data
254
N=4054-4071
199
the French-speaking cantons, whereas for other offences, the differences are less pronounced and
less consistent. The canton of St-Gall stands out as the region with the lowest delinquency rates.
The same picture emerges if offending over the entire lifespan (rather than offending over the
last 12 months) is considered (Figure 7.1). With the exception of bicycle theft, stealing is more
common in the French-speaking regions, whereas German-speaking cantons tend to have higher
rates of violence including group fights.
Delinquency (life time prevalence) by language regions in %.255
Figure 7.1
30.0
20.0
23.5
16.5
13.8 11.8
10.0
7.48.45.7
5.4
16.4
10.7
10.6
8.2
12.2
8.26.3 8.3
1.82.01.52.1
1.71.91.32.1
Burglary
Robbery
3.84.23.32.3
0.0
Shoplifting
Bicycle theft Personal theft
Group fight
Assault
Switzerland (N=4'158)
German speaking part (N=2'560)
Romandie (N=956)
Tessin (Main sample + additional sample, N=642)
Thus, the geographic distribution does not change if, instead of 12-months rates, lifespan
prevalence rates are considered.
7.3.Trends in delinquency over time
The question whether offending in general and among juveniles in particular has increased over
the last 20 years has often been a matter of debate. Before the recent drop after 2011 (whose
reasons are not entirely clear), offending in general and especially violent offences have
considerably increased in police statistics since 1990. Victimization surveys (Killias et al. 2011)
and health statistics (Killias&Lanfranconi 2012) have shown similar trends. One self-report
survey conducted in the canton of Zurich in 1998 and in 2007 has shown, however, that
offending and victimization have essentially remained stable over these years (Ribeaud& Eisner
2009). Since the International Self-reported delinquency survey has been conducted in
Switzerland in 1992, 2006 and 2013, some longitudinal comparisons are possible. It should be
taken into account, however, that not all offences were included among the list of self-reported
offences in all three sweeps of this survey. The details can be seen from Table 7.2.
255 Weighted data
200
Table 7.2
Delinquency (life time and last year prevalence) in % for 1992, 2006 and2013.256
Graffiti
Vandalism
Shoplifting
Burglary
Bicycle/moped/scooter
theft (ISRD2)
BicycleTheft (ISRD3)
Motobike/cartheft
Car break
Robbery
Personal theft (ISRD3)
Caringweapon
Group fight
Assault
Drug Dealing (ISRD2)
Drug dealing (ISRD3)
AnimalCruelty
ISRD-1 *
(N=529) ISRD-2 * (N=3'648)
ISRD-3* (N=4‘158)
Last year Life time Last year Life time Last year
8.8
6.6
11.3
9.1
13.4
7.8
16.2
12.4
15.3
23.6
9.1
1.8
1.4
0.6
2.0
0.9
6.6
3.7
1.0
0.0
0.8
2.7
1.4
0.4
1.0
0.9
9.5
10.0
0.5
1.5
11.1
15.5
2.9
3.7
7.8
8.4
1.2
2.8
12.2
7.3
1.6
2.7
1.7
10.5
10.8
8.0
3.7
6.3
1.3
2.2
1.3
7.5
9.7
7.3
3.1
5.6
4.2
5.4
3.5
* Weighteddata
To the extent that the several offences were measured in a comparable way over time in all
waves of ISRD, an increasing trend emerges for most offences. The exceptions are shoplifting,
where preventive measures (i.e. the increased use of modern technology) in shops may have
reversed the trend, and group fights. For all the other offences shown in Table 2, the increase is
substantial, especially for bicycle theft, assault and drug (i.e. mostly cannabis) dealing. Further
(and once more with the exception of shoplifting), the trend is consistent from 1992 to 2006 and
from 2006 to 2013.
256 Weighted data
201
Figure 7.2
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
Delinquency (last year prevalence), the whole Switzerland in % for 1992, 2006,
2013.257
15.3
12.4
9.7
9.1
7.8
10.0
8.4
7.3
5.4
3.1
0.6
Shoplifting
0.9 1.4
Burglary
0.0
Robbery
1992 (ISRD-1, N=529)*
Table 7.3
0.9 1.3
0.5 1.2
Cating weapon Group fight
2006 (ISRD-2, N=3'648)*
Assualt
1.5
2.8
Drug Dealing
2013 (ISRD-3, N=4'158)*
Significance of the comparison of ISRD-1, ISRD-2 and ISRD-3
ISRD-1 and ISRD-2
p-value
Shoplifting
.000
Burglary
.025
Car break
.742
ISRD-2 and ISRD-3
p-value
Shoplifting
.000
Burglary
.002
Car break
.000
Robbery
.009
Caringweapon
.000
Caringweapon
.000
Group fight
Assault
Drug dealing
.007
.000
.000
Group fight
Assault
Drug dealing
.163
.000
.000
The reason of the controversy may be that some surveys (such as the one conducted in Zurich by
Ribeaud& Eisner 2009), inspired by the model of the Kriminologisches Institut Niedersachsen
(KFN) at Hannover, are using very broad concepts of violence. For example, roughly 20 per cent
of their respondents reported having committed bodily injury at least once over the last 12
months, whereas the ISRD measure includes only cases where the victim needed to see a doctor.
As a result, only about 3 per cent of our respondents admitted having committed this narrowly
defined offence of “assault” in 2013. Under these circumstances, variation over time is far more
likely. The same holds for victimization where our rates are also far lower than those observed
by Ribeaud& Eisner (2009). In line with what has been observed in Figure 7.2, the rates of
257 Weighted data
202
victimization (particularly for assault and robbery) have also increased substantially between
2006 and 2013 (see Figure 4.1). The Zurich study, however, did not find any increase with its far
broader definitions of victimization.
In sum, the trends shown here are consistent with increasing rates of victimization observed in
chapter 4 (Figure 4.1). That victimization and offending show similar trends over time, is
consistent with the fact that the two phenomena tend to co-vary at the individual level (see the
following Figure 7.2_1). It is, therefore, plausible that they co-vary also over space and time.
Delinquency by victimization (assault) in %, N=40521-4068 258
Figure 7.2_1
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
34.6
26.9
20.5
17.3
6.2
8.6
11.7
9.0
1.1
20.5
11.5
5.8
0.9
No assault
9.6
1.9
11.5
24.5
24.4
21.5
14.8
7.2
0.9
9.4
6.8
2.8
5.0
8.2
3.5
Reported assault
As one can see from the Figure 7.2_1, victims of assault tend to commit far more offences than
those who never experienced intentional physical injury. The same association between
offending and victimization can also be observed for other offences. Although this connection is
well-established, it does not mean that the same factors are at work for delinquency and
victimization. In Chapter 1, we have seen several examples where variables that were strongly
correlated with delinquency are not or moderately at best with victimization (see 1.5)
7.4.Versatility: Are offenders specialists or generalists259?
A highly relevant question is whether offending is limited to a unique type of offence or the
symptom of a broader problem. By versatility we mean that a person committing offense X has,
over the same reference period (of, say, 12 months) committed further offences (and, eventually,
how many different offences). We can express this idea either by looking at how many
258 Weighted data
259
The variable measuring the delinquency in general is made up of 14 different types of offences. The versatility
score has been calculated considering only those cases who gave a valid answer to each of these 14 variables
(offences, last year prevalence). Respondents who provided a missing value to at least one of these 14 variables are
not included into the calculation of the versatility score.
203
respondents who admit having committed a certain offence have committed also other types of
offences. This is illustrated by Figure 7.3.
Figure 7.3
How versatile are juveniles who admit having committed (at least once over the
last year) each single minor property offence on our list? in %, N=4025-4026.260
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
68.2
60.4
56.0
55.7
16.1
Graffiti ***
42.5
36.7
29.9
28.2
55.8
21.5
10.3
14.0
Vandalism ***
20.8
Shoplifting *** Bicycle theft *** Motorbike/car
theft ***
1-3 offences
4-7 offences
29.4
22.6
17.0
14.8
Personal theft
***
8-14 offences
Respondents reporting more trivial property offences, such as graffiti, vandalism, personal theft
and shoplifting, are mostly one-type offenders, i.e. less versatile or more “normal” juveniles.
Figure 7.4
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
How versatile are juveniles who admit having committed (at least once over the
last year) each single violent or serious offence on our list, in %, N=40254026.261
64.3
62.3
68.3
60.8
49.3
26.8
37.1
31.5
31.5
39.5
31.8
28.7
33.7
20.8
17.0
8.9
25.8
13.5
17.0
43.9
33.0
23.1
16.6
15.2
Burglary *** Car break Robbery***
Caring
Group fight Assault *** Drug dealing Animal
***
weapon ***
***
***
cruelty ***
1-3 offences
4-7 offences
8-14 offences
Respondents reporting serious property offences, such as burglary, motorbike/car theft or
robbery, are more versatile. For example, two in three who admit having committed at least one
260 Weighted data
261 Weighted data
204
robbery have committed at least 8 further types of offences. On the other hand, carrying a
weapon, group fight and animal cruelty are often committed by less versatile (or more “normal”)
offenders.
We can look at versatility also from the opposite angle, namely how many low, medium or high
versatility offenders have committed at least one of the offences on our list.
Figure 7.5
How many among low/medium/high versatility offenders have committed at
least one of the following offences (over the last 12 months)? in %, N=40254026.262
120.0
96.4
96.4 91.1
91.1 91.2
91.1
100.0
82.1
78.6
73.2
80.0
64.3
60.2 59.7
57.1 58.9 58.9 50.3 56.9 56.1
52.5
60.0
42.9
42.5
40.6
31.6
40.0
20.6
15.9 22.4 13.6
15.5
14.0 18.8
12.2
9.1
8.9
8.3 10.1
6.6 2.6
6.1
20.0
4.7
0.8
0.8
0.5
0.0
1-3 offences
4-7 offences
8-14 offences
Most offences highly versatile offenders have committed most types of offences on our list. The
exception is animal cruelty that is committed only by half of the highly versatile offenders.
However, there are some nuances across offences. For example, robbery, burglary and theft of
cars/motorbikes is not committed systematically by highly versatile offenders, whereas
shoplifting, vandalism, drug dealing, bicycle theft, group fight and carrying weapons is
committed by over 90 percent of them.
7.4 Conclusions
Serious juvenile delinquency in Switzerland has a increased since 1992. The Romandie region
has higher rates of delinquency, along with urban areas like Zurich and Geneva. St-Gall is the
canton with the lowest rates.
Students, who report smaller number of offences, commit usually less serious offences. Overall,
offenders are generalists rather than specialists, in the sense that they commit different types of
offences. Those who commit different types of offences are consistently committing also more
serious offences. In this sense, versatility is a good proxy for seriousness of offending.
262 Weighted data
205
References:
Killias M., Staubli S., Biberstein L., Bänziger M., Iadanza S. International Crime Victimization
Survey (ICVS) 2010/2011.
http://krc.ch/de/index.php?a=Research&b=Forschung&c=Abgeschlossene-Forschungsprojekte
Lanfranconi B., Killias M. “The Crime Drop Discourse – or the Illusion of Uniform Continental
Trends: Switzerland as a Contrasting Case”, in J. van Dijk, A. Tseloni& G. Farrell (Eds.),
The International Crime Drop. New Directions in Research, Basingstoke (Hampshire,
UK): Palgrave-Macmillan 2012, 268-278.
Ribeaud D. & Eisner M. Entwicklung von Gewalterfahrungen Jugendlicher im Kanton
Zürich.Oberentfelden: Sauerländer. 2009.
206
Chapter 8
Contact with the police and perception of the image of the police
8.1 Overview
In the ISRD-3 respondents were asked about experience of contact with police because of
doing something illegal; as well as about students’ attitude to the police, their assessment of
police’s work and image of the police. The questionnaire includes 8 questions and 10
variables (modules 7 and 10 and about the police). Only 9th grade students were asked to
answer these question.
This chapter includes analyses of demographic factors influencing attitudes to the police and
information on how different attitudes to police are associated with delinquency.
8.2 Experience with and attitudes to the police
8.2.1 Attitudes across regions
8.2.1.1 The prevalence of contact with police because of illegal behaviour
Most respondents had some police contact at least once during their life-time, but few
(roughly 8 per cent) had so over the last year. There is fairly little difference across regions.
8.2.1.2 Opinion of young people about the police
Several questions were asked regarding views about the police and police work, including
illegal or unfaithful behaviour on the side of police officers. The findings certainly do not
necessarily reflect real experiences, but give an idea about what young people of 15-16 years
think about the police.
207
Figure 8.1
When victims report an offence to the police, police treat all groups
equally,by main and subsamples, in %.263
60.0
40.0
20.0
50.4
49.6
39.1
38.7
11.7
10.5
40.8
37.7
14.4
7.1
40.0
33.9
48.0
46.9
37.9
19.4
12.4
6.8
1.7
40.6
34.4
39.3
39.3
34.4
14.1
4.7
16.7
4.7
15.0
10.0
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
ITA
(N=642)
SG
(N=625)
AG
(N=555)
GE
(N=268)
ZH
(N=266)
No, everybody is treated equally
I do not know
Africans, Arabs, Yugoslavians, Moslems are treated worse
Other groups of foreighners, other groups of people (youths, other religion and so on) are treated worse
Overall, about two in five students think the police treat everybody the same way if a victim
comes to report a crime. However, there is some variation across the country. Ticino youths
are almost unanimous at considering police behaviour as egalitarian, whereas in Frenchspeaking cantons, as well as in Aargau and Zurich, many students claim not being able to say.
If discriminatory behaviour is anticipated, it is so mostly against Africans, Arabs, citizens of
former Yugoslavia, or Muslims in general.
A further question concerned presumed responsiveness in case of an emergency call. As an
example, burglary was presented.
263 Weighted data
208
“If burglary was committed, how quickly police would arrive?” by main and
different subsamples by main and subsamples in %.264
Figure 8.2
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
61.8
59.7
58.3
57.7
56.6
47.7
38.1
24.5
15.7
23.2
15.0
Switzerland
DE
(N=4'158) (N=2'560)
17.9
25.5
17.5
14.2
FR
(N=956)
ITA
(N=642)
slow
middle
33.3
28.3
24.7
13.3
SG
(N=625)
62.8
53.6
15.4
13.0
AG
(N=555)
GE
(N=268)
21.8
ZH
(N=266)
fast
Most students assessed speed, with which police would arrive at the scene of burglary, as
“middle” in almost in all regions.
The next questions were about police attitudes towards young people in general.
“Would you say that police generally treat young people with respect?”by
Figure 8.3
40.0
37.7
36.5
30.7
10.0
40.1
35.3
29.4
26.9
26.8
30.0
20.0
47.0
46.2
50.0
14.9 16.4
12.5 12.9 10.7
9.9
8.1
7.5
32.6
30.3
27.3
20.318.8
16.9
13.9 12.9 12.3 16.1
30.1
26.2
18.2 17.3
16.7
7.6
6.4
10.4 9.8
6.7
0.2
0.0
Switzerland
DE
(N=4'158) (N=2'560)
(almost) never
FR
(N=956)
ITA
(N=642)
sometimes
often
SG
(N=625)
AG
(N=555)
(almost) always
GE
(N=268)
ZH
(N=266)
don't know
Overall, nearly half of respondents reported that police treat young people “often” or
“always” with respect. More than10 per cent say that respect for young people can (almost)
never be expected. There is some variation across the country, critical attitudes being the most
frequently expressed by students from Latin cantons including Geneva.
264 Weighted data
265 Weighted data
209
Figure 8.4
How often police explains their decisions and actions to young peopleby main
50.0
40.0
30.0
20.0
10.0
38.2
33.3
35.6
34.5
28.8
35.9
33.3
34.0
24.7
16.4 18.5
13.0 14.1 10.6 12.7
9.9
9.5
29.4
27.9
25.8
24.2
20.9 19.0 21.9
19.7 19.9
15.3 15.2 15.2
14.9
10.9
9.9
7.0
37.8
28.7
15.9
9.8
7.9
0.2
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
(almost) never
ITA
(N=642)
sometimes
SG
(N=625)
often
AG
(N=555)
(almost) always
GE
(N=268)
ZH
(N=266)
don't know
According to about half of our respondents, police explain their decisions and actions often or
always. Again, attitudes are more critical in this respect in Latin cantons and in Geneva.
Given the urban background of Zurich, it is remarkable that the Zurich police is rated
relatively favourably across these different dimensions.
“How you think about your duty towards the police: To what extent is it your
duty to do what the police tell you, even if you don’t understand or agree with
the reasons?” by main and subsamples in %.267
Figure 8.5
60.0
50.0
40.0
36.5
33.6
36.4
32.7
31.3
30.0
20.0
52.3
49.5
30.8
29.3
23.7
22.1
13.8
16.1 13.9
16.2
13.4
10.0
30.0
29.4
22.6
18.0
33.8
27.7
23.1
15.4
38.7
31.1
16.6
30.1
19.0
12.3
0.7
0.0
Switzerland
DE
(N=4'158) (N=2'560)
my duty
FR
(N=956)
ITA
(N=642)
neither/nor
SG
(N=625)
not my duty
AG
(N=555)
GE
(N=268)
ZH
(N=266)
I do not know
266 Weighted data
267 Weighted data
210
Roughly two in five respondents accept as their duty to do what the police tell them to do.
Interestingly, given the more critical attitudes, in Latin cantons, this proportion is highest in
French-speaking cantons including Geneva.
“Police has the same sense of right/wrong as I do” (Agree/disagree) by main
Figure 8.6
50.0
40.0
40.5
36.9
30.3
20.0
10.0
33.3
31.8
29.6
26.6
30.0
42.6
38.6
41.3
38.8
37.5
30.0
27.0
14.9 13.9
11.3
11.3 12.3
10.9 12.8 8.59.6
9.8
9.0
8.1
6.76.9
16.8
21.920.3
12.5
7.8
21.7
16.3
14.5 14.5
10.6
10.5
1.9
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
disagree strongly
ITA
(N=642)
disagree
SG
(N=625)
neither/nor
AG
(N=555)
agree
GE
(N=268)
ZH
(N=266)
agree strongly
Overall, about half of respondents feel that the police share the same sense of right and wrong
as they do. Agreement is lower among students in French-speaking cantons and in Geneva.
Again, the contrast between Geneva and Zurich/St. Gallen is remarkable.
“Police are appreciative of how young people think” (agree/disagree) by main
Figure 8.7
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
37.0
33.1
26.3
19.7
31.4
27.4
18.9
12.7
12.5
8.4
9.7
33.3
24.4
20.8
disagree strongly
7.4
5.8
FR
(N=956)
36.8
33.3
28.6
24.3
22.2
12.7
12.0
Switzerland
DE
(N=4'158) (N=2'560)
33.1
32.7
ITA
(N=642)
disagree
10.5
7.3
SG
(N=625)
neither/nor
20.4
16.4
14.5
11.8
16.4 17.5
14.3
agree
25.5
22.3
7.6
6.3
AG
(N=555)
35.0
GE
(N=268)
9.6
ZH
(N=266)
agree strongly
268 Weighted data
269 Weighted data
211
Opinions on whether or not the police are appreciative of how young people think do not
differ much across regions.
“I support how police act” (agree/disagree) by main and subsamples in %.270
Figure 8.8
50.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
43.1
39.7
39.4
32.8
29.6
32.3
30.0
44.0
41.0
39.3
30.8
27.9
25.6
10.4 12.0 9.1
8.5
8.3
ITA
(N=642)
disagree
26.4
15.1
12.6 11.9
5.0
4.85.0
FR
(N=956)
disagree strongly
12.5
11.5
9.8 11.5 9.2
9.0
8.5
7.1
Switzerland
DE
(N=4'158) (N=2'560)
18.4
15.9
12.7
13.7 12.4
33.6
29.6
SG
(N=625)
neither/nor
AG
(N=555)
agree
GE
(N=268)
ZH
(N=266)
agree strongly
Overall, about half of respondents support how the police act. Support is lower in Latin
cantons and in Geneva, but explicit disagreement does not vary much across regions.
How often police takes bribes by main and subsamples in %.271
Figure 8.9
60.0
50.0
53.5
53.2
46.4
20.0
46.7
40.0
40.0
30.0
52.1
47.9
32.8
29.4
21.5
12.7
11.4
10.0
30.7
29.1
19.0
15.2
9.9
34.2
25.1
15.1
24.8
13.5
8.5
21.5
26.2
24.5
19.1
12.9
10.4
12.3
0.3
0.0
Switzerland
DE
(N=4'158) (N=2'560)
FR
(N=956)
never/almost never
ITA
(N=642)
neither/nor
SG
(N=625)
AG
(N=555)
often/very often
GE
(N=268)
ZH
(N=266)
I do not know
270 Weighted data
271 Weighted data
212
Nearly half of students say the police never take bribes. There is, however, considerable
variation across the country, with more respondents suspecting the police to take bribes in
Latin cantons.
8.2.2 Opinion of young people about the police by gender
Boys and girls do not differ much regarding perceived egalitarian vs. racist attitudes, as the
following Table 8.1 illustrates. None of the differences is significant.
Table 8.1
Male
Female
ChiSquaire
“When victim reports to police, police treats all groups equally” by gender in
%, N=1296.272
No, everybody is
treated equally*
39.0
39.1
I do not
know*
35.6
41.6
Other groups of
No, police is biased
people: foreigners,
against africans,
youths, people from
arabs, yugoslavians, other religions and so
moslems*
on*
12.5
12.9
8.7
10.6
.029
*These groups were obtained by recoding of the opened answer of the question 10.1 “When victims report crimes to the
police, do you think the police treat people of different races, different ethnic groups, or of foreign origin equally?”
However, as the following Figures illustrate, boys tend to be far more critical about the police
than girls.
“If burglary was committed, how quickly police would arrive?” by gender in
%, N=1233.273
Figure 8.10
80.0
64.0
60.0
55.2
40.0
20.0
12.6
25.7
23.4
19.1
female
male
0.0
slow
middle
fast
272 Weighted data
273 Weighted data
213
Figure 8.11
“Would you say the police generally treat young people with respect?” by
gender in %, N=1357.274
50.0
39.1
40.0
29.5 31.9
30.0
17.1
20.0
10.0
33.7
14.7
8.0
female
11.0
8.8 6.2
male
0.0
(almost) never
sometimes
40.0
29.8 27.7
30.0
don't know
35.5 33.6
17.0
20.0
(almost) always
“How often the police explain their decisions and actions to young people?”
by gender in %, N=1355.275
Figure 8.12
10.0
often
14.0 14.1
9.4
female
11.4
7.6
male
0.0
(almost) never
sometimes
often
(almost) always
don't know
274 Weighted data
275 Weighted data
214
“How you think about your duty towards the police?” by gender in %,
N=1339.276
Figure 8.13
42.2
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
37.6
30.5
29.8
female
18.2
18.1
13.8
male
9.8
my duty
neither/nor
not my duty
I do not know
Males do twice as often not consider it to be their duty to do what the police tell them to do
than females.
“The police has the same sense of right/wrong as I do (agree/disagree)” by
gender in %, N=1324.277
Figure 8.14
41.8
45.0
40.0
32.0
35.0
28.5
30.0
31.8
25.0
20.0
15.7
12.1
15.0
10.0
9.9
11.9
10.2
female
male
6.2
5.0
0.0
disagree strongly
disagree
neither/nor
agree
agree strongly
Boys and girls do not differ much in their perception of police values, but boys tend to
express more extreme judgments (in either way).
276 Weighted data
277 Weighted data
215
“I generally support how the police usually act (agree/disagree)” by gender in
%, N=1315.278
Figure 8.15
50.0
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
45.9
30.7 29.2
32.5
15.9
11.1
5.6
disagree strongly
9.6 11.3
disagree
8.3
neither/nor
agree
female
male
agree strongly
Boys and girls, once more, do not differ much overall, but boys’ judgments are more extreme.
The questions on police corruption did not significantly differentiate between girls and boys.
8.2.2 Opinion of young people about the police by respondents’ birthplace
Attitudes towards the police are often a source of worry when it comes to ethnicity. In many
countries, immigrant youths are said having particularly bad views about the police. In
Switzerland, this did not hold true for the general (adult) population, as several Swiss Crime
surveys have allowed to discover (Killias, Haymoz&Lamon 2007, 92). It has not been studied
in detail, however, to what extent this holds true also for juveniles.
In the present study, ethnicity has been measured by questions concerning birthplace (country
of origin) of respondents and their fathers/mothers, rather than by asking about nationality.
This was the only way the ISRD Steering Committee could think of that might work in some
30 countries around the globe. In connection with attitudes towards the police, respondents’
birthplace turned out to be more important than the country of origin of their parents. We
shall, therefore, focus on respondent’s birthplace in this section.
Overall, respondents born abroad tend to be more critical about the police. This might to some
extent be due to higher involvement in delinquency, as shown in Chapter 7. It will be most
interesting to see, when the results from other countries become available, whether attitudes
among immigrant youths in Switzerland differ from those expressed by juveniles in other
countries.
278 Weighted data
216
“When victims report crimes to the police, do you think the police treat
people of different races, different ethnic groups, or of foreign origin
equally?” by respondents’ birthplace in %, N=1296.279
Figure 8.16
50.0
35.6
40.0
39.7
37.5
39.0
30.0
15.4
20.0
9.6
10.0
11.5
11.8
0.0
No, everybody is treated
equally
I do not know
Africans, Arabs,
Other groups of
Yugoslavians, Moslems are foreighners, other groups
treated worse
of people (youths, other
religion and so on) are
treated worse
not in Switzerland
Switzerland
Students born in Switzerland are more likely to report that police treats all people equally.
However, the differences are not that large – Swiss respondents more often indicate “not to
know”, due probably to lack of relevant experience.
“If a violent crime or a burglary happened near where you live and the police
were called, how quickly do you think they will arrive at the scene?” by
respondents’ birthplace in %, N=1231.280
Figure 8.17
70.0
60.8
60.0
53.5
50.0
40.0
30.0
20.0
27.3
19.3
24.0
15.1
not in Switzerland
Switzerland
10.0
0.0
slow
middle
fast
Respondents born abroad more often say the police would come slowly if a violent crime or a
burglary happened.
279 Weighted data
280 Weighted data
217
“How often would you say the police explain their decisions and actions to
young people?” by respondents’ birthplace in %, N=1354.281
Figure 8.18
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
36.5
36.3
27.3
24.7
17.8
14.214.1
12.2
6.8
(almost) never
sometimes
often
(almost)
always
10.1
not in Switzerland
Switzerland
don't know
Respondents born in Switzerland are more likely to report that police often and very often
explain their decisions and actions to young people.
“How you think about your duty towards the police?” by respondents’
birthplace in %, N= 1337.282
Figure 8.19
40.0
33.3 33.7
33.8
36.9
30.0
20.0
18.8
14.1
12.9
16.5
not in Switzerland
Switzerland
10.0
0.0
my duty
neither/nor
not my duty
I do not know
Respondents born abroad are less likely to consider having the duty to do what the police tell
them to do.
281 Weighted data
282 Weighted data
218
“I generally support how the police usually act” by respondents’ birthplace in
%, N=1313.283
Figure 8.20
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
40.4
37.1
34.3
28.7
10.5
7.8
7.6
10.5 12.2
10.8
not in Switzerland
Switzerland
disagree
strongly
disagree
neither/nor
agree
agree strongly
Students born abroad are less likely to support how the police usually act.
In many of these comparisons, the differences are, although significant, not that strong. It is,
therefore, noteworthy that several attitude questions did not produce significant differences.
This has been the case for the following items:
-
“Police generally have the same sense of right and wrong as I do” (p=.540)
“The police are appreciative of how young people think” (p=.509)
“Would you say the police generally treat young people with respect?” (p=.377)
Regarding police corruption, it is somewhat disturbing that quite a few respondents, both
from immigrant and Swiss background, think the police were taking bribes. Given
Switzerland’s scores in all international comparisons, this comes as a surprise and presumably
shows that preconceptions in this field may be more important than concrete experience.
Unfortunately and for reasons related to the sensitive aspect of this theme in many countries,
no question as to concrete experiences with paying bribes, or being requested to do so, could
be included in the questionnaire.
283 Weighted data
219
“Do you think the police take bribes, and if yes, often?” by respondents’
birthplace in %, N=1339.284
Figure 8.21
60.0
48.8
50.0
40.0
34.6
30.0
32.7
28.7
not in Switzerland
15.9
20.0
16.8
12.1
10.4
Switzerland
10.0
0.0
Never/almost
never
neither/nor
often/very often
I do not know
Respondents born in Switzerland are more likely to think that police never or almost never
take bribes. Students born abroad have more neutral position or answer that police take bribes
often or very often. That immigrant youths are more often inclined to suspect the police to be
corrupt may, to some extent, eventually be related to their own experience in their respective
countries of origin. As Crime Surveys conducted in Switzerland allowed to discover,
corruption is, for the Swiss general (adult) population, mostly an experience lived abroad
(Killias, Haymoz&Lamon 2007, 57).
284 Weighted data
220
8.2.3 Opinion of young people about the police by delinquency (last year prevalence)
Attitudes towards the police are associated with delinquency. Given the cross-sectional design
of ISRD, we cannot say, however, whether negative feelings about the police favor
delinquency, or whether, the other way around, delinquents have less positive attitudes
towards police officers. Both explanations are, at first glance, equally plausible.
Delinquency (last year prevalence) by “Would you say the police generally
treat young people with respect?” in %, N=1347-1355.285
Figure 8.22
32.1 32.7
35.0
29.3 28.3
28.0
30.0
24.6
22.9
22.5
21.1
25.0
17.9
16.4
20.0
14.5
14.3
13.0
12.7
11.7
11.6 13.2
11.4
11.4
11.4
15.0 11.1
10.2
9.1
8.7
8.6
8.3
7.3
6.9
6.9
6.9
6.5
6.13.9
5.9
5.7
10.0
4.9 2.9
4.6
4.12.3
4.0 4.95.9 5.8
4.0 2.7
3.0
2.9
2.9
2.6
2.3
2.3
2.2
2.0 1.7
2.0
1.7
1.5
1.1
1.0
1.0 1.0
1.0
1.0
0.8
5.0
0.6
0.0
0.0 1.0
0.0
(almost) never
sometimes
often
(almost) always
don't know
Respondents, who report that police never or almost never treat young people with respect,
are more likely to commit an offence.
285 Weighted data
221
Figure 8.23
Delinquency (last year prevalence) by how often police explains their
decisions and actions to young people in %, N=1347-1353.286
32.8
35.0
28.6
28.2
26.7
30.0 25.0
24.7
25.0
21.1
19.5
19.5
16.4
20.0
15.8
13.2 12.1 12.1
11.612.6
11.3
15.0 11.3
11.0 10.6
10.8 10.3 12.1 9.1
10.0 11.4
9.8
9.4
9.0
8.8
7.9
7.9
7.7
7.3
10.0
6.2
6.2
5.4
4.8
4.7 5.8
4.7
4.2
4.2
3.9
3.9 3.1
3.6
3.1
3.1 2.6
2.61.6
2.3
2.3 2.1
2.12.3 1.0
2.1
1.6
1.6 3.2
1.5
1.5
1.5
1.5
5.0
1.1
1.1
0.9
0.8
0.0
(almost) never
sometimes
often
(almost) always
don't know
Students, who say that police never or almost never explain their decisions and actions to
young people, are more likely to commit any type of offence. The same pattern is visible
throughout the following Figures.
286 Weighted data
222
Delinquency (last year prevalence) by “When victim reports to police, police
treats all groups equally” in %, N=1286-1292 287
Figure 8.24
34.6
40.0
30.0
20.0
10.0
24.3
21.1
16.2
15.1
11.0
8.6
7.6 6.5
27.9
21.6
19.9 22.1
19.9
19.4
19.1
15.8
14.5
13.1
11.0
10.4 8.2
8.9
8.8 6.8
8.0
7.4
7.4
7.2
6.6 4.2
6.0 3.47.4
5.9
5.3
5.2
4.6
3.8
3.7
3.7
3.4
3.3
3.2
3.0
2.6
1.6
1.6 1.8
1.6
1.4
1.2
0.8
20.4
14.2
12.1
0.0
I do not know
Africans, Arabs, Yugoslavians, Moslems
Other groups of foreighners, other groups of people (youths, other religion and so on)
Students, who report that police treat Africans, Arabs, citizens of former Yugoslavia and
Muslims less favourably, commit more offences. For all offences, those who perceive no
discriminatory attitude on the side of the police have the lowest offending rates.
The interesting question is whether this effect is different for Swiss and for immigrant
respondents. Given that only 9th-grade students answered to these questions and that the
national sample is smaller in this chapter, we use in the following two Figures mother’s
background as a proxy for nationality. Indeed, more mothers (344) were born abroad than
fathers (325) and respondents (134).
287 Weighted data
223
treat all groups equally” if mothers were born in Switzerland in %, N=732737.288
Figure 8.25
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
38.5
27.7
23.1
20.0
18.5
21.5
22.4
16.5
15.4
15.3
13.8
13.7
11.8
11.7
11.4
10.8
10.6
9.6
7.9 7.2
7.69.4 7.8
7.1 6.6
6.9
6.5
6.25.9
6.2 7.5
6.2
5.4
5.1
4.6
4.0
3.6
3.4
3.1
3.0
2.8
2.4
2.4
2.1
2.1
2.0
1.2
1.2 1.00.0
1.2
1.0
0.3 1.2
0.3
0.0
I do not know
288 Weighted data
224
Figure 8.26
treats all groups equally” if mothers were born abroad in %, N=540-544.289
35.0
29.0
27.7
27.5
30.0
25.8
25.0
24.6
24.6
23.2
23.1
23.1
21.7
21.5
21.5
25.0
20.3
17.4
20.0
15.4
14.7
14.1
12.1 13.2
11.6
15.0 12.9
10.9
10.8
9.6 7.9
9.4
9.2
8.8
8.8
8.7
8.3
7.7 8.7 5.9
7.7
7.6
7.4
7.3
7.2
10.0
4.9
4.6
4.4 3.9
3.8 4.4
3.5
3.4
2.9
1.5
1.5
1.5
1.5 2.0
5.0
1.0
0.0
0.0
I do not know
The pattern is basically the same for respondents born in Switzerland and born abroad.
However, seeing the police as biased against immigrants is less clearly associated with
delinquency among respondents with a foreign-born mother. It could be that seeing the police
as biased against certain ethnic groups is more related to an immigrant background as such
rather than to delinquency, as it typically is among Swiss respondents.
289 Weighted data
225
Delinquency (last year prevalence) by “Duty to do what police tells you to do
even if you do not understand or agree” in %, N=1331-1337.290
Figure 8.27
30.9
35.0
28.6
27.1 27.8
30.0
25.4
23.3
22.5
25.0
19.2
19.1
20.0
13.9
13.6
13.1
13.1 12.7
12.0
11.6 12.2
15.0
10.9 10.7
10.6 11.6
9.4
9.3
9.3
8.9
8.2
8.0
7.8
7.7
7.4
7.0
6.6
6.0
10.0
5.6
5.6
5.1
4.7
4.7
3.8
3.3
2.8
2.7
2.3
2.3
2.3
2.0
1.9 1.3
1.8
1.6
1.1
5.0
0.9 2.7
0.9
0.6
0.0
0.0
my duty
neither/nor
not my duty
I do not know
A more critical attitude towards the police goes along, once more, with higher rates of
delinquency. The same is true for the following Figures.
Delinquency (last year prevalence) by “Police has the same sense of
right/wrong as I do (agree/disagree)” in %, N=1315-1323. 291
Figure 8.28
37.8
40.0
34.5
31.1
35.0
29.9
29.4
28.6
27.7
26.1
30.0
23.9
22.9
25.0
19.2
16.2
16.1
20.0
15.1
12.5 12.3
12.4
12.412.0
11.9
11.9 12.6
11.8
11.8
11.8
11.8 10.9
11.2
15.0
10.1 9.8
9.4
9.28.9 10.7
9.0
8.57.1
7.4
7.0
6.8
6.6
6.5
6.1
5.9
5.3 5.6
10.0
4.7
4.1 4.1 2.1 5.4 4.05.35.9
3.5
2.7
2.3
2.2
2.1
2.1
1.6
1.5
1.4
1.4
1.4
1.0
0.8
0.7
0.5 0.0
5.0
0.0
disagree strongly
disagree
neither/nor
agree
agree strongly
290 Weighted data
291 Weighted data
226
Delinquency (last year prevalence) by “Police are appreciative of how young
people think (agree/disagree)” in %, N=1305-1312.292
Figure 8.29
35.0
30.1
29.6 30.1
27.8
26.4
25.9
30.0 24.5
25.0
18.8
17.8 18.9
20.0
15.5
13.6
13.3
13.2 12.8 13.5
12.0
11.8
11.1
15.0 10.1
10.8
9.7 9.8
9.2
9.2
9.1 10.0
9.1 8.2
9.111.0
9.0
8.6
8.6
8.5
8.3
8.2
8.1
7.5
7.3
7.3
7.1
6.9
6.4
6.3
6.3
6.0
10.0
5.8
5.5
5.54.3
4.8
3.93.2
3.8
3.5
3.2
2.6 1.2
2.5
1.8
1.6
1.5
1.5 1.9
1.5
1.4
1.4
1.2
5.0
0.5
0.0
disagree strongly
Figure 8.30
disagree
neither/nor
agree
agree strongly
Delinquency (last year) by “I support how police act (agree/disagree)” in %,
N=1306-1314.293
45.0
38.9
37.6
35.8
40.0
33.0
33.0
31.2
35.0 27.5
25.7
25.0
30.0
20.0
25.0 19.7 17.5
18.4 19.7
16.9 15.7
15.4 13.8
20.0
14.0
14.0
13.9
12.8
12.8
11.7
11.7
11.0
10.9
10.8
10.4
10.2
10.0
9.7
9.7
15.0
9.4
9.2
8.9
8.4 6.2
8.3
7.0 7.6
6.0 6.63.7
5.7
5.3
5.2 3.6
5.2 4.42.7
4.9
4.5 2.2 5.7 6.0
10.0
3.9
3.7
2.7
2.5
2.2
2.0
1.9
1.3
1.3
1.3
1.0
0.8
0.8
0.6
5.0
0.0
disagree strongly
disagree
neither/nor
agree
agree strongly
Delinquency rates are also higher among respondents who see the police as corrupt. Indeed,
perceived delinquency among those who are in charge of maintaining public order certainly is
directly threatening the legitimacy of such an institution.
292 Weighted data
293 Weighted data
227
Figure 8.31
27.2
30.0
25.0
Delinquency by perceived police corruption (“Do you think the police take
bribes, and if yes, how often?”) in %, 1332-1339.294
20.7
20.0
23.7
22.0
18.8
18.5
14.6
14.3
14.0 13.313.7
13.6
13.1
12.8
12.5
12.4
11.3
11.2
11.1
10.7
10.7
10.6
10.5
10.2
9.5 8.5
8.9 7.6
8.9
8.9 9.2 8.2
8.9
8.3
7.6
10.0 6.3
6.8
6.5
6.5
6.14.6
3.7
3.3
3.3
2.9
2.8
2.6
2.3
2.0
5.0
1.8
1.8
1.6
1.5
1.5
1.0
0.0
0.0
15.0
never/almost never
neither/nor
often/very often
I do not know
Contrary to misbehavior among police officers, the feeling that their efficiency as an
organization is less than perfect is less clearly associated with delinquency, as the following
Figure illustrates.
294Weighteddata
228
Figure 8.32
Delinquency (last year prevalence) by “If burglary was committed, how
quickly police would arrive?” in %, N=1225-1234.295
25.0
20.0
14.0
12.2
10.811.0
8.3
8.3
10.0
15.0
5.0
19.6
15.5
13.9
13.6 13.6
12.0
11.7
10.7 12.0
9.6
9.0
8.8
13.5
9.3
8.4
2.3
2.1
1.4
5.7
3.7 2.6 3.0
2.7 2.0
2.6
1.5
1.2
13.0
7.9
7.6
4.7
3.8
3.6
5.0
3.1
3.1
0.0
slow
middle
fast
Students, who say that police would arrive slowly to a crime scene are more likely to commit
offences of all sorts. However, the differences are somewhat less pronounced than in the
preceding Figures. This could be related to the fact that lack of efficacy is less considered as a
kind of a “moral” defect.
295Weighteddata
229
8.3
Conclusion
Attitudes towards the police are relatively positive overall. However, there are a few
remarkable regional differences. In the Romandie cantons and especially in Geneva, attitudes
are more critical towards the police than in German-speaking Switzerland. This may, to some
extent, be due to the higher proportion of immigrants in French-speaking cantons where more
than 50 per cent of parents of respondents were actually born abroad (see Chapter 1).
Noteworthy is the consistently positive view of the police in Zurich, given the highly
urbanized environment. Girls see the police more favorably than boys.
Students born in Switzerland have more positive views about the police.
Positive attitude towards the police goes along with lower rates of delinquency. It is not clear
whether delinquency is an outcome of negative feelings about the police, or whether
delinquent involvement and, therefore, probably more contacts with the police as a suspect
produce negative feelings.
References:
Killias M., Haymoz S., Lamon P. Swiss Crime Survey. Die Kriminalität in der Schweiz im
Lichte der Opferbefragung von 1984 bis 2005. Bern: Stämpfli Verlag AG, 2007. 179p.
230
Chapter 9
Technical Report
9.1 Background
The first juvenile self-reported delinquency survey conducted in Switzerland with a national
sample took place in 1992, when the country participated in the first International Self-Reported
juvenile Delinquency project (ISRD-1). The second juvenile self-reported delinquency survey
took place in 2006, where more than 3’500 male and female juveniles attending the 7th – 9th
grades in 20 cantons participated. Since then no national surveys were conducted, but some
cantonal or city surveys were carried out (e.g. in the cantons of Zürich, Vaud and St. Gallen). In
recent years most of the official measures of crime (police and court statistics) suggest that
juvenile delinquency has a tendency of decreasing that contradicts with our results (comparison
of the prevalence of the selected offending in 2006 (ISRD-2) and 2013 (ISRD-3). Thus, the
current survey is extremely important in order to assess trends in juvenile delinquency at a
national level.
9.2 Sample design
The Swiss ISRD-3 involves a national random sample of 2’854 male and female juveniles
attending the 7th – 9th grades, which in the Swiss context corresponds to pupils aged mostly 1216. This sampling procedure was preferred over the city-sampling procedure  used in most of
the participating countries  because Switzerland is a small country with approximately 8 million
inhabitants296 and does not have any large city but only medium ones (the largest city, Zürich,
has a population of 400’000 inhabitants297). The sampling was drawn out of a list given by the
Swiss Federal Statistical Office containing all school facilities from the 7th to the 9th grades
existing in each Swiss canton. This list also gave information about the number of students per
grade, but did not include information about number of classes per grade and type of school 298. It
did not allow us to make a sample of classes at the very beginning, although the sample unit was
class.
The sampling occurred in four steps described below in the following sections.
296
Bevölkerungsstand und struktur.
Schweiz.http://www.bfs.admin.ch/bfs/portal/de/index/themen/01/02/blank/key/alter/gesamt.html
297
Statistik Stadt Zürich https://www.stadt-zuerich.ch/prd/de/index/statistik/bevoelkerung/bevoelkerungsstand.html
298The types of schools in accordance with: (1) pattern of property (Private/government); (2) pupils' capacities and
career-intentions (vary in different cantons).
231
9.2.1 Step 1: Selection of schools
For the national sample, 3’000 interviews were envisaged. Based on observations made during
ISRD-2 in 2006, we presumed that the number of students would be about 19 on average per
class. Therefore, it was planned to interview about 160 classes (3‘000 / 19 ~160). Anticipating
that about 70 percent of schools would cooperate, we decided to draw a sample of 219 classes.
The Swiss Federal Office of Statistics provided us with a list of schools that was used for the
national PISA tests. Out of these, 219 schools were randomly selected. Both private and
government schools where taken. Schools for children with special needs and small schools that
included only few students per grade were excluded because we could not guarantee the
confidentiality of responses in such settings.
9.2.2. Step 2: Collecting information about number of classes in the selected schools
All cantonal Departments of Education were contacted to obtain a complete list of classes per
selected school. Information was also obtained from School Internet sites and some school
principals. Thus, we gained a list of 2’458 classes nationwide299.
9.2.3. Step 3: Random selection of classes
Out of this list of 2’485 classes, 219 classes were randomly selected. In larger schools, two or
more classes were included due to this procedure. These 219 classes belonged to 127 schools. At
this stage, four small cantons (UR, NW, SH, JU) dropped out because none of their classes was
included in the national sample. The list of classes is given in Attachment 3.
9.2.4. Step 4: Additional sample
In the three cantons that wished to receive in-depth analysis, additional classes were randomly
selected to receive final (cantonal) samples of 550 students at least. The oversamples are as
follows:
- in the canton of Aargau, 17 classes from 11 schools,
- in the canton of St. Gallen, 26 classes from 12 schools,
- in the canton of Ticino, 22 classes from 14 schools.
9.3 The fieldwork
The fieldwork started by the end of February and ended by the end of November 2013. It was
carried out by our research group initially located at the Universtiy of Zurich (till June 2013) and
later at the University of St. Gallen (from June 2013 till now).
299
decision was made 20.09.2012.
232
9.3.1. Contacting schools
We contacted the Departments of Education in all cantons (see Attachment 9) with the support of
the Conference of Cantonal Directors of Education (Konferenz der Kantonalen
Erziehungsdirektoren EDK), see Attachment 8.
In some cantons we also contacted the schools directly by sending official letters with (1) copies
of the letters from the Department of Education supporting the project; (2) letter from the
Institute of Criminology of Zürich University asking for their participation with 3 attachments
(Instructions for teachers of survey making, Research plan, Informational letter for parents) (see
Attachment 5). Our research group made the necessary support by telephone and email,
communicated with school principals and single teachers.
9.3.2. Data collection
The cooperation of schools in the main sample was about as expected. In the end, 170 out of 219
classes have participated, which leaves a class-based response rate of 77.6% percent. The
number of schools that participated is 98 out of 127 (response rate is 77.2%). The response rate
at the level of schools and classes is lower in 2013 compared to 2006 when it was 94.5%. The
higher drop-out rate can be explained by increasing reservations among school principals about
the involvement of schools in research projects.
In case of declining participation schools were replaced (the table is below) if time constraints
allowed to do so. The list of replacements is given in Table 9.1. Schools could not be replaced if
we were informed about their refusal after May 2013.
233
Table 9.1
List of substituted schools
Date
Originally sampled school
Substituted school
26.02.2013
Schule Liestal BL
Rudolf Steiner Schule Birseck
BL
26.02.2013
Real, Sekundar, Berufswahlschule,
Kleinklasse der Orientierungsschule,
Neuendorf
Schulanlage, Boswil
AG
26.02.2013
Kollegium Spiritus, Brig-Gris, VS
Orientierungsschule, Gampel
VS
28.02.2013
Bern Munzinger
Ecolesecondaire, Courtelary
BE
28.02.2013
Grenchen Schulhaus III
Oberstufenhaus, Niedergösgen
SO
09.04.2013
Oberstufenschule Aeschi-Krattigen,
Täuffelen, Oberstufenzentrum
BE
Canton
No school refused in the cantons of AI, LU, SG, GL, OW, BL, GR, NE, TI, AR; 100% of the
selected classes were surveyed. In the cantons of AG, FR, VD, BE, TG, SO, ZH and GE, more
than ½ of sampled classes finally participated. The lowest response rate was in VS, ZG und SZ,
where less than one third from the estimated classes participated. The most prominent reasons of
declining participation were mostly (1) a packed schedule at schools, or (2) participation in other
“similar” surveys. In case of declining participation schools were replaced (the table is below) if
time constraints allowed to do so. The canton of Basel-Stadt declined categorically taking part in
the study.
In order to calculate the response rate at the level of students, the Teachers’ Feedback Form has
been used. We have received this form from 80.0% percent of the classes included in the
national sample (i.e. leaving out cantons with oversamples), with a total of 2’386 enrolled
students, compared with 2’854 completed interviews. In all classes with this additional
information, 2’230 students were present during data collection, 160 were absent for reasons
unrelated to the survey, and 21 were present but did not respond. This leaves 2’209 completed
interviews, or a student response rate of 92.1 percent (i.e. 2’209 / 2’386).
For the national sample (i.e. without the oversamples in the cantons of SG, AG and TI), 2’854
interviews have been completed, of which 1’702 are in German (59.6%), 956 in French (33.5%)
and 196 in Italian (6.9%, not weighted data).
Including the oversamples in three cantons, 4’158 interviews have been completed.
234
9.3.3. Interviews and teachers
The survey took place in the computer rooms of the schools. To open the questionnaire each
respondent had to follow the link of the survey and enter the password as indicated in the
instructions that were sent to teachers. There were 10 links for students, on the Internet page300:
For German speaking schools for the 7th-8th grades;
For German speaking schools for the 9th grade;
For French speaking schools for the 7th-8th grades;
For French speaking schools for the 9th grade;
For Italian speaking schools for the 7th-8th grades (this link was deleted after completing
the study in TI to avoid confusions with the additional sample);
- For Italian speaking schools for the 9th grade (this link was deleted after completing the
study in TI to avoid confusions with the additional sample);
- For the additional sample. For German speaking schools for the 7th-8th grades;
- For the additional sample. For German speaking schools for the 9th grade;
- For the additional sample. For Italian speaking schools for the 7th-8th grades;
- For the additional sample. For Italian speaking schools for the 9th grade.
Pupils had to use their computer mouse and keyboards to fill in the questionnaire. Although most
of questionnaires were filled in completely, some students did not finish for technical,
organizational or personal reasons. Nevertheless all responses reached the server automatically.
-
There were also links for Teachers’ Feedback Forms with the password, as indicated in the
instructions. Information from these Feedbacks allowed observing the process of the survey and
seeing the possible technical and organizational problems.
9.4. Questionnaire content and development
Instead of the paper-pencil questionnaire used in many countries participating in the ISRD3,
Switzerland used a computer-based online method through the Internet. In accordance with
experience of ISRD-2 in Switzerland (2006), there are no significant differences (Lucia,
Herrmann, Killias, 2007301) and the computer version reduces the risk of typing errors while
entering the data collected with a paper-pencil questionnaire.
In contrast to ISRD-2, the survey took place without external supervisors or research assistants:
the study at schools was controlled by school teachers. The comparative test showed that using
300
http://www.rwi.uzh.ch/lehreforschung/alphabetisch/killias.html
Lucia, S., Herrmann, L. & Killias, M. (2007).How important are interview methods and questionnaire designs in
research on self-reported juvenile delinquency? An experimental comparison of Internet vs paper-and-pencil
questionnaires and different definitions of the reference period. J. Exp. Criminol. (3), 39-64.
301
235
online questionnaire with teachers as supervisors may not affect validity while making surveys
less expensive and intrusive (Walser, Killias, 2012302).
Teachers filled out the online questionnaire-feedbacks, affording information about the course of
the survey: data and duration of the survey, number of present and absent students in class,
problems during the survey and so on. The full text of the Teachers’ Feedback is in Attachment
6.
The translations of the standardised English questionnaire into French, German and Italian were
made by our research group (text of the questionnaires in German, French and Italian are in the
Attachments 7.1-7.3.
The questionnaire in Switzerland includes 13 modules: 11 are from the core questionnaire and 2
are additional modules (“Dating control module” and “Computer games module”). The core
questionnaire is identical to the standardized one used by the rest of the countries, except the
country specific questions, needed to reflect the national situation. Among them are: Qs.1.3-1.5
to detect the birthplace of respondent and his/her parents; Q.1.8 to see the distribution of
religions appropriate for Switzerland; Q.1.10 to identify the minority group membership; Q. 1.13
to determine the source of family income; Q.5.5 to gain information on the composition of the
groups of friends with respect to migration status. To identify the class, grade, school, school
type, town and the canton of the respondent, the special questions were added with the title
“Before the beginning”.
Students of the 9th grade were asked all questions of the questionnaire. Students of the 7th-8th
grade did not answer the questions in module 10 regarding attitudes to the police.
9.5. Computer and Internet
During the survey, minor difficulties had to be faced due to the use of the computer
questionnaire: mostly they were related to connection problems but could be settled. One class in
TI could not complete the questionnaire; they were asked to try again, but they could not finish
the survey again. These 19 answers were deleted during the data cleaning, because they did not
include essential information. In one class, according to a teacher’s report, some students
expressed concern that our research group might inform their parents about the results of the
survey. However, they continued answering questions when teachers explained the principle of
anonymity.
302
Walser, S., Killias, M. (2012) Who should supervise students during self-report interviews? A controlled
experiment on response behavior in online questionnaires. J. Exp. Criminol. (8/1), 17-28.
236
9.6. Data processing and output
To collect the data, the online program Unipark was used. The time needed to fill out the
questionnaire did usually not exceed one lesson. Data from completed questionnaires were
entered automatically into the database, which could be then exported to SPSS Version 21.0 for
the analyses.
9.7. Data weighting
To take the size of cantons and the school grades into account, the data was weighted at the
national level for canton and school grade. Within the oversampled cantons the data was
weighted by the school grades only. Distribution of respondents by grade in the final unweighted
dataset (N=4’158) is as follows: 7th grade: 30.0%, 8th grade: 35.1%, and 9th grade: 34.9%. After
the data weighting such distribution is: 7th grade: 34.7%, 8th grade: 31.7%, and 9th grade:
33.6%. The slight imbalance in the general population is due to demographic changes within the
age-brackets included in this study303.
No weighting for age, gender and other demographic characteristics turned out to be necessary,
given the satisfactory match between the distributions in the sample and in the general juvenile
population.
All analyses were conducted with weighted data. The following table includes the sample size
per canton before and after weighting. In each Table, the N (absolute number) of respondents on
which the (valid) percentages are based is indicated. For practical reasons, the range of the
absolute numbers (in the national sample) is indicated, rather than the N for each category shown
in the Figure separately.
303
http://www.bfs.admin.ch/bfs/portal/de/index/themen/01/02/blank/key/alter/gesamt.html
237
Table 9.2
Obtained data before and after weighting by canton and grade.
General number of
students
participated in the
survey
Aargau *
555
Appenzell
54
Innerrhoden
Appenzell
15
Ausserrhoden
Bern
233
Basel99
Landschaft
Fribourg
309
Geneva
268
Glarus
79
Graubünden
62
Lucerne
183
Neuchâtel
101
Obwalden
61
St. Gallen *
625
Solothurn
120
Schwyz
15
Thurgau
93
Ticino *
642
Vaud
297
Valais
68
Zug
13
Zurich
266
Total
4158
* the cantons that were oversampled
Distribution of the obtained data Weighted data
by main and additional samples
on the
national level
Additional
Main sample
sample
219
336
444
Percentage of
the weighted
data on the
national level
10.7
54
0
7
0.2
15
0
10
0.2
233
0
482
11.6
99
0
182
4.4
309
268
79
62
183
101
61
103
120
15
93
196
297
68
13
266
2854
0
0
0
0
0
0
0
522
0
0
0
446
0
0
0
0
1304
180
231
21
66
225
95
7
268
130
27
143
219
634
119
19
647
4158
4.3
5.6
0.5
1.6
5.4
2.3
0.2
6.4
3.1
0.6
3.4
5.3
15.3
2.9
0.5
15.6
100.0
238
1. Attachement 1 304.
Population in Switzerland
Population of secondary school
students per canton (in %,
General population per canton (in %) 2010/2011 academic year)
Aargau
7.8
8.1
Appenzell A.
0.7
0.8
Appenzell I.
0.2
0.3
Basel-Land
3.5
3.3
Basel-Stadt
2.4
1.9
Bern
12.4
11.7
Fribourg
3.5
4.1
Geneva
5.8
6.2
Glarus
0.5
0.5
Graubünden
2.4
2.3
Jura
0.9
1.0
Lucerne
4.8
5.3
Neuchâtel
2.2
2.3
Nidwalden
0.5
0.5
Obwalden
0.5
0.5
Schaffhausen
1.0
1.0
Schwyz
1.9
2.0
Solothurn
3.2
3.2
St. Gallen
6.1
6.6
Thurgau
3.2
3.8
Ticino
4.2
3.4
Uri
0.4
0.5
Valais
4.0
9.4
Vaud
9.1
4.0
Zug
1.4
1.4
Zurich
17.4
15.9
304
ObligatorischeSchule.
Schweiz.http://www.bfs.admin.ch/bfs/portal/de/index/themen/15/03/key/blank/obligatorische_r/schuelerinnen_und.
html
239
240
2. Attachment 2
List of cantons that participate in the survey
AG
AI
AR
BE
BL
BS
FR
GE
GL
GR
LU
NE
OW
SG
SO
SZ
TG
TI
VD
VS
ZG
ZH
Total
Frequency (number
of classes)
16
3
1
23
6
5
18
25
5
4
10
5
2
6
12
3
9
10
22
14
4
16
219
%
7.4
1.4
0.5
10.6
2.8
0.9
8.3
11.6
2.3
1.9
4.6
2.3
0.9
2.8
5.6
1.4
4.2
4.6
10.2
6.5
1.9
7.4
100
Cantons that do not participate in the survey: JU, NW, SH, UR
241
3. Attachment 3
Schools and classes. National sample
Kanton Town
(Gemeindename)
School name (Bildungsinstitution)
Grade Clas
s
N
AG
Aarau
AG
AG
Aarburg
Baden
AG
Dottikon
AG
AG
Fahrwangen
Möhlin
AG
Neuenhof
1
2
3
4
5
6
Oberstufenschulhaus Schachen,
Aarau
Oberstufe Paradiesli, Aarburg
Bezirksschule Burghalde,
Baden
Oberstufenschulhaus Risi,
Dottikon
Schulanlage, Fahrwangen
Oberstufe, Möhlin
7
8
Real, Sekundar,
Berufswahlschule, Kleinklasse
der Orientierungsschule,
Neuenhof
9
AG
Oberentfelden
10
Oberstufenschulhaus,
Oberentfelden
11
12
AG
AG
Othmarsingen
Wohlen (AG)
13
Schulanlage, Othmarsingen
Oberstufe Bünzmatt 2, Wohlen
(AG)
14
15
16
AI
Appenzell
17
Sekundarschulhaus Hofwies 1 +
2, Appenzell
18
19
20
21
22
AR
BE
BE
Speicher
Aarberg
Aarwangen
Schulhaus Zentral, Speicher
Real-/Sekundarschule Aarberg
Volksschule Aarwangen
BE
Aeschi bei
Spiez
Belp
Oberstufenschule Aeschi bei
Spiez
Volksschule Belp Oberstufe
23
24
25
26
27
28
BE
Number
of classes
in the
concrete
school
7
A
1
9
7
A
G
1
1
8
B
1
7
8
8
8
B
D
C
F
1
2
9
7
F
B
2
8
9
7
B
B
A
1
4
8
9
9
8
D
B
E
B
3
8
9
7
9
7
8
8
9
9
8
E
C
A
A
A
G
C
G
B
B
8
E
2
1
1
5
1
1
242
29
30
31
BE
BE
BE
BE
Bern
Neue Mittelschule, Bern
Bern
Biel/Bienne
Bern Munzinger
Ecole secondaire Châtelet,
Biel/Bienne
32
33
BE
Biglen
BE
BE
Köniz
Halse bei
Burgdorf,
Rüegsau
BE
Sumiswald
Sekundar- und Realschule
Biglen
Schule Niederwangen
Sekundarstufe I Rüegsau.
Gemeindeverband
Sekundarschule - HasleRüegsau, Hasle bei Burgdorf
Schulen Sumiswald-Wasen
BE
Tavannes
Ecolesecondaire, Tavannes
BL
Wattenwil
Liestal
BL
Münchenstein
OSZ Wattenwil
Sekundarschulhaus Burg,
Liestal
Sekundarschulhaus Lärchen,
Münchenstein
34
35
36
37
38
39
40
41
42
43
44
45
46
47
BL
Pratteln
BL
BS
Zwingen
Basel
BS
Basel
BS
Basel
BS
Basel
BS
Basel
FR
Avry
48
49
50
51
52
53
54
55
Sekundarschulhaus Erlimatt 1 +
2, Pratteln
Sekundarschulhaus, Zwingen
Orientierungsschule Isaak
Iselin, Basel
Weiterbildungsschule Holbein,
Basel
Gymnasium am Mümsterplatz,
Basel
Orientierungsschule
Gundeldingen, Basel
Gymnasium Kirschgarten,
Basel
Ecole du CO de Sarine Ouest,
Avry
56
FR
57
Bulle
Ecole du cycle d'orientation de
la Gruyère, Bulle
7
9
7
7
A
A
C
B
2
9
8
C
B
1
9
7
B
A
1
1
8
8
8
9
8
9
7
7
A
C
E
C
A
B
A
B
4
7
C
3
8
9
8
F
E
C
1
9
8
D
B
1
1
8
A
1
7
B
1
8
B
1
7
F
1
7
A
2
8
7
A
F
3
1
2
2
1
1
243
58
59
FR
60
Estavayer-le-La Cycle d'orientation de la Broye
- Route de la Chapelle 31,
Estavayer-le-Lac
61
62
FR
Freiburg
63
Cycle d'orientation du Belluard
- Derrière-les-Remparts 9,
Fribourg
64
65
FR
Freiburg
66
Cycle d'orientation de Pérolles Pérolles 68, Fribourg
67
FR
Kerzers
FR
Murten
68
69
Orientierungsschule Schulhausstrasse 11, Kerzers
Centrescolaire/Schulzentrum
Prehl, Murten
70
71
72
GE
Carouge (GE)
73
Cycle d'orientation, Carouge
(GE)
74
75
GE
76
GE
ChêneBougeries
Chêne-Bourg
77
Cycle d'orientation, ChêneBougeries
Cycle d'orientation, ChêneBourg
78
79
GE
80
CollongeBellerive
Cycle d'orientation, CollongeBellerive
81
82
GE
Confignon
Cycle d'orientation, Confignon
GE
Lancy
Institut Florimont, Lancy
GE
Lancy
Cycle d'orientation, Lancy
83
84
85
86
87
88
89
90
8
9
7
J
J
E
3
7
9
7
F
D
K
3
8
8
7
D
K
C
2
9
9
A
D
1
8
D
4
9
9
9
7
A
C
D
H
3
8
9
7
F
E
B
1
8
D
3
9
9
7
A
D
I
2
9
8
9
9
7
9
7
8
8
9
E
I
D
E
B
E
I
E
D
I
3
2
5
244
91
92
GE
Onex
Cycle d'orientation, Onex
GE
Thônex
GE
Vernier
GE
GL
Versoix
Glarus
Privésecondaireinférieur,
Thônex
Privésecondaireinférieur,
Vernier
Collège du Léman, Versoix
Oberstufenschulkreis Glarner
Mittelland - Schulhaus
Buchholz, Glarus
93
94
95
96
97
98
99
100
101
102
103
GR
GR
Chur
Paspels
104
Schulhaus Quader, Chur
Oberstufe - Kreisschulen
Domleschg, Paspels
105
GR
Vaz/Obervaz
LU
Entlebuch
106
107
Schulhaus Lenzerheide/Lai,
Vaz/Obervaz
Oberstufenschulhaus
Entlebuch
108
109
LU
Hochdorf
Kantonsschule Seetal, Hochdorf
LU
LU
LU
Luzern
Malters
Nebikon
SH Staffeln Littau
SH Muoshof 3
Oberstufenschulhaus Nebikon
LU
Sursee
Kantonsschule, Sursee
NE
Colombier
(NE)
La Chaux-deFonds
CESCOLE, Colombier (NE)
110
111
112
113
114
115
116
117
NE
118
ESCF Les Forges, La Chauxde-Fonds
119
NE
120
121
122
123
NE
OW
La Chaux-deFonds
Le Landeron
Engelberg
ESCF Les Crêtets-Bellevue, La
Chaux-de-Fonds
ESRN C2T, Le Landeron
Stiftsschule (Sekundar),
Engelberg
9
8
9
9
7
J
C
C
D
A
7
A
1
7
7
G
D
1
5
7
8
9
9
7
8
B
D
C
D
A
B
1
2
9
7
A
A
1
7
A
2
9
7
8
7
9
7
8
8
9
8
A
B
A
C
F
B
A
C
D
F
7
B
2
9
8
D
D
1
8
7
B
A
1
2
9
B
3
1
2
1
1
2
2
1
245
SG
124
125
SG
SG
126
SG
127
SG
128
SG
129
SO
130
Altstätten
Oberstufenschulhaus Feld II,
Altstätten
Buchs
Oberstufenzentrum Grof, Buchs
Neckertal
Oberstufenschulhaus NeckerMogelsberg, Neckertal
Quarten
Oberstufenschulhaus
Unterterzen, Quarten
RapperswilOberstufenschulhaus WeidenJona
Jona, Rapperswil-Jona
Rorschacherber Schulhaus Steig,
g
Rorschacherberg
Derendingen
Kreisschule Wasseramt Ost Oberstufenschulzentrum
Derendingen/Luterbach ,
Derendingen
131
132
133
134
135
SO
Egerkingen
SO
Grenchen
SO
Grenchen
136
137
138
Kreisschule Gäu Sekundarschule Mühlematt,
Egerkingen
Schulhaus an der Halde,
Grenchen
Bezirkschule - Schulhaus III,
Grenchen
139
140
SO
Matzendorf
SZ
Einsiedeln
SZ
Schwyz
141
142
143
Kreisschule Thal - Bezirk- und
Sekundarschule, Matzendorf
Schuleinheit Team 7 - 9,
Einsiedeln
Schulhaus Rubiswil - Ibach,
Schwyz
144
145
TG
Affeltrangen
Affeltrangen SSG
TG
TG
Frauenfeld SSG Reutenen
Kemmental
OSA
VSG
146
147
148
149
TG
150
Sulgen SSG
Oberstufenzentrum Befang,
Sulgen
8
A
1
9
7
B
B
1
1
9
A
1
8
A
1
9
B
1
8
B
6
8
8
9
9
9
9
E
A
G
E
B
A
1
8
C
1
7
A
3
8
8
8
F
C
B
1
7
B
1
8
A
2
9
7
8
9
7
A
A
B
A
D
8
8
B
B
2
1
2
1
246
TG
Wängi
TG
Weitenzelg
TI
TI
Ascona 6613
CollegioPapio
Bironico CP 36 Scuolamedia di Camignolo
- 6804
151
152
OberstufenshausImbach II,
Wängi
Romanshorn-Salmsach SSG
153
154
155
156
157
158
TI
TI
TI
159
Castione 6532
Gordola 6536
Pregassona
(Lugano)
6963 Via
Terzerina
Scuolamedia di Castione
Scuolamedia di Gordola
Scuola media di Pregassona.
Preganossa (Lugano)
160
161
TI
162
TI
163
VD
164
Riva S. Vitale Scuola media di Riva S. Vitale
6834
Via alla Roggia Scuolamedia Parsifal
–
6924 Sorengo
Aigle
Collège des Dents du Midi,
Aigle
165
166
VD
Aubonne
Collège du Chêne, Aubonne
VD
Avenches
Collège du Château, Avenches
VD
VD
Bussigny-prèsLausanne
Lausanne
VD
VD
Lausanne
Le Chenit
VD
VD
Lutry
Morges
Tombay II, Bussigny-prèsLausanne
Ecole Nouvelle de la Suisse
romande, Lausanne
La Garanderie, Lausanne
Chez-le-Maître-Le Sentier, Le
Chenit
Collège des Pâles 2, Lutry
Collège de Chanel, Morges
VD
Orbe
Montchoisi, Orbe
VD
Oron-la-Ville
Collège, Oron-la-Ville
VD
Pully
Collège des Alpes, Pully
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
8
A
1
7
8
8
8
A
A
B
E
2
9
8
8
7
B
B
C
C
1
1
3
7
9
8
B
C
B
1
9
B
1
7
B
2
9
8
9
7
7
7
G
A
E
A
B
C
8
A
1
8
9
A
B
1
1
9
7
8
7
9
7
8
9
7
A
A
D
C
E
C
E
C
C
1
2
1
2
2
2
1
2
3
3
247
183
184
185
VD
VS
Vevey
Brig-Glis
186
Collège Bleu, Vevey
Kollegium Spiritus Sanctus,
Brig-Glis
187
188
VS
Monthey
189
Cycle d'orientation CO Reposieux, Monthey
190
191
VS
VS
MünsterGeschinen
Nendaz
VS
Sierre
VS
Sion
Orientierungsschule OS,
Münster-Geschinen
Cycle d'orientation CO - BasseNendaz, Nendaz
Cycle d'orientation CO Goubing, Sierre
Les Creusets, Sion
ZG
ZG
Menzingen
Zug
Ochsenmatt II, Menzingen
Kantonsschule, Zug
ZH
Schulhaus Ennetgraben
ZH
Affoltern am
Albis
Dübendorf
ZH
ZH
Meilen
Nürensdorf
Schulhaus Sekundar Allmend
Schulhaus Hatzenbühl
ZH
ZH
ZH
ZH
Richterswil
Seuzach
Wald ZH
Wetzikon
ZH
ZH
ZH
ZH
ZH
Zürich
Zürich
Zürich
Zürich
Zürich
Schulhaus Boden
Schulhaus Halden
Schulhaus Burg
Schulhaus Sekundarschule
Walenbach
Schulhaus Aemtler B
Schulhaus Hirschengraben
Schulhaus Leutschenbach
Kantonsschule Stadelhofen
Kantonsschule Enge
192
193
194
195
196
197
198
199
200
201
202
203
204
205
Kantonsschule Glattal
206
207
208
209
210
211
212
213
214
215
216
217
218
219
8
9
8
7
B
C
C
A
1
3
8
9
7
J
I
C
3
8
9
9
F
D
A
1
7
C
1
9
E
1
7
8
8
9
9
8
7
8
9
7
J
J
B
I
D
B
J
J
I
B
5
7
9
9
8
9
8
7
9
7
B
D
B
A
B
B
B
A
A
2
7
8
9
9
9
9
A
B
A
A
E
J
1
1
1
1
2
1
3
1
1
2
1
1
1
1
248
Classes and Schools
Number of classes per
school
Valid
1.00
2.00
3.00
4.00
5.00
6.00
Total
Frequency
of schools
73
30
16
3
4
1
127
Percent
33.3
13.7
7.3
1.4
1.8
.5
58.0
Valid percent
57.5
23.6
12.6
2.4
3.1
.8
100.0
Cummulated
Percent
57.5
81.1
93.7
96.1
99.2
100.0
249
4. Attachment 4.
Additional samples in Aargau (AG), St. Gallen (SG) and Ticino (TI)
AG
11 Schulen
17 Klassen
N
1
2
ort
Aarau
Berikon
Schule
Bezirksschule Zelgli, Aarau
Kreisschule Mutschellen - KSM 3, Berikon
Döttingen
Frick
Oberstufe, Döttingen
Oberstufenzentrum, Frick
Muri (AG)
Bezirksschule, Muri (AG)
Niederlenz
Schinznach-Dorf
Schulanlage, Niederlenz
Bezirksschule, Schinznach Dorf
Spreitenbach
Villmergen
Bezirksschule, Spreitenbach
Schulhaus Hof, Villmergen
Wohlen (AG)
Würenlingen
Primarschule und Oberstufe - Bünzmatt 3, Wohlen
(AG)
9b
Schulhaus Dorf 1968, Würenlingen
8b
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Klasse
8f
8a
8b
9a
Sekudarschule 8d
Realschule 9b
7b
7c
8b
9b
7b
9b
8c
7b
8d
SG
12 Schulen
26 Klassen
N
1
2
Ort
Amden
Bronschhofen
Schule
Realschule Amden-Weesen, Amden
Oberstufenschulhaus, Bronsschhofen
Diepoldsau
Ebnat-Kappel
Flawil
Oberstufenzentrum Kleewies, Diepoldsau
Oberstufenschulhaus Wier, Ebnat-Kappel
Oberstufenzentrum Feld, Flawil
Goldach
Jonschwil
Mels
Oberstufenschulhaus, Goldach
Oberstufenzentrum Degenau, Jonschwil
Oberstufenschulhaus Feldacker, Mels
3
4
5
6
7
8
9
10
11
12
Klasse
7a
7c
8a
7b
8a
7d
8c
9c
3fReal
8b
7a
7f
250
13
14
15
St. Gallen
Kantonsschule Am Burggraben, St. Gallen
16
17
18
19
Weesen
Widnau
Sekundarschule Weesen-Amden, Weesen
Oberstufenschulhaus Gässeli, Widnau
Wil (SG)
Privatschule Dominik Savio, Wil (SG)
20
21
22
23
24
25
26
8a
8c
7a
9b
7b
Sekundarschule, 3 Kl
(9Oberstufe)
7a
7e
8a
8b
8c
8d
9d
8a
TI
14 Schulen
22 Klassen
N
1
Ort
Agno
Schule
Agno
Bedigliora
Bellinzona
Bedigliora
Scuolaelementis&media, Bellinzona
Cadenazzo
Capriasca
Giornico
Cadenazzo
Tesserete
Giornico
Giubiasco
Scuolaelementis&media, Giubiasco
Gravesano
Locarno
Gravesano
Scuolaelementis&media, Locarno
Losone
Mendrisio
Minusio
Losone
Scuolaelementis&media, Mendrisio
Scuolaelementis&media, Minusio
Origlio
Quinto
Origlio
Quinto
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Klasse
7b
8c
8c
8b
9f
9a
7d
8b
9a
7a
9g
7a
7c
7j
8d
9d
8b
8a
8d
9c
7a
9a
251
5. Attachment 5.
-
-
-
Example of the letter to school principal (File “Letter_School_Principal_Example”.
Folder “Attachment 5”)
Attachment totheletter N1 “Beilage 1 Zusammenfassung Studie“ (File „Beilage 1
Zusammenfassung Studie“.
Folder „Attachment 5“)
Attachment totheletterN2 “Instruktionen für die Durchführung der Befragung im
Klassenverband“ (File „Beilage_2_Instruktion“.
Attachment totheletterN3 „An die Eltern der Schülerinnen und Schüler der ausgewählten
Schulklassen“ (File “ Beilage_3_Orientierungsschreiben“.
6. Attachment 6.
-
Questionnaire for teachers (File „Feedback-Fragebogen für Lehrer“.
7. Attachments 7.1-7.3.
-
The questionnaire in German, French and Italian (files “Questionnaire German”,
“Questionnaire French”, “Questionnaire Italian”.
Folder “Attachment 7.1-7.3”)
8. Attachment 8.
-
Email „Schweizerische Konferenz der kantonalen Erziehungsdirektoren“
(File „ISRD3.Brief.Information.EDK“.
Folder „Attachment 8“).
9. Attachment 9.
-
Example of the letter to cantons (File “Bildungsdirektion_Brief_Beispiel”.
“Research plan”. Attachment to the letter in German, French and Italian (Files
“ISRD3.Research.Plan_DE”, “ISRD3.Research.Plan_DE”, “ISRD3.Research.Plan_DE”.
252

The Third International Self-report Study of Delinquency among

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