Flexible workers: how about their distractions and concentration?

Transcription

Master Thesis Human Resource Studies
Flexible workers: how about their
distractions and concentration?
A quantitative study in a general New Way of Working setting
I.M. Molendijk, BSc.
Anr: 885367
Supervisor: Prof. Dr. M.J.P.M. van Veldhoven
Second assessor: Dr. T.A.M. Kooij
Project Period: January 2011 – September 2011
Project theme: Get the balance right
Master Thesis Human Resource Studies ｜ Irene Molendijk
Table of Contents
Abstract ............................................................................................................................................................................... 4
1.
Introduction .............................................................................................................................................................. 5
2.
Theoretical Framework ......................................................................................................................................... 7
3.
2.1.
Concentration on work tasks .......................................................................................................................... 7
2.2.
Distractions........................................................................................................................................................ 8
2.3.
Personal characteristic of flexibility ............................................................................................................... 9
Method ..................................................................................................................................................................... 12
3.1.
Research context ............................................................................................................................................. 12
3.2.
Procedures ....................................................................................................................................................... 12
3.3.
Description of the sample ............................................................................................................................. 13
3.4.
Instruments...................................................................................................................................................... 14
3.4.1. Diary ................................................................................................................................................................. 14
3.4.2. General Questionnaire ................................................................................................................................... 17
4.
5.
3.5.
Control Variables ............................................................................................................................................ 18
3.6.
Quality of the data .......................................................................................................................................... 19
3.7.
Statistical analysis ............................................................................................................................................ 20
Results ...................................................................................................................................................................... 21
4.1.
Variable differences between Home Days and Office Days ................................................................... 21
4.2.
Correlations ..................................................................................................................................................... 23
4.3.
Sequential multiple regression analyses and control variables................................................................. 29
4.4.
Hierarchical multiple regression analysis Home Day 1 ............................................................................ 29
4.5.
Hierarchical multiple regression analysis Home Day 2 ............................................................................ 31
4.6.
Hierarchical multiple regression analysis Office Day 1 ............................................................................ 33
4.7.
Hierarchical multiple regression analysis Office Day 2 ............................................................................ 34
4.8.
Additional analysis on the interaction effects for both Home Days and both Office Days .............. 36
Conclusion and Discussion ............................................................................................................................... 39
5.1.
Conclusion ....................................................................................................................................................... 39
5.2.
Discussion of the findings............................................................................................................................. 41
5.3.
Limitations and implications for further research ..................................................................................... 43
5.4.
Practical implications ..................................................................................................................................... 45
2
References ........................................................................................................................................................................ 47
Appendix I. General questionnaire and daily diary.................................................................................................... 51
Appendix II. Factor analysis.......................................................................................................................................... 58
Appendix III. Exclusion of control variable Age ...................................................................................................... 72
Appendix IV. Results of two-way ANOVA tests for each day separately............................................................. 74
Appendix V. (Non-) significant results of the independent-samples t-test for equality of means ..................... 78
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Abstract
The New Way of Working: a notable new-fashioned arrangement in which work is
increasingly disconnected from traditional office space and buildings and employees are allowed to
perform their work in more convenient or suitable places. The aim of this research was to
investigate which kind of working days (home- or office days) seem to be more effective in relation
to concentration on work tasks, work-related distractions and non-work-related distractions and in
which way these variables interdepently cohere. A booklet which contained a general questionnaire
and six daily questionnaires was answered by 120 respondents working in a general New Way of
Working setting. Analyses were conducted at two office days and two home-days and indicated that
non-work-related distractions have a higher negative impact on concentration on work tasks than
work-related distractions do. Moreover, the personal characteristic of flexibility moderated for home
day 1 the relationship between work- and non-work-related distractions on concentration on work
tasks. This indicated that respondents who scored high on the personal characteristic flexibility,
made the direct negative relationship between distractions and concentration on work tasks less
negative. Future research should examine the above stated relationships with a bigger and more
diverse sample and should consider multilevel research, because in such a way statements can be
made about within-person effects.
Key words: The New Way of Working, concentration on work tasks, work-related distractions, nonwork-related distractions, personal flexibility.
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1.
Introduction
Psychological literature shows that enhanced concentration on work tasks leads to higher levels of
performance (Demerouti, Taris & Bakker, 2007; Lieberman et al., 2006; Van der Linden, Keijsers,
Eling & Van Schaijk, 2005). Nevertheless, recent research by Jurofoon (2011) showed that nearly
70% of the Dutch employees experience concentration problems due to loud-talking colleagues,
noise due to devices and outside noise (http://www.fmm.nl/nieuws/nieuws/hard-pratende-collegas-zorgen-voor.73828.lynkx). As Jett & George (2003) explain in their research about interruptions in
organizational life, the physical and psychological work environment can foster interruptions.
Nowadays informal work climates and open office layouts are a trend and are designed to promote
flexibility, space, and bring people closer together. However this also increases the likelihood of
unscheduled interactions with others, which consumes time that could be spent on critical tasks and
leaves a person with insufficient time to meet a deadline, achieve a goal or simply complete a task
(Breuer, 1995). Breuer (1995) therefore notices that distractions in the workplace are problematic, as
they may affect productivity in the end.
At the moment, new information and communication technology at the office and at home
has made organizations less dependent on time and space demands. Work is increasingly
disconnected from traditional office space and buildings and employees are allowed to perform their
work in more convenient or suitable places (Baane, Houtkamp & Knotter, 2010; Vittersø, Akselsen,
Evjemo, Julsrud, Yttri & Bergvik, 2003). This New Way of Working is a vision to make work more
effective, efficient, but also more pleasant for both the organization as well as the employee (Bijl,
2009). This vision can be realized by giving the space and freedom needed for an employee to let
him determine how, where and when he works, and with what attributes and with whom (Bijl, 2009).
Research state that the home environment fosters better concentration than the office
(Montreuil & Lippel, 2002; Van Sell & Jacobs, 1994). For work-related distractions this would seem
to be logical, because fewer work interruptions are likely to take place. However, when considering
non-work related distractions, this phenomenon on concentration on work tasks can be considered
as being doubtful. Sullivan & Lewis (2001) showed that when people had the opportunity to work
from home they often had the tendency to combine work and non-work tasks. Whether this is
beneficial to obtain high concentration levels can be questionable. Another aspect towards home
telework that might be considered is whether concentration is more likely to happen if the number
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of hours an employee is working at home are increasing. In literature, telework is frequently
measured as a dichotomous variable, whereby the number of the exact hours or even days an
employee is working is becoming guessable. Pitiful, because in this way it can be that the effects of
telework are wrongly interpreted. For instance, with the New Working Practices, employees
regularly work a few hours in the morning to avoid traffic jams (Bijl, 2009). During these hours they
often read and respond their emails, before departing to the office (Baane, Houtkamp & Knotter,
2010; Bijl, 2009). This is an activity which mostly does not require a high level of concentration,
which is in contrast to the previously mentioned main reason that working at home is an
arrangement whereby enhanced concentration is obvious to be reached.
Moreover, today’s dynamic organizations are in need of a workforce that is able to adapt to
change(s) (Griffin & Hesketh, 2005; Pulakos, Arad, Donovan & Plamondon, 2000). For individuals
it is often hard to stay self-disciplined and continue a task without yielding to changes such as
distractions. Therefore this research will also take the personal characteristic of flexibility into
account to see if this will buffer the relationship between work-related and non-work-related
distractions and concentration. It is hypothesized that personal flexibility will benefit an individual to
react properly to these types of distractions, which in turn makes it possible for individuals to
achieve an optimal level of concentration to accomplish the work task at hand.
As can be seen from the preceding introduction, flexible work arrangements, such as The
New Way of Working, are becoming increasingly interesting for both employers as employees in the
present quick information gaining Twenty-Four-Hour Society of the 21st century. Therefore, the aim
of this research is to contribute to the current literature in this field by examining the relationship
between working days at home and working days at the office and concentration, with the extra
dimension of distractions in this relationship and the moderating variable flexibility, which can
probably buffer the relationship between work- and non-work-related distractions on concentration.
From a practical point of view, the aim of this research is to give organizations insight in the
efficiency of which kind of days (home- or office days) seem to be more effective in relation to
concentration. Also the uniqueness of non-work-related distractions and work-related distractions in
combination with concentration will be highlighted. The research question of this study therefore
implies:
To what extent do work- and non-work-related distractions influence an employee’s concentration on work tasks?
Furthermore, does the personal characteristic flexibility make a difference in this respect?
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Next, the theoretical framework of this study will include definitions of the previously
mentioned variables and will deepen the understanding of the relationships between the main
concepts by the use of scientific theory and empirical articles. Also the differences between these
variables between home days and office days will result in another explorative question, which is
stated at the end of the theoretical framework. The method section will provide insight into how the
conceptual model shall be tested and furthermore how the variables are operationalized.
2.
Theoretical Framework
2.1.
Concentration on work tasks
For years, the boundaries between work and home have mostly been separated. However, with the
advent of flexible work arrangements, the boundaries inevitably shifted from separating home and
work to a way of integrating home and work (Nippert-Eng, 1996). Nevertheless, with this shift it is
recognized that individuals may be actively participating in one role while simultaneously feeling
distracted by thoughts, emotions or demands that belong to another role (Cardenas, Major & Bernas,
2004; Ashforth, Kreiner & Fugate, 2000; Nippert-Eng, 1996). Ultimately, such distractions will
reduce performance efficiency and an effective possibility to enhance this performance is by taskrelevant concentration (Demerouti, Taris & Bakker, 2007). Overall, concentration has to do with an
individual’s ability to direct thinking in whatever direction this individual would intend.
Many forms of work involve individual cognitive activities, which require long periods of
uninterrupted time during which one can concentrate (Perlow, 1999). This also applies for
employees working under The New Working Conditions, which imply high levels of autonomy,
being managed by objectives, and mostly facing strict deadlines (Peters, den Dulk & van der Lippe,
2009). Therefore, it can be said that working under such conditions requires a high absorptive ability,
or in other words, an uninterrupted concentration, of an individual (Carsky, Dolan & Free, 1991).
In several studies it states that working at home enhances the ability to concentrate on work
for most individuals, if not all (Montreuil & Lippel, 2002; Vittersø et al., 2003; Van Sell & Jacobs,
1994). Findings suggest that the home environment fosters better concentration than the office,
where noise, regular interruptions, open-space lay-out and dubious air quality have a negative impact
on employees (Montreuil & Lippel, 2002). Moreover, Peters and Wildebeest (2010) notice that
telework can be seen as a resource and therefore a positive relationship between telework and
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positive work outcomes will exist. Peters and Wildebeest (2010) also emphasize the importance of
the amount of teleworking. In their research on telework, flow and exhaustion, they found that
substantial teleworking, or differently said working more than one day per week at home,
significantly increases the amount of flow at work tasks. Flow consists of absorption, job satisfaction
and intrinsic motivation. Whereas this first term, absorption, refers to a mental condition of full
concentration.
Taken together, these previously mentioned researches (Peters and Wildebeest (2010);
Montreuil & Lippel, 2002; Vittersø et al., 2003; Van Sell & Jacobs, 1994) conclude that working
from home results in higher concentration levels, whereas working at the office results in lower
concentration levels. Despite this conclusion, this research expects something quite different.
Today’s society is namely all about flexibility, multitasking, being available preferably twenty-fourhours a day, which makes it impossible to be or stay fully concentrated on work tasks. Also, the
location from which an employee works seems to be irrelevant, because quick (online) messages,
phone calls or online meetings are a common used method to gather relevant information. It is
certainly possible that therefore the efficiency will decrease, whereas the likelihood of errors will
increase. However, this seems to be irrelevant to organizations (http://www.gezondweb.be/
gezondweb/rubrieken/ziekteaandoeningen/zenuwstelsel/concentreren/wat-is-concentratie.htm).
Therefore, in this study it is expected that the level of concentration on work tasks for
employees working at the office and for employees working at home is not that different from each
other as is investigated by previous research.
2.2.
Distractions
Distractions are defined as psychological reactions triggered by external stimuli or alternative
activities that interrupt focused concentration on a primary task (Jett & George, 2003). Distractions
are generally encouraged by competing activities or environmental stimuli that are irrelevant to the
relevant task and they affect a person's cognitive processes by diverting attention that might
otherwise have been directed to that task (Jett & George, 2003). Therefore, distractions consume
time that could be spent on critical tasks, and these distractions can leave a person with insufficient
time to meet a deadline, achieve a goal, or simply complete a task (Jett & George, 2003). As a
consequence, distractions are often regarded as annoying and frustrating, because they keep
employees from their work. However, according to Zijlstra, Roe, Leonarda and Krediet (1999),
distractions can also be seen as welcome distracters in boring and monotonous work tasks.
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For an employee it is possible that while having a family dinner, he or she may get a call
from a coworker or simply be distracted by thinking about a work project while having this family
dinner (Cardenas et al., 2004). As can be seen by this example, distractions can be both behavioral
(f.i. intrusions) and/ or psychological (f.i. thoughts; Jett & George, 2003). Therefore in this research,
both behavioral and psychological distractions will be taken into account.
Disagreements in literature exist about the effectiveness of working at home to attain the
most optimal level of concentration. Some research notice that when an employee is conducting
work at home on one or more days per week, better concentration is likely to happen (Vittersø et al.,
(2003); Montreuil & Lippel, 2002; Van Sell & Jacobs, 1994). According to Van Sell and Jacobs (1994)
this is explainable, because fewer work-related interruptions will occur at home, which causes this
improved concentration. However, Sullivan & Lewis (2001) also explain that distractions at home
while working will occur in a different way, namely due to non-work-related distractions, such as
children running around, unexpected visitors coming over, and doing household chores.
Deliberately combining work tasks with such non-work tasks seems a common strategy for
teleworkers (Sullivan & Lewis, 2001) and because of this, obtaining absolute concentration is almost
unthinkable. Therefore, it can be concluded that non-work-related distractions are more common to
occur in the home environment, whereas work-related distractions seems to occur more frequently
in the office domain.
In sum it seems that distractions, in whatever form they may be, result in negative
consequences for an individual. This is especially the case when work is complex, demanding,
requires learning and an individual’s full attention (Jett & George, 2003). As stated earlier, this is
often the case for an employee working under the New Working conditions.
The hypotheses concerning work-related and non-work-related distractions therefore state:
H1: The more work-related distractions an employee experiences, the less concentration on work tasks this employee
will experience.
H2: The more non-work-related distractions an employee experiences, the less concentration on work tasks this
employee will experience.
2.3.
Personal characteristic of flexibility
Personal flexibility can be described as the ability to cope quickly with changing circumstances or
environmental uncertainty (Gupta & Goyal, 1989). Moreover, there is a strong link between
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flexibility and adaptability (Karuppan, 2004). Individuals who perform well in a changing task
context are namely said to be highly adaptable, whereas those who do not perform well in a
changing context are considered to have low adaptability (Le Pine, Colquitt & Erez, 2000). As a
consequence, one can argue that human beings are unique in their adaptability or their ability to find
routes toward desired ends (Kashdan & Rottenberg, 2010). Therefore in this research, because of
the overlap in the preceding definitions, both personal flexibility and adaptability will be used
interchangeably.
It can be said that telework is not appropriate for all employees (Lamond, Daniels & Standen,
2003). Generic task competencies may namely be highly influential in adaptation to telework, which
among others include a persons’ level of flexibility towards tasks, time management skills and the
ability to take independent decisions (Lamond, Daniels & Standen, 2003). Therefore, when a
teleworker is being distracted by work-related- or non-work-related issues, it is crucial to react
flexible, and adapt to the situation the best way possible. This is also confirmed by Jett and George
(2003), who state that the level of flexibility, or its counterpart rigidity, can affect an individual’s
response to distractions. For example, when a person is facing a rise in job demands, this persons’
coping skills are likely to stretch, which in turn can lead to reduces in personal adaptability
(O’Connell, McNeely & Hall, 2008). As individual adaptability has numerously been indicated as a
factor for organizational success (Le Pine et al., 2000), it must be clear that being flexible and
adaptable is an important facet.
For an employee each work task has an optimum to perform the task most optimally. The
body mobilizes energy to let the employee focus and concentrate to perform this task (Gaillard,
2003). Because an individual is not capable of staying highly concentrated all the time, this person
can take independent decisions to adapt to distractions or not. As previously mentioned, Zijlstra,
Roe, Leonarda and Krediet (1999) state that distractions can also be seen as welcome interruptions
of the task at hand. This can be the case when an employee is not longer highly concentrated on the
work task and a distraction therefore can be considered as a nice break to momentary escape the
work situation. Therefore it is hypothesized that:
H3: The personal characteristic flexibility will buffer the relationship between work-related distractions and
concentration on work tasks.
H4: The personal characteristic flexibility will buffer the relationship between non-work-related distractions and
concentration on work tasks.
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The conceptual model to be tested in this research, as derived from the preceding four hypotheses,
is shown in figure 1. This model will be examined on ‘home days’, being the two days employees
worked most of the time at home, and on ‘office days’ , which refers to two days employees worked
most of the time at the office. Furthermore, as derived from the preceding theory in which it was
stated that in this study it is expected that concentration on work tasks will be more or less the same
on home days and office days, work-related distractions will be higher for office days than for home
days and lastly non-work-related distractions will be higher for home days than for office days, it is
of interest to explore the following question:
To what extent does the level of concentration on work tasks and the level of work-related and non-work-related
distractions vary between home days and office days?
The research question and the added above stated explorative question will be answered in the
conclusion section, after all analyses have been conducted.
Personal
Flexibility
Work-Distractions
-
Concentration
on work tasks
Non-Work Distractions
-
Figure 1. Conceptual Model
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3.
Method
3.1.
Research context
With the aim to examine the aforestated four hypotheses and to give answer to the added
explorative question about home days and office day differences, a quantitative research was
conducted. Furthermore, a longitudinal design was used, because data was collected on a six-day
basis and therefore causal conclusions could be made between the days. However, for this study no
causal interpretations between the days were made and therefore the data-analysis can be considered
to be cross-sectional. The data for this research was collected at several organizations in The
Netherlands which all were familiar with The New Way of Working or which offered flexible work
arrangements such as teleworking. Moreover, data collection took place by the procedure of
snowball sampling. Connections at the abovementioned organizations were used to distribute a
general questionnaire and the six-day-diary. In this way, the sample would build up and therefore
enough useful data would be gathered for this study.
Despite the fact of using a snowball sampling procedure, this research managed to get an
approximately same amount of males and females and an equal variance of respondents in all age
groups. In this way generalizations could be made, because the amount of outliers was reduced.
The diary was kept six working days by each respondent individually, from which three days
at home and three days at the office. In this way it was possible to compare workdays from home to
each other and to workdays at the office and the other way around. The total number of
respondents that were approached for this research was 145, whereas the total number of
participants who returned the general questionnaire was 120. This therefore made the response-rate
82,7%. The amount of participants who answered the six-day-diary fluctuated, which can be seen in
table 2. Based on this, it was decided to not run regressions for home day three (n=77) and office
day three (n=103), because of the decreasing amount of respondents, compared to the other days.
Therefore only two working days from home and two working days at the office will be discussed in
this study.
3.2.
Procedures
The diary and the general questionnaire were combined in a booklet in which also a brief
introduction to the research was given. Moreover, the diary and the questionnaire for the
respondents was set up in Dutch. In this way no translations of the Dutch scales had to be
considered and therefore no misinterpretations in a different language have occurred. The contact
12
person of every organization received a letter with an explanation and procedure of the study. To
this person it was asked to contribute and distribute the diary and questionnaire among other suited
employees. In the letter to the contact person also the importance of confidentiality was emphasized.
Respondents could hand in the booklet in a closed envelope and put it in a common, beforehand
postmarked, envelope, which after a few weeks was send by the contact person to the researcher.
Furthermore, to all respondents clarity was given about when, or differently said, at what time of the
day, the diary should be filled in. Because of the fact that a working day under The New Way of
Working conditions could also end at other times than a normal working day from nine till five, the
best suitable option for all respondents was to fill in the diary one hour before going to sleep. Finally,
it was emphasized that there were no wrong or right answer possibilities. The booklet can be found
in Appendix I.
3.3.
Description of the sample
The participants in this research were employees working at various organizations and in different
industries across the Netherlands. All 120 respondents worked in a way that was related to The New
Way of Working conditions. There were 45% women and 55% men included in the sample. The age
of the respondents varied from 21 years till 61 years, whereas the average age was 36,1 years with a
standard deviation of 10.8. The majority of the sample population was highly educated, namely
49,2% had a university of applied sciences degree, whereas 37,5% of the population was in the
possession of an university degree. Furthermore, most of the respondents lived together with a
partner or with a partner and children (both 35%), whereas 27,5% of the respondents lived alone
and only 2,5% of the sample population lived alone with children. Of all respondents, 57,5% worked
in an operational position, 33,3% in a management position and only 9,2 % hold a board of
directors position. The average contractual hours worked by the sample population were 36.6 hours
per week, ranging from 15 hours till 40 hours a week.
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Table 1
Demographic characteristics of the sample population
Variable
Total /Mean
Men
55%
Women
45%
Average age (in years)
31,6
University
37,5%
University of applied sciences
49,2%
Operational level
57,5%
Management level
33,3%
Board of director level
9,2%
Contractual hours
36,6
N=120
3.4.
Instruments
In this study, next to a survey, also a diary method was used to look at the concepts more in
depth. In this way better understandings of the day to day experiences of the relationship between
working at home or at the office and distractions and concentration were examined. As Ohly,
Sonnentag, Niessen and Zapf (2010) state, diary methods give insight in thoughts, feelings, and
behaviors within the work context as well as characteristics of the work situation which can fluctuate
on a daily basis.
The diary consisted of three items, namely work-related distractions, non-work-related
distractions and concentration on work tasks, whereas the survey consisted one original item,
namely personal flexibility and a scale about general level of concentration on work tasks. This was
done to check for the respondents consistency in the answer-pattern in daily and general feelings of
concentration on work tasks. This will be discussed next.
3.4.1. Diary
Operationalization Working day from home and Working day from the office
The first question of the diary stated: ‘I consider this day as a: 1. A day working from home, or: 2. A
day working at the office. So in total six working days were measured with the diary, from which
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only four were used.
As explained earlier, with The New Way of Working it is of frequent occurrence that
employees work a few hours at home in the morning to avoid traffic jams. Therefore, as an
instruction respondents had to select three days they worked more than half of the working day at
home, which was considered to be a working day from home, and the other way around, namely, to
select three days they worked more than half of the working day at the office, so this was considered
to be a working day at the office. To check the hours a respondent worked at home or at the office,
the questions ‘How many hours did you work at home today’ and ‘How many hours did you work at
the office today’, were also included in the diary. The questions can be found in Appendix I.
Operationalization day-level Concentration on work tasks
Concentration was measured by four items, of which three came from the Flow State Scale by
Jackson and Marsh (1996). Originally this scale consisted of four items, but in imitation of Beard
and Hoy (2010) and Quinn (2005) the choice was made to develop a three-item concept. Reason for
this was that the study on flow by Jackson and Marsh (1996) focused mostly on sports and leisure
and thus on physical activity, whereas the studies by Beard and Hoy (2010) and Quinn (2005) were
totally focused on knowledge work and thus on intellectual activity, which also suites this research
better. Furthermore, an additional item was added, namely ‘My thoughts were wandering to other
things during the task’. This item came from the study by Demerouti, Taris and Bakker (2007) on
the critical link of concentration in the relationship between need for recovery, home-work
interference and performance, and was a reverse-coded item.
The concept of concentration measures the degree to which employees have a complete
focus upon their tasks on a seven-point Likert-type scale, anchored by 1= ‘strongly disagree’ to 7=
‘strongly agree’. Statements such as ‘My attention was focused entirely on what I was doing’ and ‘I
was completely focused on the task at hand’ had to be answered six working days on this sevenpoint Likert-type scale. Higher scores on the scale showed that respondents were more concentrated
on work tasks than respondents with lower scale scores. The study by Beard and Hoy (2010)
reported a Cronbach’s alpha of 0.792, whereas the study by Quinn reported a Cronbach’s alpha of
0.8. The study by Demerouti, Taris and Bakker (2007) reported a Cronbach’s alpha of 0.78 on time 1
and a Cronbach’s alpha of 0.83 on time 2. For this research the internal consistency of the scale had
Cronbach’s alpha’s of respectively .908 for home day one, .900 for home day two, .905 for office day
one and .892 for office day two.
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Principal factor analysis for concentration on work tasks for the two days from home and
the two days at the office showed a clear one-factor model, which declared 80,16% of the variance.
This became evident by the intial eigenvalues and the screeplot (Pallant, 2007). Furthermore, all
correlations for all days were above .3, the Kaiser-Meyer-Olkin Measure of Sampling Adequacy
(KMO) value was .824 for home day one, .815 for home day two, .815 for office day one, and .816
for office day two, whereas the Bartlett’s Test of Sphericity was significant (.00) for all days.
Therefore all statistical requirements for this scale were met (Pallant, 2007). The results of the factor
analyses can be found in Appendix II.
Operationalization day-level Work-related distractions and Non-work-related distractions
A self-designed scale has been used to measure the two types of distractions. Respondents were
asked to indicate how much they felt distracted by work-related and non-work-related distractions
on three days they worked from home and on three days they worked at the office. A starting point
for this concept was a question created by Cardenas et al. (2004), namely: ‘Estimate the total number
of hours per day you feel distracted by work thoughts or interruptions while at home or with family’.
However, as distractions are not easy to interpret in hours or even minutes, a continuous scale was
made with five answering categories. First, a short introduction to the scale was given to give the
respondent more insight in what is considered a thought and an action to work-related- and nonwork-related distractions. Second, a common question was asked, namely: ‘to what extent did you
feel distracted during your work tasks today?’ Two questions were asked about thoughts to workrelated distractions as real actions to work-related distractions. These two questions were: Today,
how much did you feel distracted by: thoughts to work tasks other than the primary task (1) and
actions to work tasks other than the primary task (2). Furthermore, two questions were asked about
thoughts to non-work-related distractions and real actions to non-work-related distractions: namely:
Today, how much did you feel distracted by: thoughts to private matters (1) and actions to private
matters (2). All five questions had to be answered on a five-point Likert-type scale, ranging from 1=
never to 5= often.
Principal factor analysis for the total distractions scale for both working days from home and
the two working days at the office showed a clear two-factor structure, which meant a clear
contradiction between the non-work related distractions and the work-related distractions
(Appendix II). For both working days from home and office day 2 the component correlation
matrix showed correlations above .3 and therefore the Oblimin rotation was reported (Pallant, 2007).
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For office day 1 the Varimax rotation was reported, because the components were correlated lower
than .3.
When conducting a separate factor analysis for work-related and non-work related
distractions, for all days the correlations in the correlation matrix were all above .3, the KMO values
were .500 and the Bartlett’s Tests of Sphericity were .00, so significant (Appendix II). The internal
consistency of the two-item scale for work-related distractions had a Cronbach’s alpha of: .680 for
home day one, .737 for home day two, .794 for office day one and .813 for office day two, whereas
the Cronbach’s alpha’s for the two-item scale of non-work-related distractions were
respectively: .894, .813, .699 and .779.
3.4.2. General Questionnaire
Operationalization personal characteristic Flexibility
Flexibility is considered to be a fixed personal characteristic of a respondent and as a consequence
will not fluctuate per day; therefore this item was measured with a survey. Personal flexibility was
measured by its counterpart, the rigidity scale, which is part of the Dutch Personality Questionnaire2 by Barelds, Luteijn, van Dijk and Starren (2007). This scale consisted of twenty items, from which
two items were reverse-coded and had a Cronbach’s alpha of 0.84. However, for this study only
eight out of the twenty items were considered to be interesting for this research. These eight items
seemed to be more in line with and relevant to feelings of distractions instead of the also measured
characteristics of appearance and being neatly.
Overall, the rigidity scale measures how orderly and dutiful a person is. Someone who scores
high on this scale is very attached to fixed rules and habits and is very conscientious. Someone who
scores low on this scale is very flexible, adapts easily to any given situations and would like to solve
problems. Therefore, in this study, the total scale had to be reverse-coded so that respondents who
scored high on this scale were seen as being highly flexible and adaptable.The scale for this study
existed of eight items, which had to be answered with three answer possibilities, namely: ‘True’,
‘don’t know’, or ‘False’. Statements such as ‘I don’t like to interrupt the task I am working on’ and ‘I
often do things in a fixed order’ had to be answered.
Principal factor analysis for the eight-item flexibility scale for the two working days from
home and the two working days at the office showed that two of the eight items did not met the
requirement for the correlation coefficients being higher than .3 (Pallant, 2007). These items were
items 75 and 79 and were deleted from the scale. For the remaining six items principal factor
17
analysis showed one clear eigenvalue higher than one, which declared 47,49% of the variance. The
KMO value for these six items was .809 and the Bartlett’s Test of Sphericity was significant (.00)
(Appendix II). The internal consistency of this six-item scale had a Cronbach’s alpha of .770, which
was indeed higher than the eight-item scale (α = .758).
Operationalization general-level Concentration
To check for consistency among the respondents answers on the scale of concentration on work
tasks, this scale was also added to the general questionnaire (Appendix I). In this way the common
and daily experiences of this concept were measured and compared to each other. The general level
of concentration scale was the same scale as the daily concentration scale, except for the fact that the
items did not start with ‘today…’. The scale existed of four items which together made a Cronbach’s
alpha of.914. In this research this general-level of concentration will be used as a control variable.
3.5.
Control Variables
To show whether the relationships between the variables in this research were not caused due to any
disturbing factors, five control variables were included in this study.
General level of concentration. With controlling for the general level of concentration, a
consistency check in the answering of the respondents on the daily questionnaire is made possible.
Gender. Research has shown that gender is related to working from home. As Sullivan &
Lewis (2001) notice, women tend to work from home because of domestic reasons, whereas men
have the tendency to work from home because of work-related- and individual reasons. Therefore it
can be argued that gender also has an impact on concentration on work tasks. According to O’
Connell et al. (2008) gender also seems to affect adaptability.
Age. Age also has an effect on working from home. The amount of teleworkers is the highest
in the age category 35 to 44 years (CBS, 2005). Furthermore there seems to be significant differences
between concentration abilities in old and young people (Grady, Springer, Hongwanishkul,
McIntosh & Winocur (2006). Grady et al. (2006) state that it is also known that older adults are
more easily distracted. Also adaptability is likely to be influenced by age (O’ Connell et al., 2008). As
O’Connell et al. (2008) state, gender and age may set expectations to social norms and create
differences in treatment in the workplace. So for all variables in this research, age seems to be
relevant.
Family life stage. When someone is living alone, fewer distractions by the family domain are
likely to occur. However, when this is not the case, distractions by co-residents are likely to happen
18
when working at home. According to Sullivan & Lewis (2001), these co-residents are crucial actors
in the construction of the home as a workplace. Moreover, in this study the expectation is that
concentration depends on the amount of distractions an employee experiences. Therefore, an
understanding of the impact of an employee’s family life stage should be taken into consideration.
Occupational level and educational background. It seems that employees with a managerial position
are more likely to work from home than employees who do not have a managerial position (Tijdens,
Wetzels & Van Klaveren, 2000). Also higher educated employees seem to work more from home,
because they have to do more thinking and writing than lower educated employees (CBS, 2005).
Therefore, attaining high levels of concentration on work tasks seem to be more relevant to higher
educated employees.
3.6.
Quality of the data
The general questionnaire was filled in by 120 respondents. The daily questionnaires in its turn had
to be restructured, due to the fact that no fixed order was given in the way the home and office days
had to be filled in by the respondents. Furthermore, not all respondents ideally followed up the
instructions in the questionnaire. For instance, some respondents did not fill in all the daily
questionnaires and others filled in more than three office days and less than three home days.
However, to conduct the regression analyses, a clearly structured SPSS datafile was needed.
Therefore the data was entered in SPSS in the following order: general questionnaire, home day 1,
home day 2, home day 3, office day 1, office day 2 and office day 3.
When further analyzing the datafile, a difference was found in ‘clear’ home and office days
and ‘unclear’ home and office days. It was decided to only keep the ‘clear’ home and office days in
the datafile. This decision was based on the rule that a respondent had to work at least twice the
amount of hours at home compared to the hours at the office on a day in order to be scaled as a real
home day and the other way around to be indicated as a real office day.
Moreover, when for instance, a respondent filled in more than three office days, this fourth
‘clear’ office day was also removed from the datafile. The previously mentioned rules led to a
removal of a total of 54 daily questionnaires from the datafile and the decision to only analyze the
data for the first two home days and the first two office days. The exact numbers of respondents
that filled in clear home- and office days can be found in table 2.
19
Table 2
Number of respondents for each day separately
Type of day
Home day 1
No. of respondents
115
Home day 2
102
Home day 3
77
Office day 1
116
Office day 2
112
Office day 3
103
3.7.
Statistical analysis
After all data was collected, a standard statistical program, SPSS, was used to enter and analyze the
data. First, the frequency tables were used to detect errors and missing values (Pallant, 2007).
Secondly, the reversed coded total scale of flexibility and the fourth item of the concentration scale
were recoded, so that high answers on the flexibility scale meant high scores on being flexible and
high scores for the fourth item of the concentration on works tasks scale meant being highly
concentrated. Finally, the data set was checked on assessing normality and outliers (Pallant, 2007).
To test the hypotheses in the preceding conceptual model, hierarchical multiple regression
analyses on the dataset were conducted for each day separately. This was done because this type of
analysis, also known as sequential multiple regression analysis, is frequently used in research using
linear- and interaction effects (Keith, 2006).
Before these hierarchical multiple regression analyses were done, all variables which were used in the
interaction effects had to be centered (Voeten & van den Bercken, 2004). Then all variables were
entered one by one into the regression equation. This was done in the following sequence:
I. Control variables
II. Work-related distractions, non-work-related distractions and personal flexibility
III. Work-related distractions x personal flexibility and non-work-related distractions x personal
flexibility.
In sum, the conceptual model was tested four times, so that the results of two working days
at home could be compared to each other and to the results of the two working days at the office. In
20
such manner conclusions were drawn about the effects of the location (home or the office) on
work- and non-work-related distractions and concentration, with the moderating variable of
personal flexibility. The results of these analyses are discussed in the Results section.
4. Results
4.1. Variable differences between Home Days and Office Days
Before testing the actual hypotheses, the variables concentration on works tasks, work-related- and
non-work-related distractions will be tested separately for home and office days. This will be done
with a paired-samples t-test, which is applied when data is collected from one group of respondents
under two different conditions (Pallant, 2007). With SPSS it is possible to test whether the average
degree of the variables significantly differ from each other. First, a paired-samples t-test will test
whether the average degree of work-related distractions on an office day is significantly higher than
on a home day. Moreover, with another paired-samples t-test it is tested whether the average degree
of non-work-related distractions is significantly higher on home days than on office days. Lastly, a
paired-samples t-test was conducted to look for significant differences between home and office
days for the variable concentration on work tasks. In this way the explorative question stated earlier
in this research can be answered: To what extent does the level of concentration on work tasks and the level of
work-related and non-work-related distractions vary between home days and office days?
The results of the three paired-samples t-test are shown in table 3.1, 3.2, and 3.3.
Table 3.1.
Results of the paired- samples t-test for Work-related distractions
Mean
Std.
Deviation
t
df
Sig. (2tailed)
Eta
squared
Pair 1
Home day 1 – Home day 2
.058
1.023
,581
101
.563
Pair 2
Office day 1 – Office day 2
.117
.9389
1,314
110
.192
Pair 3
Home day 1 – Office day 1
-.708
1.210
-6,222
112
.000
0.26
Pair 4
-.610
1.210
-5,263
108
.000
0.20
Pair 5
-.810
1.224
-6,616
99
.000
0.31
Pair 6
-.722
1.271
-5,594
96
.000
0.25
21
Foremost, as can be seen from table 3.1, work-related distractions do not significantly differ from
each other on the same kind of days. Therefore, it can be concluded that between home day 1
(M=2,726) and home day 2 (M=2,667) and between office day 1 (M=3,437) and office day 2
(M=3,320), there is no significant difference in work-related distractions. The difference between the
mean on home day 1 (M=2.726) the mean on office day 1 (M=3,437) and the mean on office day 2
(M=3,320) seem to be significant at p<0.001. Also, the difference between the mean on home day 2
(M=2,667) and the means on the office days seem to be significant at p<0.001. In general, it can be
concluded that work-related distractions seem to be lower on home days compared to office days
and the effect size between these days can be considered to be quite large, according to the eta
squared, which is higher than .14 (Pallant, 2007).
Table 3.2.
Results of the paired- samples t-test for Non-work-related distractions
Mean
Std.
Deviation
t
df
Sig. (2tailed)
Eta
squared
Pair 1
.100
1.052
,951
99
.344
Pair 2
-.041
.9562
-,447
110
.656
Pair 3
.558
1.308
4,515
111
.000
0.16
Pair 4
.514
1.218
4,385
107
.000
0.15
Pair 5
.520
1.176
4,402
98
.000
0.17
Pair 6
.417
1.160
3,519
95
.001
0.12
Next to table 3.1, table 3.2. also shows that non-work-related distractions do not significantly differ
between days of the same kind. Furthermore, the differences between the mean of home day 1
(M=2.896) and the mean of office day 1 (M=2.284) and office day 2 (M=2.324) seem to be
significant at p<0.001. This also yields for home day 2 (M=2.796) and the office days. In sum, this
means that non-work related distractions seem to be higher on home days in comparison to office
days, which is also reflected by the eta squared. The effect size between the two home- and the two
office days can be considered as relatively large, because the eta squared is approximately around .14.
22
Table 3.3.
Results of the paired- samples t-test for Concentration on work tasks
Mean
Std.
Deviation
t
df
Sig. (2tailed)
Eta
squared
Pair 1
-.005
1.276
-,039
101
.969
Pair 2
.016
1.238
,134
111
.894
Pair 3
.192
1.727
1,177
111
.242
0.01
Pair 4
.252
1.707
1,543
108
.126
0.02
Pair 5
.245
1.803
1,358
99
.177
0.02
Pair 6
.342
1.720
1,967
97
.052
0.04
Finally, the results of the paired-samples t-test in table 3.3. show that concentration between home
days do not significantly differ from each other, suggesting that the levels of concentration are the
same on days working from home. The same result yield for office days, because of p>.05, the
concentration levels on office days can be considered the same. However, when comparing home
days with office days, small differences are found. This can be explained as concentration being
more of a fixed personal characteristic, which does not fluctuate radically. A significant difference
between the mean of home day 2 (M=4.728) and the mean of office day 2 (M=4.507) is found with
p<.05. However, the difference between home day 2 and office day 1 (M=4.522) was only
significant at a p<.10. This was also the case for the difference between home day 1 (M=4.723) and
office day 2. For the difference between the means of home day 1 and office day 1, no significant
result was found, which suggests that the concentration levels did not differ for these days. In sum it
can be said that concentration on work tasks differs in some cases, but overall concentration seems
to be the same for different kind of days. Moreover, when taking a look at the eta squared, the effect
sizes between home days and office days are relatively small (relatively: .01, .02, .02, .04), suggesting
that even if there were differences between the home days and the office days, these differences are
quite small.
23
4.2.
Correlations
In the tables 4.1, 4.2, 4.3 and 4.4, the number of respondents, the means, standard deviations and
Pearson’s correlations for all variables are shown. Correlations concerning the control variables
education, living situation and work level should be interpreted with caution, because in this study’s
sample respondents did not score evenly on the answering categories. For example, in this study
almost all respondents were highly educated. Moreover, the correlation matrixes were checked for
multicollinearity issues between the variables work-related- and non-work-related distractions. As a
guideline correlations of .3 till .49 were considered to be good (Cohen, 1988). These correlations for
the two working days from home were respectively, r=.375, and r=.355. For both office days these
correlations were respectively: r=.263 and r=.488. So, in sum, there seemed to be no disruptive
multicollinearity issues.
When taking a look at the dependent and independent variables, for all days, a negative
correlation between work-related distractions and concentration on works tasks is found (r=-.509,
r=-.-.381, r=--.398, r=-.535, all with p < .01). The same, but somewhat higher, negative correlation
yields for non-work-related distractions and concentration on work tasks for all days as well (r=-.662,
r=-.658, r=-.524 and r=-.629, all with p < .01). Another remarkable and significant correlation exists
between the interaction effect of non-work-related distractions and flexibility on concentration (r=.456, r=-.502, r=-.399, r=-.475, all with p < .01). These correlations seem to be much higher than
the interaction effect of work-related distractions and flexibility on concentration (r=-.255, p < .01 ,
r=-.231, p < .01 , r=.176, n.s., r=-.280, p < .01). As can be seen by these results, being flexible in
combination with either work-related-or non-work-related distractions decreases the direct
correlation these variables have with concentration on work tasks. This conclusion suggests that
when experiencing distractions of one or both kinds and being flexible is beneficial for
concentration. Overall, for all days, non-work-related distractions seem to effect concentration on
work tasks more than work-related distractions do.
24
Table 4.1
Correlation Matrix Home Day 1; Number of Respondents (N), Mean(M), Standard Deviation(SD) and intercorrelations
Variables
N
M
SD
1
2
3
4
5
6
76
8
9
10
1. Concentration
114
4.730
1.310
2. Work Distractions
(WD)
115
2.726
.911
-.509**
3. Non Work
Distractions (NWD)
114
2.833
1.114
-.662**
.375**
4. Flexibility
120
2.161
.590
.155
-.194*
-.255**
5. Interaction WD *
Flexibility
115
-.255**
.701**
.078
.522**
6. Interaction NWD *
Flexibility
114
-.456**
.157
.729**
.421**
.391**
7. General
Concentration level
120
.381**
-.083
-.220*
.166
.051
-.119
8. Gender
120
.098
-.063
-.061
-.072
-.099
-.122
-.020
9. Age
120
36.13
.102
.012
-.055
-.036
.015
-.105
.272**
-.179
10. Education
120
5.22
-.045
-.025
-.165
.100
.042
-.074
-.046
-.039
-.082
11. Living Situation
120
2.78
-.135
.134
.167
.109
.151
.176
.097
-.096
.470**
-.078
12. Work Level
120
1.52
-.021
.147
.234*
-.241**
-.073
-.013
.033
-.176
.240**
-.232*
4.758
1.232
10.805
11
12
.148
** p < .01 (2-tailed), * p < .05 (2-tailed).
25
Table 4.2
Correlation Matrix Home Day 2; Number of Respondents (N), Mean(M), Standard Deviation(SD) and intercorrelations
Variables
N
M
SD
1
2
3
4
5
6
7
8
96
10
1. Concentration
102
4.727
1.361
(WD)
102
2.667
.945
-.381**
3. Non Work
Distractions (NWD)
101
2.797
1.070
-.658**
.355**
4. Flexibility
120
2.161
.590
.075
.027
-.146
5. Interaction WD *
Flexibility
102
-.231**
.769**
.126
.622**
Flexibility
101
-.502**
.253**
.760**
.490**
.456**
7. General
Concentration level
120
,256**
-.236*
-.154
.166
-.118
-.027
8. Gender
120
-.036
-.132
.053
-.072
-.088
.066
-.020
9. Age
120
36.13
.041
.080
.001
-.036
.003
-.050
.272**
-.179
10. Education
120
5.22
.047
-.218*
-.222*
.100
-.130
-.160
-.046
-.039
-.082
120
2.78
-.131
.206*
.182
.109
.164
.154
.097
-.096
.470**
-.078
12. Work Level
120
1.52
-.112
.166
.214*
-.241**
-.060
.024
.033
-.176
.240**
-.232*
4.758
1.232
10.805
11
12
.148
** p < .01 (2-tailed), * p < .05 (2-tailed).
26
Table 4.3
Correlation Matrix Office Day 1; Number of Respondents (N), Mean(M), Standard Deviation(SD) and intercorrelations
Variables
N
M
SD
1
2
3
4
5
6
77
8
9
10
1. Concentration
116
4.569
1.306
(WD)
116
3.414
.931
-.398**
3. Non Work
Distractions (NWD)
116
2.254
.917
-.524**
.263**
4. Flexibility
120
2.161
.590
.130
-.110
-.306**
5. Interaction WD *
Flexibility
116
-.176
.632**
-.059
.674**
Flexibility
116
-.399**
.147
.743**
.368**
.379**
7. General
Concentration level
120
.471**
-.172
-.286**
.166
.009
-.186*
8. Gender
120
.107
-.124
.001
-.072
-.110
.003
-.020
9. Age
120
36.13
.177
-.108
-.065
-.036
-.132
-.098
.272**
-.179
10. Education
120
5.22
-.096
-.127
-.069
.100
-.010
-.011
-.046
-.039
-.082
120
2.78
-.030
-.020
.048
.109
.058
.113
.097
-.096
.470**
-.078
12. Work Level
120
1.52
-.032
.267**
.214*
-.241**
-.044
-.042
.033
-.176
.240**
-.232*
4.758
1.232
10.805
11
12
.148
** p < .01 (2-tailed), * p < .05 (2-tailed).
27
Table 4.4
Correlation Matrix Office Day 2; Number of Respondents (N), Mean(M), Standard Deviation(SD) and intercorrelations
Variables
N
M
SD
1
2
3
4
5
6
76
8
9
10
1. Concentration
112
4.507
1.289
(WD)
111
3.320
1.048
-.535**
3. Non Work
Distractions (NWD)
111
2.324
1.048
-.629**
.488**
4. Flexibility
120
2.161
.590
.278**
-.338**
-.429**
5. Interaction WD *
Flexibility
111
-.280**
.623**
.064
.490**
Flexibility
111
-.475**
.263**
.725**
.255**
.437**
7. General
Concentration level
120
.376**
-.141
-.249**
.166
-.012
-.178
8. Gender
120
.139
-.113
.005
-.072
-.124
.003
-.020
9. Age
120
36.13
.113
.028
-.043
-.036
-.030
-.100
.272**
-.179
10. Education
120
5.22
-.036
-.095
-.170
.100
.007
-.113
-.046
-.039
-.082
120
2.78
-.078
.076
.186
.109
.136
.268**
.097
-.096
.470**
-.078
12. Work Level
120
1.52
-.153
.364**
.328**
-.241**
.038
.077
.033
-.176
.240**
-.232*
4.758
1.232
10.805
11
12
.148
** p < .01 (2-tailed), * p < .05 (2-tailed).
28
4.3. Sequential multiple regression analyses and control variables
In order to test the influence of work-related distractions and non-work-related distractions,
personal flexibility and the interaction effects of these variables on concentration on work tasks,
hierarchical multiple regression analysis was conducted to test the four hypotheses for two home
days and two office days independently.
On the grounds that the sample size of this study was not quite large (N=120), the choice
has been made to use a maximum number of five independent variables that will be included in the
analyses. Meyers, Gamst & Guarino (2006) recommended to have a sample size that is twenty times
the number of predictors. Since the respondents vary from 102 till 120 per day, it seems that the
best solution is to apply five independent variables. In this study this means that only two control
variables could be entered into the regression analyses. Because of the fact that the last three control
variables; education, living situation and work level, did not vary equally between the corresponding
answer categories and research about the combination of gender and concentration and/or gender
and distractions is less pronounced, the choice have been made to include age and general level of
concentration as the most important control variables in this research.
Nevertheless, as a conclusion only general feelings of concentration appear to have a
significant effect on the dependent and the independent variables, whereas age does not (Appendix
III) Therefore, this non-significant control variable age will not be taken into account when further
analyzing the data.
29
4.4. Hierarchical multiple regression analysis Home Day 1
Table 5.1
Results Hierarchical multiple regression analysis Home Day 1
Model 1
Model 2
Model 3
.381***
.256***
.261***
Work distractions
-.312***
-.293***
Non-work distractions
-.509***
-.471***
Personal Flexibility
-.077
-.066
General Concentration level
Work distractions * Flexibility
.078
Non-work distractions * Flexibility
.087
R²
.145
R² Change
F Change
18,843***
.581
.600
.436***
.019
37,492***
2,517***
*** p < .001 (2-tailed), ** p < .01 (2-tailed), * p < .05 (2-tailed).
As can be seen by table 5.1, 14,5% of the variance in concentration on work tasks is explained by
Model 1, or differently said, by the control variable general concentration level. The beta (ß= .381,
p<0.001) suggests that the higher a respondents general level of concentration is, the higher this
respondents concentration level is on home day 1.
Model 2 explains an additional 43,6% to the variance in concentration on work tasks. This
model shows that work-related distractions and non-work-related distractions have a negative effect
on concentration (respectively: ß= -.312, p< 0.001 and ß= -.509, p< 0.001). Therefore hypotheses
one and two are confirmed for home day 1.
In addition, Model 3 explains only an additional 1.9% of the variance in concentration on
work tasks. In this model the moderator effects of personal flexibility are added. However, no
significant effects of neither the interaction effect between work-related distractions and personal
flexibility nor the interaction effect of non-work-related distractions and personal flexibility were
30
found. Therefore, hypotheses three and four are rejected for home day 1. In figure 2.1 the results of
the hierarchical multiple regression analysis for home day 1 are shown.
Personal
Flexibility
.087(n.s)
Work-Distractions
-.078(n.s)
-.312***
Concentration
on work tasks
-.509***
Figure 2.1. Results of linear regression analysis for home day 1
4.5. Hierarchical multiple regression analysis Home Day 2
In table 5.2 the results of the hierarchical multiple regression analysis for home day 2 are shown. As
can be seen from this table, 6,5% of the variance in concentration on work tasks is explained by a
respondents general level of concentration.
Furthermore, an additional 45.8% to Model 1 of the variance in concentration on work tasks
is explained by Model 2. Model 2 shows that work-related distractions and non-work-related
distractions have a negative effect on concentration on work tasks (respectively: ß= -.137, p< 0.05
and ß= -.593, p< 0.001). Therefore hypotheses one and two are also confirmed for home day two.
In addition, just like home day 1, Model 3 for home day 2 only explains an additional small
non-significant variance to Model 2 (R² Change=1%). In other words, no significant interactions
effects were found. In other words, the interaction effect of work-related distractions and the
personal characteristic flexibility on concentration on work tasks and the interaction effect of nonwork-related distractions and the personal characteristic flexibility on concentration on work tasks
were not found. Therefore, hypotheses three and four are also rejected for home day 2. Figure 2.2
shows the results of the hierarchical multiple regression analysis for home day 2.
31
Table 5.2
Results Hierarchical multiple regression analysis Home Day 2
Concentration on Work Tasks
Model 1
Model 2
Model 3
.256***
.137*
.126
Work distractions
-.137*
-.136
-.593***
-.632***
-.031
-.045
-.121
.048
R²
.065
R² Change
F Change
6,939**
.475
.485
.410***
.010
25,007***
,895***
Personal
Flexibility
.048(n.s)
Work-Distractions
-.121(n.s)
-.137*
Concentration
on work tasks
-.593***
Figure 2.2. Results of linear regression analysis for home day 2
32
4.6. Hierarchical multiple regression analysis Office Day 1
Table 5.3 shows the results of the hierarchical multiple regression analysis of office day 1. As can be
noticed, 22,2% of the variance in concentration on work tasks is explained by Model 1, namely by
the respondents general level of concentration. The beta of general level of concentration (ß= .471,
p<0.001) suggests that the higher the general level of concentration of a respondent is, the higher
this respondents concentration on work tasks for office day 1 is.
Model 2 demonstrates significant negative effects of work-related distractions and nonwork-related distractions on concentration on work tasks (respectively: ß= -.248, p< 0.001 and ß= .385, p< 0.001). Therefore, hypotheses one and two for office day 1 are confirmed.
Moreover, Model 3 shows to be a non-significant addition to the variance already explained
by Model 2. Both interaction effects stated in this model can be considered neglectable (ß= 0.001,
p= not significant and ß= 0.048, p = not significant). This means that hypotheses three and four are
rejected for office day 1. Figure 2.3 shows the results of the hierarchical multiple regression analysis
for office day 1 graphically.
Table 5.3
Results Hierarchical multiple regression analysis Office Day 1
Model 1
Model 2
Model 3
.471***
.330***
.336***
Work distractions
-.248***
-.241***
-.385***
-.384***
-.069
-.072
.001
Non work distractions * Flexibility
.048
R²
.222
R² Change
F Change
32,505***
.447***
.449
.225***
.002
15,054***
,224***
33
Personal
Flexibility
.048(n.s)
Work-Distractions
.001(n.s)
-.248***
Concentration
on work tasks
-.385***
Figure 2.3. Results of linear regression analysis for office day 1
4.7. Hierarchical multiple regression analysis Office Day 2
Table 5.4 demonstrates the results of the hierarchical multiple regression analysis for office day 2.
Model 1 appears to explain a percentage of 14.1 of the variance in concentration on work tasks.
In Model 2, work-related distractions and non-work-related distractions both have negative
direct effects on concentration on work tasks (respectively: ß= -.306, p< 0.001 and ß= -.447, p<
0.001). Therefore, it can be concluded that both hypothesis one and hypothesis two are confirmed
for office day 2.
Moreover, for this office day, the interaction effect of work-related distractions and personal
flexibility seems to be significant ( ß= -.138, p<.05). However, the interaction effect of non-workrelated distractions and the personal characteristic flexibility appears to be non-significant (ß= -.019,
p= not significant) and therefore hypothesis four is already rejected. Figure 2.4 displays the results of
the hierarchical multiple regression analysis for this office day 2.
34
Table 5.4
Results Hierarchical multiple regression analysis Office Day 2
Model 1
Model 2
Model 3
.376***
.231***
.231***
Work distractions
-.303***
-.315***
-.447***
-.467***
-.054
-.074
-.138*
-.019
R²
.141
R² Change
F Change
17,948***
.515
.531
.373***
.016
27,175***
1,775***
Personal
Flexibility
-.019(n.s) -.138*
Work-Distractions
-.303***
Concentration
on work tasks
-.447***
Figure 2.4. Results of linear regression analysis for office day 2
35
To take a closer look at the significant interaction effect of work-related distractions and personal
flexibility on concentration on work tasks for office day 2 (hypothesis 3), an interaction plot has
been made. The border between high and low outcomes was at the middle point of the actual
responses given to the scale of personal flexibility and work-related distractions. However, as can be
seen in figure 2.5, the opposite of what is expected happens. Namely when an individual scores high
on the personal characteristic of flexibility in combination with experiences of high work-related
distractions he or she has a lower concentration on work tasks instead of a higher concentration on
work tasks. It is therefore, hypothesis three in this study is rejected for office day 2. Moreover, in
the figure it is indicated that there seems to be almost no differences in the levels of concentration
on work tasks for individuals who experience low work-related distractions and scoring either high
or low on personal flexibility. This is logical to occur, because when an individual does not
experience any or low distractions, he or she does not always have to react to them and in turn can
stay highly concentrated on the task at hand.
Figure 2.5. Interaction plot of Work-related distractions and Personal Flexibility for office day 2
4.8. Additional analysis on the interaction effects for Home Days and Office Days
As was found by the separate hierarchical regression analyses, none out of the eight possible
interaction effects have been confirmed. It is therefore expected that there is no clear linear effect
between both types of distractions and personal flexibility. Overall, with hierarchical multiple
36
regression analysis it is expected that effects will be found on two combinations. The first one being
high distractions and low personal flexibility, which will have disadvantageous consequences for
concentration on work tasks. The second one being high distractions and high personal flexibility,
which will have better consequences for concentration on work tasks than not being flexible at all.
These effects are shown in figure 3. However, when one of these expectations does not occur, no
interaction effects will be found in hierarchical multiple regression analysis. Therefore, to take a
more detailed look at the seven other non-significant interaction effects, a two-way univariate
analysis of variance (ANOVA) was conducted.
With two-way ANOVA the effect of two independent variables on the dependent variable
and the interaction effect can be simultaneously tested (Pallant, 2007). Within this analysis the
variables work-related- and non-work-related distractions and personal flexibility are beforehand
transformed into categorical variables. In this way, six groups are formed: a group scoring high and
low on work-related distractions, a group scoring high and low on non-work-related distractions and
a group scoring high and low on flexibility. The border between high and low was at the midpoint of
the actual responses on the scale for each of these groups, in order to get the most equal distribution.
In such a way all combination effects for high and low work-related distractions, high and low nonwork-related distractions and high and low personal flexibility levels on concentration on work tasks
will become clear by looking at the mean of concentration on work tasks for these combined groups
separately.
HIGH
-
0
+
+
(non-)work
Distractions
LOW
LOW
HIGH
Figure 3. Expected linear interaction effects of both work and non-work distractions and personal flexibility
For all days this two-way between-groups analysis of variance was conducted to explore the impact
of personal flexibility and distractions on concentration of work tasks. Per day two ANOVA-tests
were done, one with the independent variable concentration on work tasks, personal flexibility and
37
work-related distractions and another one with the dependent variable concentration on work tasks,
personal flexibility and non-work-related distractions. As can be seen in figure 4, for almost all days
it seems that concentration was indeed the lowest among respondents whom experienced high
distractions (both work and non-work) and who scored low on the personal characteristic flexibility.
However, just like the interaction effect of work-related distractions and personal flexibility on
concentration on work tasks on office day 2, there was a same kind of exception, namely for office
day 1 and the level of non-work-related distractions. On that specific day respondents had lower
concentration levels when experiencing high distractions, but also whom scored high on the
personal characteristic of flexibility. In Appendix IV, the results of the two-way ANOVA are given
for each day separately both for work-related- as for non-work-related distractions.
Moreover, the results of the independent-samples t-test are shown in Appendix V. In this
Appendix (non-)significant differences between the two most relevant groups for this study are
shown, namely group 1: low personal flexibility and high work-related- and non-work-related
distractions and group 2: high personal flexibility and high work-related- and non-work-related
distractions. These two groups are the relevant ones, because when an individual experiences none
to low distractions his or hers concentration on work tasks will without a doubt be higher than
someone who experiences high distractions. Then in turn, personal flexibility seems irrelevant in this
case, because this concept measures how well an individual copes with distractions or with
irregularities at work. This is measured and reflected in the lower quadrants of figure 4.
As can be seen in the results in Appendix V, only home day 1 shows a significant interaction
effect of work-related distractions and personal flexibility on concentration on work tasks (p<.05)
and a significant interaction effect of non-work-related distractions and personal flexibility on
concentration on works tasks (p<.05).
However, even with the fact that concentration on work tasks generally was the lowest
among respondents who experienced high distractions and who were low on personal flexibility,
these results can be considered neglectable for the remaining three days when comparing these
results with the results of respondents who scored high on distractions and high on personal
flexibility (p>.05). Therefore, in this study, hypotheses three and four are confirmed for home day 1,
but still rejected for home day 2 and the two office days.
38
HIGH
Low
(non-)work
Distractions
LOW
Low/
Moderate
High
High
LOW
HIGH
Figure 4. Two-way ANOVA; results for all days except for office day 1; non-work-related distractions
5. Conclusion and Discussion
5.1. Conclusion
The aim of this study was to give an appropriate answer to the research question stated in the
introduction:
To what extent do work- and non-work distractions influence an employee’s concentration on work tasks?
Furthermore, does the personal characteristic of flexibility make a difference in this respect?
Four hypotheses were formulated to see if there were indeed relationships between work-related
distractions, non-work-related distractions and concentration on work tasks and the possibility of a
moderating effect of personal flexibility. The first hypothesis stated that work-related distractions
have a negative effect on concentration on work tasks; this hypothesis was confirmed for all four
days, which were two home days and two office days. The second hypothesis stated that non-workrelated distractions have a negative effect on concentration on work tasks; this hypothesis was
confirmed for all days as well. The third hypothesis concerned the moderating effect of personal
flexibility on work-related distractions on concentration on work tasks. This hypothesis was rejected
for all days, although for office day 2 a negative significant effect (ß =-.138, p<.05) was found.
However, this interaction effect was not in the way that it was expected to be and therefore it was
decided to reject this hypothesis for office day 2. The fourth and last hypothesis stated that the
39
personal characteristic flexibility will buffer the relationship between non-work-related distractions
and concentration on work tasks. However, this hypothesis was rejected with hierarchical multiple
regression analysis for all days.
Because for all days none out of the eight possible interaction effects have been found in the
regression analyses, it was expected that there was no clear linear effect between both types of
distractions and personal flexibility. Therefore a univariate analysis of variance was conducted for all
days. As expected, the results of this test showed that concentration on work tasks was generally the
lowest for respondents who experienced high distractions and low flexibility. Nevertheless, the
differences between these respondents and respondents who also experienced high distractions but
scored high on flexibility can be considered as being not significant and therefore neglectable for
home day 2 and for both office days. However, for home day 1 the third and fourth hypothesis was
confirmed with p<.05, being the interaction effect of personal flexibility on work-related distractions
and non-work-related distractions on concentration on works tasks. This indicates that when an
individual is personally flexible this in turn diminishes the direct negative relationship between workrelated and non-work-related distractions and concentration on work tasks.
Next, to see if there were indeed differences between the variables for the two home days and the
two office days an explorative question was stated in this research:
To what extent does the level of concentration on work tasks and the level of work-related and non-workrelated distractions vary between home days and office days?
The expectation was that work-related distractions would be higher on office days compared to
home days and that non-work-related distractions would be higher for home days compared to
office days. Moreover, it was expected that concentration on work tasks would be more or less the
same for office days and home days, because with the New Way of Working and the Twenty-FourHours-Society it has become normal to communicate, whenever, wherever and without actually
meeting each other.
Three different paired-samples t-tests were conducted for all days to see if these expectations
were met: one considered the variable work-related distractions; another considered the variable
non-work-related distractions; whereas a last paired-samples t-test considered the variable
concentration on work tasks. For all three variables it seemed that the same type of days, so home
days or office days, did not significantly differ from each other, so they can be considered to be the
40
same. Furthermore, the paired-samples t-test for both types of distractions showed that home days
do significantly differ from office days, in such a way that work-related distractions are higher at
office days compared to home days and non-work-related distractions are higher on home days
compared to office days. The corresponding eta squared for these pairs of distractions had an
overall large effect, which means that the differences for these variables between different kinds of
days were large. Concentration on work tasks, on the other hand, seems to slightly differ for the pair
home day 2 and office day 2, however, only a small effect size was found (eta squared =0.04). For
the other three pairs, no significant effect of p<0.05 was found. Therefore, it can be said that
concentration seems to be a stable factor, which does not fluctuate radically between different
locations (home or the office). It also seems not to fluctuate radically within a person. This was
based on the control variable general level of concentration in the regression analyses, namely, when
a respondents general level of concentration was high, his or hers daily concentration seemed to be
high as well (respectively ß= .256, p<.001, ß= .137, p<.05, ß= .330, p<.001, ß= .231, p<.001) This
finding suggests that concentration on work tasks, when influenced by distractions, more or less can
be labeled as a stable personal characteristic and should not fluctuate radically between days,
locations or time.
In sum it can be said that the beforehand made expectations for the three different variables
between different types of locations, being the home and the office, were fulfilled.
5.2.
Discussion of the findings
The most striking finding in this study is the fact that concentration on work tasks appeared to be
largely the same for home days as for office days. This is not in line with previous research, but for
this research, which was held in a generally New Way of Working environment, it was exactly what
was beforehand expected. However, it can be that this finding was influenced by the living situation
of the respondents who lived alone. It is this group, from which it was expected to have the highest
possibility to stay or be concentrated on work tasks in comparison to the other groups, namely the
groups: living alone with children, living together or living together with children. The reason why
this group could have higher concentration levels at home is because they experience no distractions
of other family members who live in the same house and therefore they can plan their own working
schedule, because they do not have to take into account other persons wishes and/or demands.
Nevertheless, the group of respondents that lived alone only consisted of 33 respondents out of the
120 respondents. Therefore, as this group is somewhat underrepresented in this study, it can be that
41
the differences between home days and office days is not significant.
Next, the degree of work-related distractions appears to be the highest on office days in
comparison to home days, as this was tested with a paired-samples t-test. As mentioned in the
theory section, research found that working from home fosters better concentration than working at
the office, because less work-related interruptions should take place at home (Montreuil & Lippel,
2002; Van Sell & Jacobs, 1994). However this seems not necessarily the case when taking a look at
the results of the hierarchical multiple regression analyses. Especially, when taking a closer look at
home day 1, concentration on work tasks for that day is besides non-work-related distractions (ß= .509, α = 0.001) also highly effected by work-related distractions (ß= -.312, α = 0.001). Nevertheless,
home day 2 shows a much lower negative effect for work-related distractions on concentration on
work tasks (ß= -.137, α = 0.05). For the office days the differences between the effects of non-workrelated distractions and work-related distractions on concentration on work tasks seemed to be
much lower, so more in balance, than the home days.
In contrast, the degree of non-work-related distractions appears to be the highest for home
days, which was also tested with a paired-samples t-test. As Sullivan & Lewis (2001) already
explained, this is logical to occur, because employees working at home can give more way to nonwork-related distractions’ activities, whereas office employees generally cannot (f.e. doing the dishes,
taking the children to school, taking the dog for a walk). This in turn means that working from
home can be considered disadvantageous for an employee to obtain high concentration levels. When
testing this hypothesis 2, it certainly showed that the relationship between non-work-related
distractions and concentration on work tasks on home days was quite high (ß= -.509, p<.001 and .593, p<.001). However, this same relationship was also tested on office days, and showed quite high
negative effects as well (ß= -.385, p<.001 and -.447, p<.001). The unexpected part was the fact that
for all days, so also for the two office days, the relationship between non-work-related distractions
and concentration on work tasks was higher than the relationship between work-related distractions
and concentration on work tasks. This in turn can be explained by the emotional value non-workrelated distractions, or differently said private or personal distractions, have on an individual. In such
times, when private distractions take place, it is hard to stay focused, because worrying about private
issues will without a doubt have consequences for an employee’s concentration on work tasks. This
is better known as strain-based home-work interference (HWI), which means that anxiety and
fatigue caused by the home domain will make it more difficult to perform well in the work domain
(Demerouti et al., 2007).
42
After the execution of the regression analyses only one significant interaction effect out of
the eight possible ones emerged, being the one of personal flexibility and work-related distractions
on concentration on work tasks for office day 2. Although this hypothesis was still rejected for
office day 2, because its effect was not in the way it should have been for this research, the nonsignificant effects for the other seven hypotheses can be explained more in depth. An explanation
for this remarkable result of the non-existence of interaction effects can be found in the limited
distribution of the answers of the respondents on both the personal flexibility scale and the
distractions scales, which makes it clear why there were no linear effects found with the regression
analyses. On the flexibility scale the mean score was 2,16, where the top score was 3, suggesting that
the amount of respondents in general considered themselves being flexible. For non-work-related
distractions the highest mean respectively was 2,83, and the lowest mean was 2,25, whereas for
work-related distractions the highest mean was 3,41 and the lowest mean had a value of 2,67. This in
turn can be considered quite low, because the scale’s top score was 5. As an explanation it can be
that respondents did not feel like answering the questionnaire at the end of ‘heavy days’, which
possibly are the days they felt they were highly distracted. In conclusion this indicates why with
linear multiple regression analysis no effects were found on high work-related and high non-workrelated distractions and low personal flexibility.
A solution to find more significant effects was an additional execution of ANOVA for all
days separately. Although with these univariate analyses of variance tests, two significant interaction
effects were found, there still were five non-significant differences found between the two relevant
groups of this study. A presumably explanation for these non-significance differences can be the fact
of the limited sample size of this study. As Keith (2006) explains: to have a power of .80, you will at
least need 800 respondents to find a sequential addition of an interaction effect to the regression.
This in turn is quite a large difference with the 102 till 120 respondents which participated in this
study.
5.3.
Limitations and implications for further research
A general point of discussion concerning this research is the size of the sample. Although this
sample size was acceptable to find direct effects, this may not be the case for finding interaction
effects. Therefore, to find out if the interaction effects of personal flexibility on work related- and
non-work related distractions on concentration on work tasks is present, a research of approximately
n=800 is needed in future research (Keith, 2006). Also a more balanced sample should be
considered. In this research most of the respondents were highly educated and had quite high work
43
levels, which in turn made it difficult to state about their exact effects.
Furthermore, according to Ohly, Sonnentag, Niessen and Zapf (2010), a diary study should
at least consist of five days to decrease bias and increase generalizability. Unfortunately, in this study
the third home day was not properly answered by enough respondents (n=77), when handling the
rule of n=100. Because of this, the third office day (n=102) have not been taking into account either.
It is therefore, further research should keep in mind the arduousness of finding enough respondents
who are willing to participate in such a demanding study.
Also the fact that for this study no data was collected about the type of industry, the types of
jobs of the respondents and the kind of tasks these respondents had to perform, reduces the
strength of this study. New research about the New Way of Working should mention these control
variables, so more detailed insights can be given about New Way of Working employees.
For this study, just like in other research, the risk of social desirability was inevitable.
Respondents might not have been completely honest when answering the questions in the booklet.
However, this study emphasized the anonymity of the respondents and the confidential treatment of
the data in both the diary and the general questionnaire. Also the perception of distractions may
have been different between persons. Although beforehand a short introduction was given in the
diary of what distractions are, this still might have been interpreted differently between persons.
Further research should therefore map this and also the perceptions of the differences between
positively experienced- and negatively experienced distractions in more detail.
Because of the fact that for employees working at home the amount of non-work-related
distractions was much higher than for employees working at the office, more insight is needed in
what kind of non-work-related distractions for both the home and office days seem to matter.
Qualitative research in this case is needed. Also in this light, the limitation of a proper distractions
scale has to be mentioned. For this study a self-designed scale was used to map work-and non-work
related distractions. As with every self-designed scale, limitations can occur. For instance, the scale
used in this research only consisted of two items for work-related distractions and two items for
non-work-related distractions. Further research should therefore develop more items per scale,
which in turn will make these scales stronger.
Another scale-issue relates to the scale of personal flexibility. The scale of rigidity, which was
constructed by Barelds et al. (2007), was used as a starting point for the personal flexibility scale in
this research. However, just like the original scale the personal flexibility scale used a three-point
answering category, with ‘2’ being ‘don’t know’. As Furr (2011) explains, researchers should avoid
44
using this category as a midway between two poles of a dimension, because such an answering
category can reflect two different outcomes, namely: a lack of knowledge or a lack of opinion, which
are two completely different things.
Moreover, future research about this study’s topic should consider using multilevel analysis.
Especially because of the fact that more and more employees are starting to work in organizations
that apply New Way of Working practices. In this case it would be possible to use this within-person
design to give more insight in the way hours at home are used for work and in that way deepen the
insight about the often used dichotomous variable working from home.
5.4.
Practical implications
The New Way of Working, the integration of home and office, flexibility, multitasking, the feeling of
being available twenty-four-seven hours a day, seven days a week; just a few concepts that are hot
topics in today’s society. However, as also became clear by this study, these topics have some
efficiency problems for their employees, which seem to be irrelevant or less of a priority to
organizations (http://www.gezondweb.be). For example, with The New Way of Working, or other
flexible arrangements, open-office layouts are a must for a lot of organizations. Nevertheless, with
these layouts distractions are more likely to happen and more difficult to counteract. Therefore,
when considering the nowadays frequently introduced open-office layouts, trade-offs should be
made by organizations if this indeed is as efficient as it thought to be. From the results of this study,
which generally was set out in a New Way of Working setting, it may well be that such open office
layouts hindered concentration, which in turn can hinder performance (Demerouti et al., 2007;
Lieberman et al., 2006; Van der Linden et al., 2005). In such settings, distractions, of work-related
nature, could occur more frequently than in the case of separate office rooms. Therefore, it is
recommended to introduce concentration rooms next to the open-office layouts, in which
employees can focus on important work-related aspects. For employees working at home, same kind
of arrangements should be considered, because overall, the non-work-related distractions
experienced at home seem to have a quite negative effect on concentration. Therefore, a separate
working room at home seems to be a wise decision as well. In general, when it may be the case that
an employee wants to welcome distractions, he or she can just leave or open the room in both the
home- as the office environment.
Furthermore, in many job advertisements nowadays organizations ask for employees which
have to be highly flexible, because such organizations want their employees to adapt quickly to
45
changes when they emerge (Griffin & Hesketh, 2005; Pulakos, Arad, Donovan & Plamondon, 2000).
As individual adaptability is considered to be one of the factors that explain organizational success
(Le Pine, et al., 2000), organizations should focus more on the importance of this personal
characteristic as well. For example, when recruiting employees, a personality questionnaire can be
taken to see how rigid, or the opposite, how flexible an applicant is (Barelds, et al., 2007). Or, an
assessment test can be done to see how well an applicant deals with changing tasks. Subsequently,
these results can be included in the application process to find the best match for an organization.
In conclusion, it seems that with the integration of the home and the office as the work
domain, distractions are more difficult to counteract. However, as being flexible and being
concentrated seems to be crucial for the survival of organizations and individuals, it is of high
necessity to counter less important distractions by leaving crowded and noisy rooms to focus on
tasks which requires high levels of concentration. As became clear by the theoretical framework of
this study, such tasks appear to be highly relevant to a New Way of Working employee.
46
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50
Appendix I. General questionnaire and daily diary
Onderzoek naar de effecten van flexibel werken op het welzijn
van werknemers
In opdracht van:
Universiteit van Tilburg
Faculteit Sociale Wetenschappen
Inhoud boekje:
1 algemene vragenlijst
6 dagelijkse korte vragenlijsten
Onderzoek door:
Irene Molendijk (uw contactpersoon)
E-mail: [email protected]
Tel.: 06-15411155
51
Algemene informatie
Allereerst hartelijk dank voor uw medewerking aan dit afstudeeronderzoek van vijf Master studenten
Human Resource Studies aan de Universiteit van Tilburg. Het onderzoek gaat over uw beleving van het
werk en het effect daarvan op uw welbevinden.
Instructie
Op de volgende pagina start de algemene vragenlijst. Het invullen van deze vragenlijst zal
ongeveer 15 minuten in beslag nemen. Wij willen u vragen om deze op een afzonderlijke dag in
te vullen alvorens aan de zes andere vragenlijsten te beginnen. Beantwoord de vragen vlot en
geef het antwoord dat als eerste in u opkomt. Lees ook steeds goed de betekenis van de
antwoordcategorieën.
Wij zijn geïnteresseerd in uw eigen mening, er zijn dus geen goede of foute antwoorden.
Naast het beantwoorden van de algemene vragenlijst, verzoeken wij u om de zes dagelijkse
vragenlijsten in te vullen. Per dag zal dit vijf minuten van uw tijd in beslag nemen. De instructie
hiervoor treft u op de pagina na de algemene vragenlijst.
Vertrouwelijk
We willen benadrukken dat uw antwoorden strikt vertrouwelijk worden behandeld, niemand
binnen uw organisatie krijgt uw antwoorden te zien.
Contact informatie
Mocht u vragen hebben, neemt u dan gerust contact op met uw contactpersoon. Deze staat
vermeld op de voorzijde van dit boekje.
Retourneren
Nadat u zowel de algemene vragenlijst als de zes korte vragenlijsten heeft ingevuld, verzoeken wij u om
dit boekje vóór 8 mei te retourneren in bijgevoegde envelop. Controleert u alstublieft goed of u alle
zeven vragenlijsten volledig heeft ingevuld.
52
Algemene vragenlijst
1. Wat is uw geslacht?
Man / Vrouw
2. Wat is uw leeftijd?
...........
3. Kruis aan wat uw hoogst genoten opleidingsniveau is.
o Basisonderwijs
o VMBO/MAVO
o HAVO/VWO
o Middelbaar beroepsonderwijs
o Hoger beroepsonderwijs
o Wetenschappelijk onderwijs
4. Kruis aan welke thuissituatie voor u momenteel van toepassing is.
o Alleenstaand
o Alleenstaand met kind(eren)
o Samenwonend met partner
o Samenwonend met partner en kind(eren)
5. Kruis aan in welke positie u momenteel werkt.
o Uitvoerend
o Management
o Directie
6. Hoeveel uur per week werkt u volgens uw contract?
Vul s.v.p. het aantal uur per week in (bijv. 24 uur of 40 uur):
................. uur
53
Concentratie tijdens werktaken
1= helemaal mee oneens 2= mee oneens 3= een beetje mee oneens 4= neutraal
5= een beetje mee eens 6= mee eens
7= helemaal mee eens
60. Over het algemeen is mijn aandacht volledig gericht op waar ik mee
bezig ben.
1 2
61. Over het algemeen heb ik totale concentratie.
1 2
62. Over het algemeen ben ik volledig gericht op de taak waar ik mee
bezig ben.
1 2
63. Over het algemeen dwalen mijn gedachten af naar andere dingen
tijdens een taak.
1 2
Flexibiliteit
3 4 5 6 7
3 4 5 6 7
3 4 5 6 7
3 4 5 6 7
1= onjuist 2= weet niet
74. Een regelmatig levenspatroon bevalt me het best.
3= juist
1
2
3
75. Ik begin pas ergens aan als ik weet hoe het zal aflopen.
1
2
3
76. Ook bij onbelangrijke dingen moet ik eerst nadenken voor ik wat doe.
1
2
3
77. Als ik uit mijn dagelijkse regelmaat word gehaald hindert mij dat.
1
2
3
78. Ik houd er niet van een taak waar ik mee bezig ben te onderbreken.
1
2
3
79. Ik moet lang van tevoren weten waar ik aan toe ben.
1
2
3
80. Het kost me moeite om van een plan af te wijken.
1
2
3
81. Ik doe dingen vaak in een vaste volgorde.
1
2
3
54
Instructie dagelijkse vragenlijsten
U heeft op een voorgaande dag de algemene vragenlijst ingevuld. Dit boekje bevat verder zes korte
vragenlijsten welke bedoeld zijn om in te vullen op zes aparte werkdagen. De zes vragenlijsten zijn
identiek aan elkaar.
Zes dagen
Wij verzoeken u om zes dagen te selecteren, waarvan:
-
Drie dagen waarop u meer dan de helft van uw werktijd thuis heeft gewerkt.
Drie dagen waarop u meer dan de helft van uw werktijd op kantoor heeft gewerkt.
N.B. De dagen waarvoor u een lijst invult hoeven niet opeenvolgende werkdagen te zijn.
Instructie
Het is de bedoeling dat u aan het eind van elk van deze zes dagen één vragenlijst invult, circa een uur
voordat u naar bed gaat.
Beantwoord de vragen vlot en geef het antwoord dat als eerste in u opkomt. Lees ook steeds
goed de betekenis van de antwoordcategorieën.
Wij zijn geïnteresseerd in uw eigen mening, er zijn dus geen goede of foute antwoorden.
Vertrouwelijk
We willen nogmaals benadrukken dat uw antwoorden strikt vertrouwelijk worden behandeld,
niemand binnen uw organisatie krijgt uw antwoorden te zien.
55
Dagelijkse vragenlijst
1. Datum van vandaag:
………… - ………… - 2011
2. Vandaag heb ik meer dan de helft van mijn werktijd thuis / op kantoor gewerkt.
(omcirkel wat van toepassing is)
3. Hoeveel uur heeft u vandaag thuis gewerkt?
………….. uur
4. Hoeveel uur heeft u vandaag op kantoor gewerkt?
………….. uur
Van tijd tot tijd wordt iedereen wel eens afgeleid van zijn/haar werk, bijvoorbeeld door pratende
collega’s, huishoudelijke verplichtingen, het ophalen van uw kinderen van school of een telefoontje van
een collega, uw partner of uw kind. Ook kunt u worden afgeleid door gedachten, bijvoorbeeld aan uw
kinderen, aan een ruzie met uw partner, of aan vakantieplannen. Ook kunnen uw gedachten afdwalen
naar werkgerelateerde zaken, anders dan het werk waar u op dat moment mee bezig bent.
Hieronder vindt u een aantal vragen over de mate waarin u vandaag werd afgeleid tijdens uw werk. Geef
telkens aan wat voor u van toepassing is door het juiste getal te omcirkelen.
Afleiding tijdens het werk
1=nooit
2= bijna nooit
3= neutraal
4= regelmatig
7. In hoeverre werd u vandaag tijdens u werk afgeleid?
5= vaak
1 2 3 4 5
Indien u vandaag thuis heeft gewerkt, kunt u dan aangeven in hoeverre u vandaag tijdens uw werk thuis
werd afgeleid door de volgende zaken:
8. Gedachten gerelateerd aan andere werkzaken dan de taken waarmee u
op dat moment bezig was.
9. Gedachten gerelateerd aan privé-zaken.
1 2 3 4 5
1 2 3 4 5
56
10. Bezigheden gerelateerd aan werk, anders dan de taken waarmee u op
dat moment bezig was.
1 2 3 4 5
11. Bezigheden gerelateerd aan privé-zaken
1 2 3 4 5
Indien u vandaag op kantoor heeft gewerkt, kunt u dan aangeven in hoeverre u vandaag tijdens uw
werk op kantoor werd afgeleid door de volgende zaken:
12. Gedachten gerelateerd aan andere werkzaken dan de taken waarmee u
op dat moment bezig was.
1 2 3 4 5
13. Gedachten gerelateerd aan privé-zaken.
1 2 3 4 5
14. Bezigheden gerelateerd aan werk, anders dan de taken
waarmee u op dat moment bezig was.
1 2 3 4 5
15. Bezigheden gerelateerd aan privé-zaken
Concentratie tijdens werktaken
1= helemaal mee oneens
2= mee oneens
5= een beetje mee eens
6= mee eens
1 2 3 4 5
3= een beetje mee oneens
7= helemaal mee eens eens
31. Vandaag was mijn aandacht volledig gericht op waar ik mee bezig was.
32. Vandaag had ik totale concentratie.
4= neutraal
1 2 3 4 5 6 7
1 2 3 4 5 6 7
33. Vandaag was ik volledig gericht op de taak waar ik mee bezig was.
1 2 3 4 5 6 7
34. Vandaag dwaalden mijn gedachten af naar andere dingen tijdens de taken. 1 2 3 4 5 6 7
Bedankt voor het invullen van deze vragenlijst
Hartelijk bedankt voor uw deelname aan dit onderzoek. Wij verzoeken
u om dit boekje in bijgevoegde envelop te retourneren.
57
Appendix II. Factor analysis
Table 1
Component matrix Concentration on work tasks Home Day 1
Item Nr.
Item
Component 1
31
Vandaag was mijn aandacht volledig
gericht op waar ik mee bezig was.
,952
32
Vandaag had ik totale concentratie.
,942
33
Vandaag was ik volledig gericht op de
taak waar ik mee bezig was.
,918
34
Vandaag dwaalden mijn gedachten af
naar andere dingen tijdens de taken.
,756
Extraction Method: Principal Component analysis.
a. 1 components extracted.
Table 2
KMO and Bartlett’s Test for Concentration on work tasks Home Day 1
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
Bartlett’s Test of
Sphericity
Approx. Chi-Square
400,363
df
6
Sig.
,824
,000
Table 3
Component matrix Concentration on work tasks Home Day 2
Item Nr.
Item
Component 1
31
,943
32
,933
33
,913
34
,746
58
Table 4
KMO and Bartlett’s Test for Concentration on work tasks Home Day 2
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
Sphericity
Approx. Chi-Square
324,123
df
6
Sig.
,815
,000
Table 5
Component matrix Concentration on work tasks Office Day 1
Item Nr.
Item
Component 1
31
.942
32
.938
33
.943
34
.708
Table 6
KMO and Bartlett’s Test for Concentration on work tasks Office Day 1
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
Sphericity
Approx. Chi-Square
409,426
df
6
Sig.
,815
,000
59
Table 7
Component matrix Concentration on work tasks Office Day 2
Item Nr.
Item
Component 1
31
,946
32
,932
33
,923
34
,696
Table 8
KMO and Bartlett’s Test for Concentration on work tasks Office Day 2
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
,816
Sphericity
Approx. Chi-Square
358,704
df
6
Sig.
,000
Table 9
Oblimin Pattern Matrix for Distractions Home Day 1
Factor
Item
7. In hoeverre werd u vandaag
tijdens uw werk afgeleid?
1
2
,596
,448
8. Gedachten gerelateerd aan
andere werkzaken dan de taken
waarmee u op dat moment bezig
was.
privé-zaken.
,828
,942
60
10. Bezigheden gerelateerd aan
werk, anders dan de taken
was.
privé-zaken.
,902
,970
Extraction Method: Principal Component Analysis.
Rotation Method: Oblimin with Kaiser Normalization.
a. Rotation converged in 5 iterations.
Table 10
Factor correlation matrix for Distractions Home Day 1
Factor
1
2
1
1,000
,411
2
,411
1,000
Table 11
KMO and Bartlett’s Test for Distractions Home Day 1
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
,752
Sphericity
Approx. Chi-Square
271,827
df
10
Sig.
,000
Table 12
Oblimin Pattern Matrix for Distractions Home Day 2
Factor
Item
1
2
,633
,391
61
was.
privé-zaken.
,787
,933
was.
privé-zaken.
,952
,900
Table 13
Factor correlation matrix for Distractions Home Day 2
Factor
1
2
1
1,000
,367
2
,367
1,000
Table 14
KMO and Bartlett’s Test for Distractions Home Day 2
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
Sphericity
Approx. Chi-Square
195,036
df
10
Sig.
,751
,000
62
Table 15
Varimax Rotated Component Matrix for Distractions Office Day 1
Factor
Item
1
2
,824
,448
was.
,866
privé-zaken.
was.
,850
,882
privé-zaken.
,888
Rotation Method: Varimax with Kaiser Normalization.
Table 16
Factor correlation matrix for Distractions Office Day 1
Factor
1
2
1
1,000
,287
2
,287
1,000
Table 17
KMO and Bartlett’s Test for Distractions Office Day 1
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
,710
63
Sphericity
Approx. Chi-Square
184,552
df
10
Sig.
,000
Table 18
Oblimin Pattern Matrix for Distractions Office Day 2
Factor
Item
1
,898
was.
,855
privé-zaken.
was.
2
,893
,909
privé-zaken.
,919
Extraction Method: Principal Component Factoring.
Table 19
Factor correlation matrix for Distractions Office Day 2
Factor
1
2
1
1,000
,497
2
,497
1,000
Extraction Method: Principal Component Factoring.
64
Table 20
KMO and Bartlett’s Test for Distractions Office Day 2
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
,779
Sphericity
Approx. Chi-Square
245,415
df
10
Sig.
,000
Table 21
Correlation Matrix Work-related Distractions Home Day 1
was.
was.
was.
1
,515
was.
,515
1
Table 22
KMO and Bartlett’s Test for Work-related Distractions Home Day 1
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
Sphericity
Approx. Chi-Square
34,672
df
1
Sig.
,500
,000
65
Table 23
Correlation Matrix Work-related Distractions Home Day 2
was.
was.
was.
1
,584
was.
,584
1
Table 24
KMO and Bartlett’s Test for Work-related Distractions Home Day 2
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
,500
Sphericity
Approx. Chi-Square
41,539
df
1
Sig.
,000
Table 25
Correlation Matrix Work-related Distractions Office Day 1
was.
was.
1
was.
,660
66
was.
,660
1
Table 26
KMO and Bartlett’s Test for Work-related Distractions Office Day 1
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
,500
Sphericity
Approx. Chi-Square
64,846
df
1
Sig.
,000
Table 27
Correlation Matrix Work-related Distractions Office Day 2
was.
was.
was.
1
,685
was.
,685
1
Table 28
KMO and Bartlett’s Test for Work-related Distractions Office Day 2
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
Sphericity
Approx. Chi-Square
,500
68,735
67
df
1
Sig.
,000
Table 29
Correlation Matrix Non-Work-related Distractions Home Day 1
privé-zaken.
privé-zaken.
privé-zaken.
privé-zaken.
1
,808
,808
1
Table 30
KMO and Bartlett’s Test for Non-Work-related Distractions Home Day 1
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
,500
Sphericity
Approx. Chi-Square
117,758
df
1
Sig.
,000
Table 31
Correlation Matrix Non-Work-related Distractions Home Day 2
privé-zaken.
privé-zaken.
privé-zaken.
privé-zaken.
1
,686
,686
1
Table 32
KMO and Bartlett’s Test for Non-Work-related Distractions Home Day 2
Kaiser-Meyer-Olkin
Measure of Sampling
,500
68
Adequacy
Sphericity
Approx. Chi-Square
62,599
df
1
Sig.
,000
Table 33
Correlation Matrix Non-Work-related Distractions Office Day 1
privé-zaken.
privé-zaken.
privé-zaken.
1
,550
privé-zaken.
,550
1
Table 34
KMO and Bartlett’s Test for Non-Work-related Distractions Office Day 1
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
,500
Sphericity
Approx. Chi-Square
40,845
df
1
Sig.
,000
Table 35
Correlation Matrix Non-Work-related Distractions Office Day 2
privé-zaken.
privé-zaken.
privé-zaken.
1
,644
privé-zaken.
,644
1
69
Table 36
KMO and Bartlett’s Test for Non-Work-related Distractions Office Day 2
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
Sphericity
Approx. Chi-Square
58,035
df
1
Sig.
,500
,000
Table 37
Component matrix Personal flexibility
Item Nr.
Item
Component 1
74
Een regelmatig levenspatroon bevalt
me het best.
,618
76
Ook bij onbelangrijke dingen moet ik
eerst nadenken voor ik wat doe.
,596
77
Als ik uit mijn dagelijkse regelmaat
word gehaald hindert mij dat.
,781
78
Ik houd er niet van een taak waar ik
mee bezig ben te onderbreken.
,615
80
Het kost me moeite om van een plan
af te wijken.
,726
81
Ik doe dingen vaak in een vaste
volgorde.
,773
70
Table 38
KMO and Bartlett’s Test Personal flexibility
Kaiser-Meyer-Olkin
Measure of Sampling
Adequacy
Sphericity
Approx. Chi-Square
168,081
df
15
Sig.
,809
,000
71
Appendix III. Exclusion of control variable Age
Table 39
Regression analysis Home day 1 with control variable Age
Age
Model 1
Model 2
.102
.073
Flexibility
-.043
Work Distractions
-.311***
Non Work Distractions
-.553***
R²
.010
R² Change
.525
.515***
Table 40
Regression analysis Home day 2 with control variable Age
Age
Model 1
Model 2
.041
.055
Flexibility
-.006
Work Distractions
-.173*
-.598***
R²
R² Change
.002
.461
.460***
72
Table 41
Regression analysis Office day 1 with control variable Age
Age
Model 1
Model 2
.177*
.117
Flexibility
-.034
Work Distractions
-.270***
-.456***
R²
.031
R² Change
.362
.331***
Table 42
Regression analysis Office day 2 with control variable Age
Age
Model 1
Model 2
.113
.100
Flexibility
-.032
Work Distractions
-.311***
-.486***
R²
R² Change
.013
.475
.462***
73
Appendix IV. Results of two-way ANOVA tests for each day separately.
Table 43.1
Univariate analysis of variance Home Day 1
Dependent variable: Concentration on work tasks
Group (work distractions - flexibility)
Mean
Std. Deviation
N
Low-Low
22,15
4,00
13
Low-High
20,84
3,96
44
High-Low
15,17
5,92
23
High-High
17,74
4,91
34
Sig
.050
Table 43.2
Group (non-work distractions - flexibility)
Mean
Std. Deviation
N
Low-Low
23,69
2,53
13
Low-High
21,06
3,78
48
High-Low
14,36
5,15
22
High-High
16,97
4,83
30
Sig
.004
74
Table 44.1
Mean
Std. Deviation
N
Low-Low
19,68
5,09
22
Low-High
21,47
4,79
34
High-Low
15,36
5,39
14
High-High
17,22
5,12
32
Sig
.973
Table 44.2
Mean
Std. Deviation
N
Low-Low
22,00
3,16
14
Low-High
21,59
4,49
37
High-Low
15,24
5,31
21
High-High
16,62
5,14
29
Sig
.374
75
Table 45.1
Univariate analysis of variance Office Day 1
Mean
Std. Deviation
N
Low-Low
22,38
4,10
8
Low-High
20,60
4,10
20
High-Low
17,20
4,82
30
High-High
17,47
5,48
58
Sig
.394
Table 45.2
Mean
Std. Deviation
N
Low-Low
20,93
5,50
14
Low-High
19,89
4,87
53
High-Low
16,75
4,23
24
High-High
14,84
4,62
25
Sig
.662
76
Table 46.1
Mean
Std. Deviation
N
Low-Low
19,82
3,30
17
Low-High
19,91
4,37
58
High-Low
13,45
4,81
20
High-High
14,63
4,79
16
Sig
.569
77
Appendix V. (Non-) significant results of the independent-samples t-test for equality of
means
Table 47.1
T-test for equality of means Home day 1(high work-related distractions – personal flexibility)
Concentration Home Day 1
Equal
variances
assumed
Sig.
t
df
Sig. (2-tailed)
.317
-1.777
55
,081
-1.714
41,295
,094
Equal
variances not
assumed
Note.
p<.05, one-tailed
Table 47.2
T-test for equality of means Home day 1(high non-work-related distractions – personal flexibility)
Equal
variances
assumed
Sig.
t
df
Sig. (2-tailed)
.727
-1.867
50
,068
-1.848
43,677
,071
Equal
variances not
assumed
Note.
p<.05, one-tailed
78
Table 48.1
T-test for equality of means Home Day 2 (high work-related distractions – personal flexibility)
Equal
variances
assumed
Sig.
t
df
Sig. (2-tailed)
,780
-1.118
44
,270
-1,095
23,736
,285
Equal
variances not
assumed
Table 48.2
T-test for equality of means Home Day 2(high non-work-related distractions – personal flexibility)
Equal
variances
assumed
Equal
variances not
assumed
Sig.
t
df
Sig. (2-tailed)
,971
-,926
48
,359
-,921
42,390
,362
79
Table 49.1
T-test for equality of means Office Day 1(high work-related distractions – personal flexibility)
Concentration Office Day 1
Equal
variances
assumed
Sig.
t
df
Sig. (2-tailed)
,283
,152
94
,880
,156
73,792
,876
Equal
variances not
assumed
Table 49.2
T-test for equality of means Office Day 1(high non-work-related distractions – personal flexibility)
Equal
variances
assumed
Equal
variances not
assumed
Sig.
t
df
Sig. (2-tailed)
,496
1,506
47
,139
1,509
46,899
,138
80
Table 50.1
T-test for equality of means Office Day 2(high non-work-related distractions – personal flexibility)
Equal
variances
assumed
Equal
variances not
assumed
Sig.
t
df
Sig. (2-tailed)
,662
-,730
34
,470
-,730
32,343
,470
81

Flexible workers: how about their distractions and concentration?

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