imitative suicides - The Odum Institute

IMITATIVE SUICIDES: A NATIONAL STUDY OF THE EFFECTS OF
TELEVISION NEWS STORIES*
KENNETH A. BOLLEN
DAVID P. PHILLIPS
Dartmouth College
University of California at San Diego
A 1974 ASR paper by Phillips showed that suicides increase in the month of highly
publicized suicide stories. Several subsequent papers have built on this finding and
have suggested that publicized suicide stories trigger increases in covert suicides
disguised as motor vehicle or airplane accidents. If the original ASR findings cannot
be replicated, then doubt is cast on all these studies. In this paper we demonstrate
that U.S. daily suicides increase significantly after highly publicized suicide stories
appear on television evening news programs. We provide the first evidence that the
increase in suicides occurs only after and not before the suicide story. In addition, we
provide the first systematic study of the length of time a suicide story affects suicides;
the effect probably does not extend beyond ten days. These findings support and
extend the literature on imitative suicides.
In the early twentiethcenturyDurkheimand
Tardeconducteda famousand bitterdebateon
the relativeimportanceof imitation.,Durkheim
([1892] 1964, [1897] 1966) claimed that imitation did not significantlyaffect "social facts" in
generalor suicide rates in particular.' His view
is sharedimplicitly,if not explicitly,by modern
sociologists, who have almost entirely ignored
the topics of imitationand suggestion.
In contrast to sociology, other disciplines
have continuedto displaya vigorousinterestin
the topics of imitation and suggestion. Psychologists have conducted more than 2,000
studies of the imitationof violence in the mass
media (reviewed in Surgeon General, 1972;
NIMH, 1982;Comstock, 1975;Comstock and
Fisher, 1975; Comstock and Lindsey, 1975;
Gordon and Verna, 1978; Liebert and
Schwartzberg, 1977; Hearold, 1979; Wilhoit
andde Bock, 1980;Robertsand Bachen, 1981).
Economists and market researchershave examinedthe impact of imitationand suggestion
in advertising (Dirksen and Kroeger, 1973;
Michmanand Jugenheimer,1976;Sandageand
*Directall correspondenceto: KennethA. Bollen,
Department of Sociology, Dartmouth College,
Hanover, NH 03755.
This researchwas carriedout while Bollen was at
GeneralMotorsResearchLaboratories.We wish to
thank a numberof individualswho aided the completionof this project.CraigPalmerandTom Laffey
providedcomputerprogramming.Useful comments
on earlierversions of the paper were given by Ken
Barb and Greg Cermak. Marilyn Southern typed
severaldraftsand the final versionof the paper.The
Inter-universityConsortiumfor Politicaland Social
Research suppliedthe mortalitydata.
1 For a useful introductionto Durkheim'sdebate
with Tardeon this issue, see Clark(1969, especially
pp.7-18, "ConflictingIntellectualCurrents:Tarde,
Durkheim,and Sociology").
802
Fryburger, 1975; Engel et al., 1973; Jacoby,
1976).
Sociological interest in imitation has been
revived, particularlyin recent work on overt
and covert imitativesuicides. The first of these
studies by Phillips (1974) showed that (1)
monthly U.S. suicide rates increased in the
month of a front-page suicide story; (2) the
greater the publicity devoted to the suicide
story, the greaterthe increase in suicides; and
(3) the increase in suicides occurredmainly in
the geographic areas receiving the publicity.
These findings persisted after seasonal and
time trend corrections, and suggested that
suicide stories triggerimitative suicides.
A series of papers on covert or disguised
suicidesfollowed. These studies suggestedthat
some imitative suicides are disguised as accidents. Phillips (1977, 1979) showed that daily
Californiamotor vehicle fatalities (MVP) increased significantly following front-page
suicide stories. Bollen and Phillips (1981)
replicated this finding for Detroit. Phillips
(1978, 1980)also showed that daily U.S. noncommercialairplanecrashes increased significantly after highly publicized murder-suicide
stories. All of these studies controlledfor seasonal fluctuations and trends. Most of the
studies also found that the greater the publicity devoted to a story, the greaterthe increase
in mortality,and that the increases in mortality
occurred primarily in the geographic areas
where the suicide stories were most publicized.
Confidence in this chain of investigations
dependsupon the validityof the findingsin the
original suicide study (Phillips, 1974). There
are at least two reasons for viewing this study
with caution. First, the research has not been
replicated.At present, we know only that the
results in the originalpaper hold when a particular time period (1947-1968) is examined
AmericanSocological Review 1982, Vol. 47 (December:802-809
IMITATIVE SUICIDES
with a relatively unconventional, quasiexperimentalanalytic technique. These original findings need to be replicatedfor another
time period with another, more conventional
statistical technique.
A second reason for reservingjudgmenton
the validityof the originalsuicide study is that
its findings are based on monthlyratherthan
daily data. This study showed that U.S.
suicides increasedin the calendarmonthwhich
contained a publicized suicide story Because
this findingis based on monthlydata it leaves
open the possibility that suicides increased in
the few days prior to the publicized suicide
story, as well as just afterwards. If daily
suicide data revealed that U.S. suicides rise
immediatelyprior to a suicide story, then the
findings in the original suicide study would
have to be substantiallyreinterpreted.And,
because this study forms the foundationof all
subsequentstudies in the area, they too would
need to be reinterpreted.In sum, a replicative
study using daily suicide data has the potential
to support or undermine a growing body of
research whose reliability has not been seriously questioned
In the following sections, we use a quasiexperimental technique as well as a conventional regressionanalysis to examine U.S.
daily suicides, 1972-1976. We seek to determine: (1) whetherit is possible to replicatethe
originalfindingof a rise in U.S. suicides after
publicized suicide stories, (2) whether the increase in suicides occurs only after a suicide
story and not before, and (3) how long the rise
in suicides persists after the appearanceof a
suicide story.
DATA SOURCES
Mortality Data
We obtained detailed U.S. daily mortality
statistics, 1972-1976, from the InterUniversity Consortiumfor Politicaland Social
Research; this organization,in turn, had acquiredthe data from the U.S. NationalCenter
for Health Statistics. These high-qualitydata
provide the basis for all federal mortality
statistics.3
2 Phillips's method of analyzing his monthly data
(1974:343) does not eliminate this possibility, though
it does render it unlikely.
I The International Classification of Diseases
category of "Suicide and self-inflicted injury"
(E950-E959) was used to select the suicide deaths
from the master tape. Our data set covers the period
1972-1976 because U.S. computerized mortality
data were not available outside of this time period
when we conducted our study.
803
Data on Television Coverage of Suicide Stories
Previous research has relied on newspaper
stories for publicitymeasures.Newspapersare
well suited for the study of city or state areas
but less feasible for nationalstudies. The major
problemis the developmentof a nationallyrepresentative sample of papers that have publically available subject indices with which
front-pagesuicide stories may be located. Although major papers (e.g., the New York
Times) have such indices, these newspapers
are not representativeof all U.S. newspapers.
Television news programs are a desirable
alternative source for publicity measures for
several reasons. First, more so than any newspaper, television news reaches a nationalaudience. Second, television news is the major
source of news for many Americans.A practical advantage is that a subject index for the
eveningnews is availablefor the time periodof
this analysis. Thus, television news stories
providea useful exploratorytest of the national
response to publicized suicides.4
The Vanderbilt Television News Index (Joint
University Libraries, 1972-76) was searched
under the topic heading "suicide" for all
suicide stories carried on two or more of the
networkevening news programs(presentedby
ABC, CBS, and NBC). We considered only
stories about specific individualsuicides; we
omitted stories discussing the general suicide
rate or trends in that rate, because abstract
storiesof this type are presumablynot likely to
triggerimitative suicides.5
METHODS OF ANALYSIS
To providea meaningfulanalysis,the effects of
suicide stories must be disentangledfrom the
effects of other, extraneous variables. This
"disentangling"was accomplishedin two different ways. First, we conducted a brief, ex4 One disadvantage of this national publicity measure is that it does not allow us to examine easily
whether areas receiving the greatest publicity have
the greatest suicide response to the publicity. Newspaper publicity measures do have this advantage
over television measures.
5 We also eliminated stories that occurred too near
a public holiday; this was necessary in order to separate the effects of suicide stories from the effects of
holidays on suicides. Following the same procedure
used by Bollen and Phillips (1981), we eliminated a
suicide story, if (1) a holiday falls 0-6 days after the
publicized suicide, or (2) a holiday falls 0-4 days
before the publicized suicide. If multiple stories occurred within a week, only the most recent story date
was used. Finally, if the actual suicide was a number
of years before the reporting of it, the story was
dropped since people may not identify with such
"historic" cases.
804
AMERICAN SOCIOLOGICAL REVIEW
Table 1. U.S. Suicides in Week Following Suicide Stories Publicized on Two or Three of the Major
Television Network Evening News Programsa
(1)
Date of
Publicized
Suicideb
(2)
Suicides in
Experimental
Period
(3)
Suicides in
Control
Period
(4)
Difference Between
Experimentaland Control
Period Suicides
April 25, 1972
554
444
110
June 4, 1973
528
93
435
487
514
September11, 1973
-27
20
482
462
July 15, 1974
21
April 11, 1975
593
572
52
553
501
September3, 1975
May 13, 1976
-25
550
575
244
TOTALS
3747
3503
a The experimentalperiodis definedas the day of the publicizedsuicide and the six
days followingit. For
definitionof control period see the text.
b
In chronologicalorderthe suicide storiesare on the followingindividuals:G. Sanders(actor),E. Brudno
(ex-POW),S. Allende(presidentof Chile),C. Chubbuck(talk-showhostess), E. Black(corporateemployee)
and J. Howe (husbandof B. Ford's private secretary), USSR airplanecrewman, and D. McRae (Virginia
man).
ploratoryanalysis, using a quasi-experimental
design, in which an experimental period is
comparedwith a matchedcontrol period. Second, we conducted a more thorough,systematic analysis, using a conventional regression
analysis to control explicitly for potentially
confoundingvariables.
Quasi-Experimental Analysis
As we noted earlier, no previous research has
studiedthe fluctuationof daily suicides around
suicide stories. Thus, at the startof this study,
we could not be certainon which days, if any,
suicides would increase. We initially defined
the experimental period as the entire week
after the publicizedsuicide, ratherthan as any
particularday. Later in this study daily figures
will also be used.
To determine whether the number of
suicides in the experimentalperiodis unusually
high, we comparethis numberwith the number
of deaths in a matchedcontrol period. In general, the controlperiod is the week priorto the
experimentalperiod.6 The following example
illustratesour procedure.ChristineChubbuck,
a television talk show hostess, shot herself
while on the air on Monday,July 15, 1974.The
experimentalweek is from Monday,July 15 to
Sunday, July 21. The control period is from
Monday, July 8 to Sunday, July 14.
Table 1 describes the numberof suicides in
the experimentalweeks and in matchedcontrol
weeks. A positive number in column 4 indicates that more suicides occur in the experimental period than one would expect from
6 The only exception to this rule occurs when the
control period contains a holiday. In this case, the
first precedingweek that is free from holidayeffects
is used as the control period.
controlperiodmortality.It is evident that U.S.
suicides generallyincrease in the week after a
publicized suicide story (p=0.068; t = 1.725,
6 d.f.; one-tailed t-test for matched pairs).
Overall,U.S. suicides increasedby 7.0 percent
after suicide stories.
In the above analysis we have aggregated
suicide statistics for the entire week following
the suicide story. We have not examined the
increase in suicides for each day separately.
Table2 presentsthis type of daily analysis. The
increasein suicides is greatestfor the sixth day
(12.3%)and next greatest for the second day
(9.5%). On most of the other days examined,
the increasein suicides is small but not negligible. In short, suicides do not produce a single
peak; rather,the increase in suicides is spread
over the week following the publicizedsuicide
story. Overall, for the entire week, suicides
increaseby about35 (i.e., 244/7)afterthe average suicide story.
Our exploratory, quasi-experimental
analysis of the suicide data suggests that publicized suicides trigger additional suicides.
However, this approach, though simple and
convenient, is not very powerful, because it
does not utilize all the informationavailablein
Table 2. Absolute and Percentage Increase in U.S.
Suicides on Day of Publicized Suicide and
in the Following Six Days
Day
0
1
2
3
4
5
6
Absolute Increase
(Experimental-Control)
Percentage
Increase
28
35
45
32
35
6
63
5.2
6.8
9.5
6.7
7.4
1.1
12.3
IMITATIVESUICIDES
the data. For example, this technique compares only one control period with each experimentalperiod, thus producinghighly variable estimates of the number of dead to be
expected in each experimentalperiod.
An alternative, more powerful approach,
based on regressionanalysis, implicitlyuses a
number of control periods for each experimental period. With an increased number of
control periods, idiosyncratic fluctuations in
any one controlperiodno longerpose a serious
problem. An additionalbenefit of regression
analysis is that it allows us to attack certain
problems not easily investigated with the
quasi-experimentalapproach.For example, we
use regression procedures to determine how
long the effect of a story lasts.
REGRESSIONANALYSIS
Effect of a Suicide Story X Days After
Appearance of the Story
Our regression analyses use dummy variables
to control for the potentially confoundingeffects of day of the week, month, year, and
holidays. For instance, to control the dayof-the-week effects, a 0-1 variable is coded
for all days that are Mondays,anotherdummy
variablefor Tuesday, etc., with Sundaybeing
the omitted category. With the seasonal and
holiday factors included as explanatoryvariables, the estimates of the publicized suicide
effects are net of the influences that, say, a
particularday of the week, month,or year may
have on suicides.
A dummyvariable,STORY(X),is also used
to indicate the occurrence of a publicized
suicide. The regression coefficient for
STORY(X)gives the effect of a suicide story
on suicides X days later (i.e., the effect of
STORYlagged X days). Initially,our analysis
will be restrictedto ten days after the story. In
a later section, we will relax this restriction.
Table3 presentsour regressionresults.7This
'We tested for autocorrelationof the regression
residuals.The usualDurbin-Watsontest for autocorrelationis not appropriatewhen a laggedendogenous
variable-SUICIDE(I) in our model-is used in a
regression (Nerlove and Wallis, 1966). However,
Durbin(1970) has devised two alternativetests for
equations with lagged endogenous variables. Durbin's h test requiresthat (I -N(VAr(a))be positive,
where N is the numberof cases and Var(a)is the
estimated variance of the coefficient of the lagged
endogenousvariable(Durbin,i970:418).This is not
true for our model. A two-step alternativetest describedby Durbin(1970)was used instead.The first
step is to computethe residuals,e, fromthe ordinary
least-squaresregression. Next, regress e(0) on e(1)
and the other explanatoryvariables in the original
equation.The significanceof the coefficient for the
e(l) variable is a test of autocorrelation.Applying
this test we find a coefficient of 0.0581 with a stan-
805
Table 3. SUICIDES Regressed on Publicized
Suicide Story, Controlling for Daily,
Monthly, Yearly, and Holiday Effects for
U.S., 1972-1976
Regressand
R2
R2
F
Degrees of
Freedom
N
SUICIDES
0.168
0.150
9.2
39, 1777
1817
Regressor
Regression Coefficient
t-statistic
Intercept
64.93*
0.07*
6.28*
6.03**
1.93
0.73
-0.05
1.30
7.65*
8.03*
-0.16
0.58
-4.34
6.81*
1.11
0.83
-0.07
0.41
-1.44
1.39
3.60*
4-37*
5.60*
3.31*
2.26*
3.32*
3.94*
2.39*
0.41
-0.88
-5.08*
-4.35*
-2.80*
0.67
5.43
-9.19*
-2.41
-6.96*
-5.07*
-0.01
33.08
2.92
1.66
1.60
0.51
0.19
-0.01
0.34
2.03
2.12
-0.04
0.15
-1.15
7.79
1.24
0.94
-0.08
0.47
-1.65
1.18
3.13
3.73
4.65
2.84
1.93
2.87
3.29
2.08
0.34
-0.75
-6.77
-5.85
-3.80
0.92
1.62
-3.84
-0.71
-3.00
-2.34
-0.00
SUICIDE(1)a
STORY(0)
STORY(l)
STORY(2)
STORY(3)
STORY(4)
STORY(5)
STORY(6)
STORY(7)
STORY(8)
STORY(9)
STORY(10)
Monday
Tuesday
Wednesday
Thursday
Friday
Saturday
February
March
April
May
June
July
August
September
October
November
December
1972
1973
1974
1975
New Years
Memorial Day
July 4
Labor Day
Thanksgiving
Christmas
a
Suicides lagged one day.
* Significant at 0.05 level or better, one-tailed
t-test.
** Significant at 0.055 level.
darderrorof 0.1973.Thus, the coefficientis less than
a thirdthe size of its standarderrorand is clearlynot
statistically significant. The possibility of higher
order autocorrelationwas less formally considered
by examiningthe correlogramof the residualsfrom
the regression. Strictly speaking these correlations
are not-fullyaccuratebecause the residualsare computed from an equation with a lagged endogenous
variable.But this methodwould suggest a potential
problem if fairly large correlations (say 0.2 or
greater)occurred.The largestcorrelationwas about
0.1, which was deemed negligible.
806
table reveals that suicides peak twice after a
publicizedsuicide story. The first peak occurs
on the day of the publicizedstory and the day
after(lags 0 and 1), and the second peak occurs
on the sixth and seventh days after the story
(lags 6 and 7). If we sum these four significant
coefficients,
[STORY(0), STORY(1),
STORY(6),and STORY(7)],we obtain an estimate of the net increase in suicides in the
week following the "average" suicide story.
When this is done, we find an increase of
nearly 28 suicides for each story.8
These STORY coefficients are sufficiently
large to have substantive importanceand not
just statistical significance. One way to assess
this importanceis to compare the size of the
STORYcoefficients with the size of the other
coefficients in Table 3. Combined,the STORY
coefficients are greater than any day-ofthe-week, month, year, or holiday effect.
When considered individually,the significant
STORY coefficients are generally largerthan
the coefficients for the other variables. For
example, each of the four STORY
coefficients-STORY(0),
STORY(1),
STORY(6),STORY(7)- is largerthan any of
the monthly or yearly effects. The largest
day-of-the-week effect is for Monday, when
an increase of 6.81 suicides is expected. This
coefficient is smaller than the coefficients for
STORY(6)[= 7.65] and STORY(7)[= 8.03]
and is only slightlylargerthan the coefficients
AMERICAN SOCIOLOGICAL REVIEW
A Test for Spuriousness
In this paper and in the literatureit has been
assumed that the increase in suicides after a
suicide story is in some way triggeredby the
appearance of that story. This assumption
would have to be discarded if it is found that
suicides increaseprior to suicide stories.
We tested this assumption in the following
way. In additionto the variableslisted in Table
3, we introducedlead terms, STORY(+X), designed to estimate the effect of a story X days
beforethe appearanceof that story. The results
of this regression show that suicides do not
increase prior to the appearanceof a suicide
story. Half the STORY(+X) coefficients are
positive and half are negative. None of the
coefficients is statistically significant at the
0.05 level. The same conclusion is reached if
the regression equation is rerun, with the
lagged variables, STORY(X),removed.
How Long Does the Effect Last?
Systematicestimates of the durationof suicide
story effects have not been provided previously in the literature.Until now, our analyses
have been restrictedto a ten-day period. Several procedures can be employed to discover
whether the effect of a suicide story lasts beyond the tenth day. For example, the coefficient for STORY(X)can be calculated for increasingly large values of X. However, this
approachis complicatedby the fact that, when
for STORY(0) [= 6.28] or STORY(l) [= 6.03].
In sum, suicide stories generallyhave a larger many values of X are examined simultashort-termeffect on suicides than do the other neously, some coefficients will be statistically
significantby chance alone. For examplewhen
extraneous variablesconsidered.9
our analysis was extended to X = 250, statistically significantcoefficients would still occa8 If the criterion of a 0.05 level of significance is
sionally emerge.
strictly applied, STORY(l) with p = 0.055 would fail
The difficultyof identifyingsignificantcoefto meet this standard. In this case the increase in
ficients is compoundedby the fact that suicide
suicides based only on "statistically significant"
coefficients would be estimated at about 22 in the
stories do not have a smoothly diminishing
week after each publicized suicide.
effect over time. For instance, in the case of
9 Although the effect of any given suicide story is
suicidal motor vehicle fatalities, previous requite large compared with seasonal effects, the
search (Phillips, 1979; Bollen and Phillips,
cumulative effect of all suicide stories combined is
1981)found a sharp "spike" in motor vehicle
not large compared with the cumulative effect of all deaths three days after a suicide story, with no
seasonal factors combined. This is because heavily
significantincreases immediatelysurrounding
publicized suicide stories occur only rarely. Also,
some of the other results in Table 3 deserve ad- this spike. With such a pattern one might
ditional comment. First, note that suicides are much plausibly find a second or third spike many
higher on Monday than on any other day of the days later without significant coefficients inweek. Suicides are most frequent in March through tervening.'0
October, with the highest suicide levels occurring
from April to May. The smallest number of suicides
occurred in 1972-1974, while the level of suicides
was about equal in 1975 and 1976. Finally, suicides
decrease markedly on all holidays (except for New
Year's Day). This finding is consistent with results in
an earlier study (Phillips and Liu, 1980). A detailed
comparison of the temporal variations in suicides
and motor vehicle fatalities is in Bollen (forthcoming).
10 This erratic lag structure also rules out the use
of some of the more common distributed lag
structures developed in econometric research (see,
e.g., Maddala, 1977:355-89; Griliches, 1967). Most
of these econometric techniques assume a rather
smooth lag structure. For instance, the Koyck
scheme assumes a geometric decline in effects while
the Almond lag technique assumes that a polynomial
can be used to approximate the lag pattern. In addi-
IMITATIVE SUICIDES
807
Table 4. Incrementin the ExplainedVariance(R2)of Suicide with Additionof Lagged Variables
Equation
R2
Lagged Variables
(1)
0.1727
STORY(O)-STORY(10)
(2)
0.1766
STORY(0)-STORY(20)
(3)
STORY(0)-STORY(30)
0.1802
(4)
STORY(0)-STORY(60)
0.1969
(5)
STORY(0)-STORY(100)
0.2225
a
None of the F-values is statisticallysignificantat 0.05 level.
ComparedEquations
F-Valuea
(2) to (1)
(3) to (1)
(4) to (1)
(5) to (1)
0.797
0.762
0.988
1.137
--
After considering several procedures, we vides no evidence that suicide stories affect the
adopted two techniques for estimatingthe du- level of suicides for more than ten days.
ration of suicide story effects: (1) Replication
In summary, the replicationtechnique provides some evidence that the effect of a suicide
Technique, and (2) F-test.
story mayextend beyond the tenthday, but the
F-test does not supportthis finding. In the abReplication Technique
sence of additionaldata, it seems safest to conThe same regressionswere run for the U.S. clude that the suicide stories exert all or almost
data under analysis here and for earlier all of their effect within the first ten days.
Californiadata (takenfrom Phillips, 1979).We
sought to determinewhether suicides peaked
significantlyon the same day in both data sets. SUMMARYAND DISCUSSION
If simultaneouspeaks were found on, say, the Our empiricalfindings provide:
20thday in both data sets, then one wouldhave
(1) a replicationof a key finding-the rise in
some evidence that the effect of a suicide story
overt suicides after a publicized suicide
lasts for 20 days.
story,
For each data set, the variables,
(2) the first evidence that this rise occurs
STORY(0)-STORY(100),were included in a
after and not before the suicide story,
regressionequation. The choice of 100 days is
(3) the first systematic investigation of the
arbitrary,but if evidence of a significantpeak
length of time a suicide story affects
is found in both data sets on, say, the 99th day,
mortality.
the analysis could be extended beyond the
These findingsbuttressthe generalliterature
100th day. This turned out to be necessary. on imitative suicides. The key results in this
Beyond the 10th day, only STORY(31) and literature are now replicated, both for overt
STORY(75) were statistically significant in suicides (Phillips, 1974,and this paper)and for
both data sets. These results suggest that the covert suicides (Phillips, 1977, 1979, 1982;
effect of a publicized suicide might extend as Bollen and Phillips, 1981).Taken together, all
far as the 75th day. However, the evidence of these findings support the hypothesis that
fromthe F-test does not supportthese findings. publicized suicides triggerimitative behavior;
sometimesthis behavioris overt (in the formof
an explicit suicide) and sometimes covert (in
the form of automobileor airplaneaccidents).
F-test for Statistical Significance
Up to now we have been using the word
In this procedure, we use an F-test (Nam- "imitation" as a global, descriptive term,
boodiri et al., 1975: Part I) to determine meaning the performance of an act after a
whether there is a significantincrementin ex- similaract has been modeled by another perplained variance when the lagged coefficients son. We have not tried to speculate on the
are extended beyond the tenth day. In other psychosocialprocesses that underlieimitation.
words, we test whether the goodness of fit of Now that some majorfindingsin the literature
the regression equations is significantly im- have been replicated, it seems appropriatefor
proved as we add STORY(I1)-STORY(30), researchersto begin to examine the detailed
STORY(11)-STORY(60), or STORY(11)- individualprocesses leading to imitation.
STORY(100)to the equation.
The analyses to date have been based on
Table 4 presents the appropriateF-statistics macro mortality data. This has limited us to
and indicates that there is no statistically sig- studying aggregate responses to publicized
nificant increment in explained variance be- suicides. Futureresearchmightprofitablyturn
yond a lag of ten days. Thus, this table pro- from macroanalyses to micro studies of imitation. For example, it would be valuable to
tion, manyof these techniquesrequirethe researcher study case historiesof individualswho commit
to specify the durationof the effect, andthis begs the suicide after a publicizedsuicide to determine
in what respects they differ from individuals
question we are seeking to answer.
808
dying in a time period without publicized
suicides. This type of study would require
interviewswith friends and relativesof the deceased and is only feasible for smallgeographical areas. However, such intensive case
studies should provide a great deal of information on the imitationprocess.
Anotherphenomenonthat may be better explainedwith microanalyses is the double peak
in deathsaftera publicizedsuicide story. Many
of the macroanalyses in the literaturesuggest
that two groups of "imitators" may existthose who respond early to the suicide story
and those who respond late. In this paper, for
example, suicides peak on days 0,1 and then
again on days 6,7. The California study of
motorvehicle fatalitiesshows a doublepeak on
day 3 and on day 8 while a similardouble peak
exists for airplane accidents following publicized suicides.
The early respondersin the firstpeak may be
more impulsive and may have already contemplatedsuicide, even before the example of
the publicized suicide occurred. For these
early responders, the publicized suicide may
serve merely to precipitatea death that would
have occurredeven in the absence of the publicized suicide. In contrast, late responders
may make a less impulsive, more considered
response to the publicizedsuicide. These persons may not have contemplatedsuicide prior
to the example of the publicized suicide.
The findings cited above also indicate that
the early suicide peak precedes the early auto
accident peak, and the late suicide peak precedes the late auto accident peak. Thus, persons dying by suicide seem to react more
quicklyto the publicizedsuicide story than do
persons dying in auto accidents. This pattern
may occur because persons dying in an overt
suicide are less conflicted and ambivalentthan
persons dying in a covert suicide, e.g., one
disguised as an automobileaccident. The ambivalence of the covert suicide may result in a
period of indecision and thus in a delayed response to the suicide story. It is also possible
that disguised suicides requiremore planning,
and hence more time, than overt suicides. Future research is needed'to test these conjectures and to generate new ones.
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