ArticlePDF Available

Interaction Domains and Suicide: A Population-based Panel Study of Suicides in Stockholm, 1991-1999

Authors:

Abstract and Figures

This article examines how suicides influence suicide risks of others within two interaction domains: the family and the workplace. A distinction is made between dyad-based social-interaction effects and degree-based exposure effects. A unique database including all individuals who ever lived in Stockholm during the 1990s is analyzed. For about 5.6 years on average, 1.2 million individuals are observed, and 1,116 of them commit suicide. Controlling for other risk factors, men exposed to a suicide in the family (at work) are 8.3 (3.5) times more likely to commit suicide than non-exposed men. The social-interaction effect thus is larger within the family domain; yet work-domain exposure is more important for the suicide rate because individuals are more often exposed to suicides of coworkers than family members.
Content may be subject to copyright.
Interaction Domains and Suicide: A Population-based Panel Study
of Suicides in Stockholm, 1991-1999
Peter Hedström
Liu Ka-Yuet
Monica K. Nordvik
Social Forces, Volume 87, Number 2, December 2008, pp. 713-740 (Article)
Published by The University of North Carolina Press
DOI: 10.1353/sof.0.0130
For additional information about this article
Access Provided by Columbia University at 08/31/10 11:00PM GMT
http://muse.jhu.edu/journals/sof/summary/v087/87.2.hedstrom.html
Interaction Domains and Suicide: A Population-based
Panel Study of Suicides in Stockholm, 1991-1999
Peter Hedström, Singapore Management University and University of Oxford
Ka-Yuet Liu, Columbia University
Monica K. Nordvik, Stockholm University
is article examines how suicides inuence suicide risks of others
within two interaction domains: the family and the workplace. A
distinction is made between dyad-based social-interaction eects
and degree-based exposure eects. A unique database including
all individuals who ever lived in Stockholm during the 1990s is
analyzed. For about 5.6 years on average, 1.2 million individuals
are observed, and 1,116 of them commit suicide. Controlling
for other risk factors, men exposed to a suicide in the family (at
work) are 8.3 (3.5) times more likely to commit suicide than non-
exposed men. e social-interaction eect thus is larger within
the family domain; yet work-domain exposure is more important
for the suicide rate because individuals are more oen exposed
to suicides of coworkers than family members.
As Bearman (1991) noted, an important insight in Durkheim’s classic
study of suicide was his recognition that the structure of social relations
is important for explaining variations in suicide rates. These insights were
only partly explored in Durkheim’s own work, however, and lack of relevant
data means that we still know far too little about how the social structures
in which individuals are embedded inuence their suicide risks and the
suicide rates in society at large.
In this article we focus on one specic aspect of this: how suicides
among those with whom a focal individual interacts inuence his/her
own suicide risk, and how such processes are conditioned by the social
structures in which they take place. Although we are primarily interested in
the structural aspects of suicides, we will pay a great deal of attention to
individual-level processes. Such processes are essential for understanding
why we observe what we observe, and when it comes to empirically
is research has been supported by grants from e Swedish Council for Working Life
and Social Research and the NEST/Path Finder initiative of the European Community, the
DYSONET and MMCOMNET projects. We wish to thank Yvonne Åberg, Peter Bearman,
Francois Collet, Fredrik Liljeros and the referees for their useful comments. Direct
correspondence to Peter Hedström, School of Social Sciences, Singapore Management
University, Singapore 178903, e-mail: phedstrom@smu.edu.sg, or Nueld College, New
Road, Oxford OX1 4RB, United Kingdom, e-mail: peter.hedstrom@nueld.ox.ac.uk.
© The University of North Carolina Press Social Forces 87(2), December 2008
714 • Social Forces 87(2)
assessing the importance of network effects it is essential to control for
potentially confounding individual-level factors.
Our approach thus differs from what in the suicide literature is often
referred to as a “sociological” or “Durkheimian” approach to suicide
research, an approach that focuses on associations between suicide rates
in different population groups and various properties of these groups.
1
Methodological developments during the past few decades as well as
the increased availability of data sets with detailed information on the
individuals at risk and their local social environments, allows for more
precise analyses of the social-structural aspects of suicide. Rather than
focus exclusively on macro-level patterns, we focus on the links between
micro and macro, i.e., on how individuals’ suicide risks are affected
by characteristics of their social environments, and on how the social
domains in which suicides take place inuence the extent to which others
are exposed to and inuenced by them.
As will be discussed below, a range of studies suggest that exposure
to the suicide of another person is likely to increase the suicide risk of the
exposed individual. The data used have not always been ideal, however.
Ecological studies have the shortcoming of not adequately controlling
for individual-level risk factors, and in most ecological studies it is not
known who has actually been exposed to the suicide of another person
(Baron and Reiss 1985). With their small sample sizes and cross-sectional
designs or short follow-up periods, many individual-level analyses lack the
power to detect how suicides affect the suicide risks of others.
We have access to a unique Swedish database that allows us to
overcome some limitations of previous studies. The database is a panel
including all adults who ever lived in the greater Stockholm metropolitan
area during the 1990s. It includes detailed socio-demographic information
on all these individuals, including causes of death for all who died during
this period of time. In addition, and of crucial importance for this study, it
contains information that allows us to identify co-workers, relatives and
family members of a suicide.
The article also makes a theoretical contribution by highlighting the
importance of two types of network effects: a dyad-based social-interaction
effect and a degree-based exposure effect. We show that focusing on one
of these effects at the expense of the other can easily lead to a biased
understanding of the role that networks play in explaining suicide rates
and other macro-level outcomes.
Network Eects
Suicide risks have been linked to a range of medical and biological factors
including various psychiatric disorders and personality characteristics (see
Interaction Domains and Suicide • 715
Jacobs, Brewer and Klein-Benheim 1999). Although such factors typically
operate “behind the back” of the individuals, suicide researchers such as
Shneidman (1969) have long suggested that suicide should be seen as a
purposeful act aimed at solving one’s problems. It is useful to explicitly
analyze suicides as intentional actions because by adopting an action
perspective we are better positioned to understand the mechanisms
through which interactions with others are likely to inuence a focal
individual’s suicide risk (see also Michel and Valach 1997).
Actions have been conceptualized and analyzed in numerous ways,
but a common denominator among most of these approaches is a view
according to which actions are seen and analyzed as a joint product of
reasons and opportunities.
2
As suggested by Davidson (1980), Elster (1983)
and others, the cause of an action can be seen as a specic constellation of
desires, beliefs and opportunities in the light of which the action appears
reasonable and understandable. Beliefs and desires are mental events that
can be said to cause an action in the sense of providing reasons for the
action; they have a motivational force that allows us to understand and, in
this respect, explain the action.
As illustrated in Figure 1, to the extent that the suicide of one person
(“Individual i”) inuences the suicide risk of another person (“Individual j”),
this inuence must be mediated via the beliefs, desires or opportunities of
the latter person (see also Hedström 2005). In order to better understand
why and when network effects are likely to be important, it is essential to
specify clearly the mechanisms that are likely to be at work (see Hedström
and Swedberg 1998 for a general argument to this effect).
One belief-based interaction mechanism that has received some attention
is concerned with how exposure to the suicide of another person may change
the focal person’s beliefs about how others are likely to react were he to
commit suicide. For example, if a suicide generates considerable sympathy
towards the deceased individual, this may change the focal person’s beliefs
about how others are likely to react to his suicide in such a way that he
Figure 1. Suicide-Exposure Eects from an Action-eory Perspective
Figure 1. Suicide-Exposure Effects From an Action-theory Perspective
Risk that Individual j
Decides to Commit
Suicide
Beliefs of Individual j
Desires of Individual j
Opportunities of
Individual j
Suicide of Individual i
716 • Social Forces 87(2)
becomes more prone to commit suicide (see Cutler, Glaeser and Norberg
2001; Hankoff 1961). The mechanism is exemplied by the remark made
by a 13-year-old boy during the funeral of someone who committed suicide:
“How nice it would be to have all those people crying and making a fuss
over me.” (Hezel 1985:120)
3
It is this mechanism that explains why most
media guidelines suggest that “glorication” of suicide and sensational
mass media reporting should be avoided (CDC 1994; WHO 2000).
Suicides of others may also inuence the focal person’s beliefs about
his ability to commit suicide. As we know from research within numerous
other areas of life, the availability of social models is one key source of
self-efcacy (Bandura 1994). Seeing that people similar to ourselves
succeed in performing a particular type of action tends to strengthen our
beliefs in our own ability to perform the same type of action. According
to Linehan et al. (1983), for example, such beliefs (what they refer to as
“courage”) are important for explaining why some suicidal individuals, but
not others, decide to take their own lives. Thus, the suicides of others
may increase the focal individual’s suicide risk by changing the focal
person’s self-efcacy beliefs.
Desire-related interaction mechanisms also are likely to be of importance.
In almost every culture, there is a strong normative pressure against
committing suicide (Farberow 1975).This may dissuade some individuals
from committing suicide who in another normative context would have
done so. In most areas of life, such normative pressures tend to be density
dependent in the sense that the strength of the normative pressure against
doing X is a negative function of the number of other people already doing
X (see Hedström 2005). This implies that an increased exposure to the
suicides of others will reduce the normative pressure against committing
suicide, thereby increasing the suicide risk.
In addition to these belief- and desire-related interaction mechanisms,
it also seems important to consider so-called “trigger mechanisms” or
events that change the cognitive status of an action alternative from being
a mere theoretical possibility to a consciously reected upon alternative.
4
As argued by Åberg (2003), each day of our lives we are faced with an
almost innite number of possible action alternatives, but we consciously
reect upon only some of them. In order to explain why individuals do
what they do, it is often essential to take into consideration events that
change the cognitive status of different action alternatives. Suicide is a
theoretical possibility for any of us, but rarely is it a consciously reected
upon alternative (see Rudd 2000). The suicide of another person may
act as a trigger that causes a shift in perspective and turns suicide into
a more salient decision alternative (see Ward and Fox 1977). In this way
the suicides of some can inuence the decision-making processes and
suicide risks of others.
Interaction Domains and Suicide • 717
Previous Research on Exposure Eects
Previous research (Agerbo 2005; Qin, Agerbo and Mortensen 2002;
Runeson and Åsberg 2003) clearly suggest that high suicide risks are
associated with family histories of suicidal behavior. Less is known about
the mechanisms that may contribute to this. In addition to the mechanisms
discussed above, familial transmission of psychiatric disorder is likely to
be important (Egeland and Sussex 1985). Results from twin and adoption
studies furthermore suggest an important genetic component to suicide
(Brent and Mann, 2005). Much higher levels of concordance have been
reported between monozygotic than between dizygotic twins (e.g., Roy
and Segal 2001), and Fu et al.’s (2002) large-scale twin study suggests
that genetic factors account for as much as 36 percent of the variation in
suicide ideation and 18 percent of the variation in suicide attempts. The
remaining variation nevertheless is substantial, which suggests that non-
genetic factors also are of considerable importance.
Turning to the effect of exposure to suicides of non-family members,
studies on the time-space clustering of suicides provide some indirect
evidence on the importance of exposure effects. For example, Gould et al.
(1990) found signicant time-space suicide clusters among young people
in the United States and estimated that such clusters accounted for about
5 percent of all teenage suicides.
Another source of indirect evidence on exposure effects is the research
on the effects of mass media reports on suicides. Phillips (1974) conducted
the rst large-scale study of mass media effects on suicide. He examined
monthly statistics on suicides in the United States from 1947 through 1968
and found that the publication of front-page newspaper articles on suicides
led to subsequent increases in the number of suicides (Phillips 1979,1980).
Although some studies have failed to replicate these ndings (e.g., Horton
and Stack 1984; Kessler et al. 1989), results from a large number of studies
have converged in support of the existence of a systematic association
between media reports on suicides and subsequent suicide rates (Pirkis
and Blood 2001; Stack 2000). In particular, suicide risks appear to be more
inuenced by reports of celebrity suicides than non-celebrity suicides: a
recent meta-analysis of 419 studies showed that studies which looked at
celebrity suicides were more than ve times as likely to report an imitation
effect than the others (Stack 2005). One possible reason for why copy-cat
suicides are more likely after celebrity suicides is that such stories are
more widely reported and therefore reach large audiences, but it may also
reect that people identify more strongly with well-known persons than
with those they know nothing about.
Case studies of suicides in schools have similarly found that a suicide
typically leads to elevated rates of suicide and suicide attempts (Brent et
718 • Social Forces 87(2)
al. 1989; Poijula, Wahlberg and Dyregrov 2001). Studies using survey data
also suggest the existence of such effects (Bearman and Moody 2004;
Cerel, Roberts and Nilsen 2005; Hazell and Lewin 1993; Ho et al. 2000;
Lewinsohn, Rohde and Seeley 1994).
Interaction Domains and Suicides
The research summarized in previous sections thus suggests that a
systematic causal relationship is likely to exist between the suicides of
some and the suicide risks of others. Exposures, triggering events and
the like are not randomly distributed in the population, however; in order
to understand why some individuals are more likely than others to commit
suicide, it appears essential to also consider the social structure in which
the individuals are embedded.
To clarify, consider the hypothetical ego-centered network in Figure
2. Person is directly tied to 10 other individuals (in reality the relevant
ego networks are much larger than this, of course). Given the interaction
mechanisms discussed above, if this person were to commit suicide, we
would expect it to directly affect the suicide risks of the alters.
The total effect of e’s suicide on the suicide rate, I
e
, will depend on the
number of alters who become aware of e’s suicide and the effect that e
has on each of these alters. If we let p
ea
represent the inuence of e on
each of the n
e
alters to which e is directly linked, the total direct inuence
of e is equal to
5
=
=
e
n
a
e aepI
1
ea
Person-to-person networks such as that in Figure 2 are particularly useful
to focus on when patterns of interaction are fairly stable over time. But
as suggested by Hedström (2005), this is not always the case. Individuals
move between neighborhoods, schools, workplaces, etc., and during any
given period of time, individuals typically interact only with a subset of the
potential interaction partners in each domain. The amount of time devoted
to interactions with people at work, for example, may be more or less
stable over time, even though the specic people we interact with may
vary a great deal. Similarly, the inuence that people at work have on us
may be more or less stable over extended periods of time, although the
specic people who exercise this inuence may vary a great deal. In cases
like these, when the focus is on dynamic processes that unfold in networks
that themselves are changing over time, it is often more appropriate and
analytically more straightforward to focus on so-called catnets. Following
White (1965:3), a catnet is a network describing the relations that exist
between social categories, a category being a “bunch of people alike in
Interaction Domains and Suicide • 719
some respect.” Figure 3 contains an ego-centered domain-specic catnet
representation of the person-to-person network of Figure 2.
In this hypothetical example there are thus three relevant categories or
interaction domains, and the inuence of e’s suicide on the suicide rate,
I
e
, can be expressed as follows:
=
=
K
k
e ke kenpI
1
ek ek
×
where k indexes the domain, K the possible number of domains,
e k p
ek
the
average inuence of individual e upon those in domain k, and
ek
the
number of individuals in domain k that are tied to e (excluding e).
The value of I
e
shows the extent to which the effect of a suicide is
amplied by the social structure. If I
e
is greater than zero we have a
positive social multiplier, and the greater I
e
is the more amplied the
effect of e’s suicide will be. The extent of amplication depends upon the
specic combination of
e k p
ek
and n
ek
values. Individuals in certain domains,
Figure 2. Hypothetical Ego-centered Network
Figure 2. Hypothetical Ego-Centered Network
=
=
=
e
= Famil
y
= Neighbor
= Co-worke
r
Figure 3. Ego-centered Catnet Representation of Figure 2
Figure 3. Ego-Centered Catnet Representation of Figure 2
e
Domain 1: Famil
y
n
1
= 1
Domain 2: Work
n2 = 5
Domain 3: Nei
g
hborhood
n
3
= 4
pe3
pe1
pe2
720 • Social Forces 87(2)
the immediate family for example, are likely to be greatly affected by
e’s suicide (the
e k p
ek
value is likely to be high for this domain), but the
number of individuals in this domain (n
ek
) is likely to be rather low. In
other domains the opposite pattern will hold; the
e k p
ek
values will be low
and the n
ek
values will be high. Previous studies of exposure effects have
typically considered only a single domain and, as a consequence, they
have not been able to consider the variation and co-variation in the
e k p
ek
and
n
ek
values. In the empirical analyses presented below, we focus on how
these parameter values differ between the family domain and the work
domain. From a public-health perspective it is the specic combination of
values that matters. That is to say, even if the
e k p
ek
-value is low, the public
health effect can be considerable if the n
ek
-value is high, implying that
many individuals are exposed. And vice versa if the n
ek
-value is low.
e Stockholm Database
The database we use in this study contains information on the entire adult
population (age range 18-64) in the larger Stockholm metropolitan area
for each year throughout the 1990s. Statistics Sweden assembled it by
merging various administrative and population registers. The data is of
high quality and missing values are virtually nonexistent. Constructing
a database like this is only possible in a country where all government
registers use the same identifying keys, in this case a personal ID number,
and when government authorities regularly register a large amount of
information about the individuals they come into contact with.
The database includes a range of demographic and socio-economic
information, information on both current and past family relations as
well as several generations of kinship relations derived from parent-
child information. It also includes information on places of work which
will be used to link individuals to each other. The data used in this study
consists of all individuals in the database who lived and worked in the
Stockholm metropolitan area at some point during the years 1991-1999,
and were in the age-range 18-64 at that point in time. In total, 1,195,098
individuals are included in the analyses, and each individual is observed
over an average of 5.6 years.
The outcome variable of interest refers to suicides and not to suicidal
ideations. Information from the National Cause of Death Register was
used to identify the suicide cases. We follow the usual practice in
suicide epidemiology and dene a suicide on the basis of the following
cause-of-death codes: E950-E959 or E980-E989 for the years 1991-1996
(International Classication of Diseases, 9th revision) and X60-X84, Y87.0,
or Y10-Y34 for the years 1997-1999 (International Classication of Diseases,
10th revision). Because we use lagged independent variables, the suicides
Interaction Domains and Suicide • 721
Figure 4a. Number of Individuals at Risk
Figure 4a. Number of Individuals at Risk
0
50000
100000
150000
200000
250000
300000
350000
400000
450000
500000
92 93 94 95 96 97 98 99
Women
Men
Number of Individuals at Risk
Year
Figure 4b. Number of Suicides
Figure 4b. Number of Suicides
0
20
40
60
80
100
120
140
92 93 94 95 96 97 98 99
Year
Number of Suicides
Women
Men
722 • Social Forces 87(2)
that we seek to explain took place from 1992 through 1999. All in all 1,116
suicides took place in the study population during these years.
Figure 4a and 4b shows how the number of suicides and the number
of individuals at risk changed during the 1990s. About 400,000 men and
400,000 women were at risk each year and between 54 and 118 men and
46 and 59 women committed suicide each year.
Methods
Since the events to be analyzed are recorded on an annual basis only, a
discrete-time event history approach is used. We estimate the parameters
of the following type of model:
where p
it
equals the hazard rate, or the conditional probability that
individual i will commit suicide during year
t
, given that s/he was alive
at the beginning of year t, and α, γ
k
, , and λ are logistic regression
coefcients to be estimated. x
ikt
are individual-level risk attributes likely
to inuence an individual’s suicide risk. F
it-1
is a variable measuring the
number of suicides that took place in individual i’s family during the
preceding year, and W
it-1
is a variable measuring the number of suicides
that took place in the individual’s workplace during the preceding year.
Family members were identied in two steps. First we identied the focal
individual’s partner, mother, father, siblings, children, grandparents and
grandchildren. Then we identied the mother, father, siblings, children,
grandparents and grandchildren of the family members identied in the
rst step. All the individuals identied in these two steps were regarded
as family members of the focal individual.
6
“Workplace” is dened as
the specic establishment in which the individual worked at the end of
November during the preceding year.
Before the parameters of the above model are estimated, the units
must be changed from persons to “person years” so that each person
contributes as many observations as the number of years that he
was at risk (see Allison 1982). For example, an individual who entered
our population in 1998 will only contribute one observation, while an
individual who entered in 1994 will contribute ve observations. The set
of 1,195,098 persons included in these analyses contributed a total of
6.65 million person years.
The set of right-hand variables included in the analysis was guided by
ndings from prior research. As background information to the event-
history analyses, these variables are described in tables 1a and 1b.
Interaction Domains and Suicide • 723
Above we discussed in some
detail the reasons for including
the exposure variables. Let us
also in a highly telescoped manner
mention a few words about why
the control variables described
in Table 1b were included in the
analysis. As far as age and gender
are concerned, Girard (1993) and
many others have shown that
they are systematically related
to suicide risks even when
controlling for a host of other
factors. The family type variables
are similarly included because
previous research has shown that
living alone is associated with an
elevated suicide risk (Heikkinen et
al. 1995). Having young children
has been found to be associated
with lower suicide risks, especially
among women (Qin, Agerbo
and Mortensen 2003), but the
protective effect appears to
decrease with the age of the
child (Cantor and Slater 1995).
The country-of-birth variables are
included because Johansson et
al. (1997) found that foreign-born
Swedes had higher suicide risks
than the native born. Lorant et al.
(2005) found that low educated
men had higher suicide rates than
highly educated men, and having
a low income has similarly been
found to be associated with a
higher risk of suicide (Qin, Agerbo
and Mortensen 2003). Permanent
disability or sickness has similarly
been found to be associated with
an increased suicide risk (Lewis
and Sloggett 1998), and so has
sickness-related absence from
Table 1a: Description of Exposure Variables Included in the Analysis
Carol Anne,
Table 1 was missing the “Men” and “Women” labels.
Table 3 had < 100 where it should have been 100
Table 1a: Description of Exposure Variables Included in the Analysis
Mean Standard Deviation Distribution (%)
Exposure Variables Definition Men Women Men Women
Number of
Exposures Men Women
.0025 .0027 .051 .053 0 99.75 99.74
1 .25 .25
Exposure to suicide at
workplace with less
than 100 employees
Number of exposures to
suicide at workplace in
2 .00 .01
.070 .11 .33 .44 0 94.64 92.28
1 4.14 5.25
2 .77 1.54
3 .41 .79
Exposure to suicide at
workplace with more
than 100 employees
Number of exposures to
suicide at workplace
4 .04 .15
.00046 .00049 .21 .22 0 99.95 99.95
1 .05 .05
Exposure to suicide in
family
Number of exposures to
suicide in family
2 .00 .00
Table 3: Estimates of the Public-Health Effects of Suicide Exposures and Selected Comparison Events Measured in
Number of Suicides
Men Women
Actual Number of Suicides 706 410
Removing Effect of:
Family exposure -2.63 -1.78
Workplace exposure -6.45 -6.43
100 employees -5.68 .00
100 employees -.78 -6.64
Widowhood -3.86 -6.82
Divorce -1.44 -10.16
Unnatural deaths in family -.77 -1.83
724 • Social Forces 87(2)
work (Qin, Agerbo and Mortensen 2003). Research on negative life events
such as unnatural deaths and divorces similarly suggest that exposure to
such events tends to elevate the suicide risk (Heikkinen, Aro and Lonnqvist
1994; Zisook, Chentsova-Dutton and Shuchter 1998), and this also appears to
be the case with widowhood (Agerbo 2005; Luoma and Pearson 2002).
7
Results
The logistic regression results are presented in tables 2a and 2b, and we
report both the unadjusted bivariate associations between each covariate
and the risk of committing suicide, and the adjusted ones which control for
the effects of all the other covariates. We start by summarizing the effects of
the exposure variables, and unless specically noted, the discussion refers to
the effects that have been adjusted for the effects of the other covariates.
8
Table 1b: Description of Control Variables Included in the Analysis
Table 1b: Description of Control Variables Included in the Analysis
Distribution (%)
Variable Name Definition Men Women
Family type Dummy variables distinguishing between:
Couple living together 50.4 50.3
One-person unita 11.9 18.22
Other 37.7 31.46
Children aged 0-3 years At least one child aged 0-3 living at home 13.3 13.6
Children aged 4-15 years At least one child aged 4-15 living at home 25.0 28.55
Country of birth Dummy variables distinguishing between:
Sweden 84.55 84.55
Finland 4.14 6.31
Denmark, Norway, Iceland .77 .83
Easter Europe other than former Yugoslavia 1.30 1.62
Australia, New Zealand, Oceania .00 .03
Other 9.24 6.67
Early retirement Retired early due to a medical reason 1.9 3.1
Social welfare recipient Received social welfare benefit 5.2 5.3
Divorce Divorced less than 5 years ago 3.5 3.6
Widow(er) Became widow(er) less than 5 years ago .15 .36
Unnatural death in family Exposed to unnatural death of family
member due to injury, homicide, or war .03 .04
Interaction Domains and Suicide • 725
We included family size and
workplace size in the model to
control for the possible effects of
the size of the interaction domain.
We had not expected to nd an
effect of family size, but we had
anticipated the possibility of
nding a positive workplace size
effect because it seemed plausible
that it could be the proportion
rather than the absolute number
of suicides that mattered. The
results are the reverse, however.
We find that individuals from
large families run a higher risk of
committing suicide than indivi-
duals from smaller families, and
that the size of the workplace
has no independent effect on the
suicide risk after controlling for the
other covariates in the model (and
distinguishing between exposure
in workplaces with more and with
less than 100 employees).
The exposure variables behave
more or less as expected. This
is particularly true for exposure
within the family. The odds ratios
are extremely high for women as
well as for men, suggesting an
eight- to nine-fold elevated risk for
those who have been exposed to
the suicide of a family member.
9
It is important to keep in mind
that this “social-interaction effect”
is likely to be upwardly biased,
however. The suicide propensities
of two members of the same
family are likely to be associated
because of common ancestry as
well as unmeasured common
environmental inuences. Such
factors are not properly captured
Table 1b continued
CA,
1392.0 is aligned now.
Table 1b: Continued
Mean Standard Deviation Range
Men Women Men Women Men Women
Age Age in November 39.7 39.8 12.2 12.4 18-65 18-65
Educational level Years of education 10.0 10.0 5.4 5.4 0-18 0-18
Benefits for illness or work
related injuries
Logged amount (100’s SEK) due to illness or
work related injuries received .73 1.0 1.7 1.9 0-8.7 0-8.7
Income Logged total disposable income (in base-
amountsb) in year t 1.2 1.1 .52 .46 0-8.8 0-7.4
Family size Number of family members in the extended
family (not including the focal individual) 8.7 8.8 3.8 3.8 0-29 0-27
Workplace size Number of employees at the workplace 396.8 558.5 986.9 1392.0 1-8453 1-8453
Notes:
a This category may include cohabiting couples who do not have any children in common.
b One base-amount is approximately equal to 33,000 SEK
Notes:
a is category may include cohabiting couples who do not have any children in common.
b One base-amount is approximately equal to 33,000 SEK
726 • Social Forces 87(2)
Table 2a: Parameter Estimates of Discrete Event-History Models for Men
Table 2a: Parameter Estimates of Discrete Event-History Models. Men.
Men
n = 601,245; N = 3,338,578
Unadjusted Adjusted
Variable b OR 95%CI b OR 95%CI
Number of Exposures to Suicide
In family 2.22*** 9.21** 3.00-28.25 2.12*** 8.33*** 2.70-25.64
At workplace with 100 employees 1.48*** 4.38** 2.06-9.31 1.25*** 3.50*** 1.62-7.56
At workplace with 100 employees .11 1.11 .91-1.36 .01 1.01 .78-1.31
Age
Years .06** 1.06** 1.01-1.11 .09*** 1.09*** 1.04-1.15
Years2/1000 -.00 999.5 999.0-1.00 -.80** 999.2* 998.6-999.8
Family Type
Couple 1.00
1-person 9.98*10-1*** 2.71*** 2.30-3.20 1.19*** 3.28*** 2.61-4.14
Other .24 1.27 .96-1.68 .69*** 2.00*** 1.45-2.75
Children
No 1.00 1.00
Aged 0-3 yrs -.86*** .42*** .30-.59 -.25 .78 .54-1.13
Aged 4-15 yrs -.77*** .46*** .37-.58 -.35* .70* .54-.92
Education Level
Years of education .03 1.03 .98-1.08 -.04 .96 .92-1.00
Years of education2/1000 -.04*10-1* 996.5* 993.4-999.6 2.69 1002.7 999.7-1005.7
Early Retirement
No 1.00 1.00
Yes 1.58*** 4.87*** 3.75-6.34 .79*** 2.21*** 1.62-3.02
Benefits for Illness or Work Related In
j
uries
(
lo
gg
ed
)
.28*** 1.33*** 1.29-1.36 .23*** 1.25*** 1.21-1.30
Social Welfare Recipient
Interaction Domains and Suicide • 727
No 1.00 1.00
Yes 9.97*10-3*** 2.72*** 2.18-3.39 .61*** 1.85*** 1.45-2.35
Level of Income
Logged annual amount -.16* .86* .76-.97 -.35*** .70*** .64-.78
Divorcee
No 1.00 1.00
Yes .57*** 1.77*** 1.30-2.42 .04 1.04 .74-1.44
Widow/Widower
No 1.00 1.00
Yes 1.77*** 5.87*** 2.63-13.13 1.03* 2.80* 1.25-6.30
Unnatural Death in Family
No 1.00 1.00
Yes 1.48 4.41 .62-31.36 1.48 4.40 .61-31.50
Country of Birth
Sweden 1.00 1.00
Finland .47** 1.60** 1.19-2.17 .32* 1.37* 1.01-1.87
Denmark/Norway/ Iceland .63* 1.87* 1.00-3.50 .66* 1.93* 1.04-3.60
Eastern Europe other than Yugoslavia -.40 .67 .29-1.49 -.51 .60 .27-1.35
Australia/New Zealand/Oceania - - - - - -
Other -.10 .91 .69-1.19 -.08 .92 .69-1.23
Family Size .01 1.01 .99-1.03 .07*** 1.07*** 1.05-1.10
Workplace Size .00 1.00 .99-1.00 .00 1.00 .99-1.00
Constant -11.69***
Pseudo R2 .05
-2LL 701.51
Note: Estimated coecients (b), odds ratios (OR) and condence intervals for the odds ratios (CI). n = number of individuals and N =
number of person years.
728 • Social Forces 87(2)
Table 2b: Parameter Estimates of Discrete Event-History Models for Women
Table 2b: Parameter Estimates of Discrete Event-History Models. Women.
Women
n = 593,853; N = 3,308,271
Unadjusted Adjusted
Variable b OR 95%CI b OR 95%CI
Number of Exposures to Suicide
In family 2.28*** 9.79*** 2.41-38.11 2.20** 9.01** 2.23-36.30
At workplace with 100 employees -.08 .92 .14-6.09 -.19 .83 .12-5.55
At workplace with 100 employees .24** 1.28** 1.08-1.51 .10 1.11 .86-1.42
Age
Years .05 1.06 .99-1.12 .08* 1.09* 1.02-1.16
Years2/1000 -.42 999.6 998.9-1.00 -.92* 999.1* 998.3-999.9
Family Type
Couple 1.00 1.00
1-person 1.21*** 3.36*** 2.68-4.21 1.22*** 3.40*** 2.55-4.53
Other .55*** 1.73*** 2.68-4.21 .50** 1.65** 1.18-2.31
Children
No 1.00 1.00
Aged 0-3 yrs -1.18*** .31*** .19-.50 -.81** .45** .26-.76
Aged 4-15 yrs -.73*** .48*** .37-.63 -.42* .66* .47-.91
Education Level
Years of education .00 1.00 .94-1.07 -.08** .92** .87-.98
Years of education2/1000 -1.22 998.8 995.7-1002.9 4.95* 1005.0* 1000.9-1009.1
Early Retirement
No 1.00 1.00
Yes 1.92*** 6.84*** 5.32-8.80 1.11*** 3.05*** 2.23-4.15
Benefits for Illness or Work Related Injuries (logged) .32*** 1.38*** 1.33-1.44 .28*** 1.32*** 1.26-1.39
Social Welfare Recipient
Interaction Domains and Suicide • 729
No 1.00 1.00
Yes 1.26*** 3.54*** 2.73-4.59 .96*** 2.60*** 1.95-3.47
Level of Income
Logged annual amount -.03 .97 .80-1.18 -.29** .75** .61-.92
Divorcee
No 1.00 1.00
Yes .83*** 2.29*** 1.60-3.29 .38 1.47 .99-2.15
Widow/Widower
No 1.00 1.00
Yes 1.93*** 6.91*** 3.69-12.95 1.15*** 3.15*** 1.64-6.05
Unnatural Death in Family
No 1.00 1.00
Yes 2.62*** 13.77*** 3.43-55.25 2.47*** 11.80*** 2.89-48.17
Country of Birth
Sweden 1.00 1.00
Finland .70*** 2.01*** 1.49-2.72 .69** 1.99** 1.42-2.80
Denmark/Norway/ Iceland 0.29 1.26 .47-3.37 .31 1.37 .51-3.67
Eastern Europe other than Yugoslavia .94*** 2.57*** 1.55-4.24 .89** 2.44** 1.44-4.11
Australia/New Zealand/Oceania 2.04* 7.70* 1.08-54.82 2.41* 11.12* 1.62-76.28
Other -.61* .54* .32-.93 -.54 .59 .34-1.02
Family Size .01 1.01 .99-1.03 .08*** 1.08*** 1.05-1.11
Workplace Size .09*10-4** 1.00** 1.00-1.00 .00 1.00 .99-1.00
Constant -12.38***
Pseudo R2 .08
-2LL 652.85
Note: Estimated coefficients (b), odds ratios (OR), and confidence intervals for the odds ratios (CI). n = number of individuals and N =
number of person years.
*p < .05; **p <.01; ***p < .001
Note: Estimated coecients (b), odds ratios (OR) and condence intervals for the odds ratios (CI). n = number of individuals and N =
number of person years.
730 • Social Forces 87(2)
by our control variables, and this is likely to inate the estimate of the
family-based social-interaction effect.
Exposure at work is only signicant for men, and only in workplaces
with fewer than 100 employees. The effect of workplace exposure
is not of the same magnitude as that of family exposure, but it is
nevertheless considerable (OR = 3.50). The workplace exposure effect
is unconfounded by genetic and other shared factors, and thus is likely
to be caused by the type of social mechanisms discussed above. The
reason for the absence of an effect in larger workplaces most likely does
not mean that small and large workplaces differ from one another in this
respect. More likely, it simply reects the fact that in large workplaces
the relevant reference group is not the workplace as a whole but some
smaller department or subsection that we cannot identify in our data.
As far as the reasons for the lack of a signicant workplace effect among
women, we can only speculate because the data does not allow for further
analyses. Gender differences in workplace attachment appear to be one
plausible reason. Although Swedish women are more likely to work than are
women in many other countries, they still bear the main household and child-
care responsibilities (Hall 1992), which may lead to a weaker attachment to
the workplace, and work is typically more important for men’s self-identities
than for women’s (Girard 1993; Neugarten and Hagestad 1976).
As far as we know, this is the rst study that systematically examines
the effect of suicide exposures in the workplace. One possible objection
to the way in which we have interpreted these results is that they may, at
least in part, reect unmeasured differences between workplaces in the
exposure to other types of risk factors – stress levels, for example – which
could possibly generate a spurious exposure effect. To partially control
for that possibility we re-estimated the models in Table 2, including 58
industry dummies to partially control for unobserved heterogeneity. The
results of these analyses were in every essential respect identical to those
reported in Table 2 and they thus give further weight to the exposure-
interpretation of the results reported here.
If we then turn to the control variables, their effects are more or less
as we would expect them to be. As previous research suggests, age is
systematically associated with the suicide risk. The partial effect estimates
suggest that the suicide risk gradually increases with age and that it is as
highest at the age of 44 for men and 41 for women.
As expected, coupled individuals, men as well as women, have lower
suicide rates than singles. On the basis of these data we cannot tell whether
this is a “protective effect” of the family arrangement as such or a selection
effect due to suicidal individuals being less likely to be coupled.
Also as expected, having children living at home appears to be
associated with lower suicide risks for men as well as for women. For
Interaction Domains and Suicide • 731
men, the effect is signicant only for children in the older age category,
while for women we nd the expected pattern of a declining “protective”
effect with the age of the child.
Contrary to much of previous research, we nd that the net effect of
years of education is positive for women (this can be seen by plotting the
combined effect of the educational variables). That is, women’s suicide
risk increases with increasing education, all else being equal. For men, the
point estimates suggest the same pattern, but these estimates are not
signicantly different from zero.
10
The variables that serve as proxies for health-related problems – early
disability retirement and illness and work related injuries – behave as
expected. Individuals who received such benets had clearly elevated risks.
The same is true for the two deprivation-related variables. The regression
coefcient associated with the social-welfare variable is positive, and the
regression coefcient of the income variable is negative.
Having gone through a divorce in the past five years, somewhat
surprisingly given previous research ndings, does not appear to signicantly
elevate the risk for either sex. It should be emphasized that this refers to the
partial effect of divorce, however. As the results of the bivariate unadjusted
analyses show, those who had experienced a divorce had a signicantly
higher suicide risk than those who had not experienced a divorce. Hence,
these results suggest that the two groups differ from one another in relevant
respects, and after controlling for these differences, the divorce experience
is no longer signicantly related to the suicide risk.
Having become a widow or widower in the past ve years is associated
with an elevated risk for men as well as for women, and this is also true
for those who experienced an unnatural death in the family. This latter
variable is associated with a sharply elevated risk for women. The point
estimate is high also for men, but the test suggests that the estimate is
not signicantly different from zero.
Finally, and as expected, immigrants from several different nations
have elevated suicide risks as compared to those born in Sweden. With
data like this it is not possible to assess to what extent this is a result
of the immigration and assimilation experience as such, or whether it
reects individual differences between immigrants and native Swedes
not picked up by the variables included the model. For our purpose, this
is not a major concern, however, because we only included country
of birth as a control variable to reduce the risk of the estimates of the
exposure effects becoming confounded.
To assess the overall importance of networks it is not sufcient to examine
only social-interaction effects like those in Table 2, one must also take into
account the number of individuals who are exposed. This is particularly
important when comparing domains such as these that differ widely in size
732 • Social Forces 87(2)
and average degree. On average, the suicides being studied here resulted in
2.9 family members being exposed, while suicides at small workplaces, here
dened as workplaces with less than 100 employees, resulted in 15.3 other
individuals being exposed.
11
Table 3 displays results taking into account
both the dyad-based interaction effects of Table 2 and the degree-based
effect, i.e., the number of individuals being exposed to each suicide.
The rst row of Table 3 shows the actual number of suicides that took
place, and this is identical to the number of suicides predicted by the
logistic regression models. The second row shows what the number of
suicides would have been according to the logistic models had no one
been exposed to the suicide of a family member (or, equivalently, the
number of suicides being observed if family-based exposure had no effect
on the suicide risk). These estimates suggest that we would then have
observed three fewer male suicides and two fewer female suicides than
we actually observed. These public-health effects may seem surprisingly
small given the considerable social-interaction effects shown in Table 2.
Although one should treat these estimates with great caution and not
pay too much attention to the exact magnitude of the estimates, they
illustrate the importance of the distinctions introduced earlier. Although
the social-interaction effects, what we referred to as
e k p
ek
, are substantial,
the collective public health effect is rather modest because the networks
within the family domain are such that not many individuals are exposed;
the n
ek
values are low within the family domain.
The third row of Table 3 performs the same kind of counterfactual thought
experiment for workplace exposure. Since the effects were signicant only
for men, we focus exclusively on the public health effect among men. Had
no one been exposed to a suicide in the workplace, these estimates suggest
that there would have been six to seven fewer male suicides than actually
was observed. A signicant effect is found only in the smaller workplaces,
but as argued above, this is most likely due to poor measurement of the
Table 3: Estimates of the Public-Health Eects of Suicide Exposures and
Selected Comparison Events Measured in Number of Suicides
Carol Anne,
Table 1 was missing the “Men” and “Women” labels.
Table 3 had < 100 where it should have been 100
Table 1a: Description of Exposure Variables Included in the Analysis
Mean Standard Deviation Distribution (%)
Exposure Variables Definition Men Women Men Women
Number of
Exposures Men Women
.0025 .0027 .051 .053 0 99.75 99.74
1 .25 .25
Exposure to suicide at
workplace with less
than 100 employees
Number of exposures to
suicide at workplace in
2 .00 .01
.070 .11 .33 .44 0 94.64 92.28
1 4.14 5.25
2 .77 1.54
3 .41 .79
Exposure to suicide at
workplace with more
than 100 employees
Number of exposures to
suicide at workplace
4 .04 .15
.00046 .00049 .21 .22 0 99.95 99.95
1 .05 .05
Exposure to suicide in
family
Number of exposures to
suicide in family
2 .00 .00
Table 3: Estimates of the Public-Health Effects of Suicide Exposures and Selected Comparison Events Measured in
Number of Suicides
Men Women
Actual Number of Suicides 706 410
Removing Effect of:
Family exposure -2.63 -1.78
Workplace exposure -6.45 -6.43
100 employees -5.68 .00
100 employees -.78 -6.64
Widowhood -3.86 -6.82
Divorce -1.44 -10.16
Unnatural deaths in family -.77 -1.83
Interaction Domains and Suicide • 733
relevant reference groups in the larger workplaces. Had we been able to
identify the relevant reference groups in the larger workplaces, undoubtedly
the estimated public-health effect would have been considerably higher
since more than 40 percent of employees work in such workplaces. For
reasons such as these one should not pay much attention to the exact
gures, but even with these caveats in mind, the results clearly suggest that
it is important to consider the workplace when seeking to explain suicide
rates. Although the
e k p
ek
value for the work domain was much lower than for
the family domain, the public-health effect of exposure in the work domain
was much greater because of its higher n
ek
value.
The last three rows of Table 3 are included as comparison points for
evaluating the substantive importance of the estimated public-health
effects of the exposure variables. Here we perform the same type
of thought experiments for three negative life events that are often
considered in suicide research: becoming a widower, going through a
divorce, and experiencing the unnatural death of a family member. For men,
family exposure appears to be of approximately the same public-health
importance as these three types of life events, while workplace exposure
is more important. For women, the public-health effect of family exposure
is comparable to that of an unnatural death of a family member, but it is
not of the same magnitude as that of the other two types of events.
Conclusion
The analyses reported here suggest that network effects are important
for explaining suicides. Suicides of family members as well as of co-
workers inuence the suicide risks of those exposed. In addition, the
results suggest that the degree of the deceased individual’s ego-
centered network is important because it inuences the number of
exposed individuals and thereby the suicide rate. When examining the
dyad-based social-interaction effects, exposure in the family domain
seemed to be about twice as important as exposure in the work domain,
but when we also took into account the degree-based exposure effects
and examined the collective public-health effect, we found workplace
exposure for men to be at least twice as important as family exposure.
This result is particularly striking because the estimated family-exposure
effect is likely to be upwardly biased since we were not able to control
for factors such as the genetic component of suicide and inheritable
psychiatric disorders known to increase the suicide risk.
Individual-level studies of exposures to suicide have largely concentrated
on adolescents, and it is generally believed that exposure effects are
important only within this age group. As far as we know, this is the rst
study to demonstrate that workplace exposure is also associated with a
734 • Social Forces 87(2)
higher suicide risk among adults. National suicide prevention strategies
usually pay no attention to suicide exposure in the workplace. The results
reported here suggest that prevention strategies focusing on the workplace
may be at least as important as those focusing on the family.
We believe that some of the empirical results and analytical distinctions
introduced in this article are important also for explaining other outcomes.
Whenever the interaction among individuals is deemed important for the
collective outcome to be explained, as in differential-association theory’s
(Sutherland 1947) explanation of crime rates for example, the distinction
between dyad-based and degree-based network effects appears essential.
Focusing exclusively on one of these two types of effects can lead to a faulty
understanding of the importance of social interactions and networks.
In addition, we believe that this article illustrates the importance of
tightly linking theory and data.
12
If our theory suggests that networks and/
or localized social interactions are important, it is essential to use datasets
which actually contain such information because the wider the gap is
between theory and data the less theoretical bearing and relevance will
the empirical research have. It is always tempting to cut corners by using
aggregate data or indirect proxy variables from existing surveys, but since
social action and interaction is at the heart of so much of sociological theory,
there will often be no good alternative to collecting the type of data used
in this article, i.e., longitudinal data on the actions and attributes of large
numbers of individuals and the patterns of interaction among them.
13
Notes
1. See Sainsbury, Jenkins and Levey (1980) and Breault (1986) for examples.
Mäkinen’s (1997) replication study of Sainsbury et al.’s study, however, has
cast serious doubts on the reliability and robustness of such aggregate
associations. Also see Pescosolido (1994) for a critique of the approach.
2. Let us emphasize that analyzing suicides as intentional actions does not mean
that the intention behind all suicides is to take one’s life. The intention may
have been to send a signal to others about a desperate life situation, but the
unintended outcome of the act was death. Nor does an action approach imply
that individual intentions are necessarily unclouded by strong emotions or
cognitive biases.
3. It also is exemplied by the title of the Swedish singer Magnus Uggla’s 1989
hit album “What’s the Point of Killing Yourself if You Can’t be Around to Hear
the Yap.”
4. We ignore pure opportunity-related interaction mechanisms because a
person’s suicide rarely affects others’ opportunities to commit suicide. One
possible exception is when an individual invents a new suicide method, e.g.,
Interaction Domains and Suicide • 735
the use of car exhaust gas as a means of committing suicide in Britain in the
1970s. See Clarke and Lester (1987).
5. pea can be thought of as measuring how the probability of an alter’s committing
suicide is affected by e’s suicide, holding everything else constant.
6. It should be observed that only individuals residing in the Stockholm
metropolitan area are included in the database.
7. Given the fact that previous research suggests that religion plays an
important role in this context, we regret the fact that the database includes
no information on the individuals’ religious orientations.
8. It would have been useful to estimate fixed-effect logit models, but
unfortunately such models would be highly inefcient because they disregard
so much of the data. Suicides are extremely rare events, and xed-effect
logit models only make use of data on units with variation on the dependent
variable. Since suicides occur so rarely, we also estimated the so-called
rare-event logit model (King and Zeng, 1999). Qualitatively the results were
identical to those reported here.
9. These ORs of family exposure are higher than those found in another
Swedish register-based study (Runeson and Åsberg, 2003). There are some
differences in the study designs that may explain these discrepancies, most
notably that they used people who had died from other causes than suicide
as their control group.
10. If we examine the relationship between the two educational variables and
the suicide risks without any other control variables, the expected negative
pattern is found.
11. In larger workplaces, the number of potentially exposed individuals was of
course much higher, but because we do not have information on the way in
which these workplaces were internally organized, we cannot estimate the
likely number of truly exposed individuals in large workplaces. Our cut-off value
of 100 to distinguish between “large” and “small” workplaces is arbitrarily
chosen, but the results seem robust at least to small changes in this value.
12. See Hedström and Bearman (forthcoming) for more detailed discussions
of this analytically oriented middle-range approach that seeks to tightly link
sociological theory and empirical research.
13. Needless to say, data of the size and scale used in this article will be
prohibitively expensive to collect, but such data only is needed when the
outcomes to be explained are extremely rare, and even in such circumstances
smaller case-control designs often can be used.
736 • Social Forces 87(2)
References
Åberg, Yvonne. 2003. Social Interactions: Studies of Contextual Effects and Endogenous
Processes. Stockholm: Department of Sociology, Stockholm University.
Agerbo, Esben. 2005. “Midlife Suicide Risk, Partner’s Psychiatric Illness, Spouse
and Child Bereavement by Suicide or Other Modes of Death: A Gender Specic
Study.” Journal of Epidemiology and Community Health 59(5):407-12.
Allison, Paul D. 1982. “Discrete-Time Methods for the Analysis of Event Histories.”
Sociological Methodology 13:61-98.
Bandura, Albert. 1994. “Self-Efcacy.” Pp. 71-81. Encyclopedia of Human Behavior.
Vilayanur S. Ramachaudran, editor. Academic Press.
Baron, James N., and Peter C. Reiss. 1985. “Same Time, Next Year: Aggregate
Analysis of the Mass Media and Violent Behavior.” American Sociological
Review 50(3):347-63.
Bearman, Peter. 1991. “The Social Structure of Suicide.” Sociological Forum 6(3):501-24.
Bearman, Peter, and James Moody. 2004. “Suicide and Friendships among
American Adolescents.” American Journal of Public Health 94(1):89-95.
Breault, Kevin D. 1986. “Suicide in America: A Test of Durkheim’s Theory of
Religious and Family Integration, 1933-1980.” American Journal of Sociology
92(3):628-56.
Brent, David A., Mary M. Kerr, Charles Goldstein, James Bozigar, Mary Wartella
and Marjorie J. Allan. 1989. “An Outbreak of Suicide and Suicidal Behavior
in a High School.” Journal of the American Academy of Child & Adolescent
Psychiatry 28(6):918-24.
Brent, David A., and J. John Mann. 2005. “Family Genetic Studies, Suicide and
Suicidal Behavior.” American Journal of Medical Genetics Part C 133C(1):13-24.
Cantor, Christopher H., and Penelope J. Slater. 1995. “Marital Breakdown,
Parenthood, and Suicide.” Journal of Family Studies 1(2):91-102.
CDC. 1994. “Centers for Disease Control Recommendations for a Community
Plan for the Prevention and Containment of Suicide Clusters.” Morbidity and
Mortality Weekly Report 37(S6):1-12.
Cerel, Julie, Timothy A. Roberts and Wendy J. Nilsen. 2005. “Peer Suicidal
Behavior and Adolescent Risk Behavior.” Journal of Nervous and Mental
Disease 193(4):237-43.
Clarke, Ronald V., and David Lester. 1987. “Toxicity of Car Exhausts and Opportunity
for Suicide: Comparison between Britain and the United States.” Journal of
Epidemiology & Community Health 41(2):114-20.
Interaction Domains and Suicide • 737
Cutler, David M., Edward L. Glaeser and Karen Norberg. 2001. “Explaining the
Rise in Youth Suicide.” Pp.219-70. Risky Behavior among Youths: An Economic
Analysis. Jonathan Gruber, editor. University of Chicago Press.
Davidson, Donald. 1980. Essays on Actions and Events. Clarendon Press.
Egeland, Janice A., and James N. Sussex. 1985. “Suicide and Family Loading for
Affective Disorders.” Journal of American Medical Association 254(7):915-8.
Elster, Jon. 1983. Explaining Technical Change: A Case Study in the Philosophy of
Science. Cambridge University Press.
Farberow, Norman L. 1975. “Cultural History of Suicide.” Pp. 1-15. Suicide in
Different Cultures. Norman L. Farberow, editor. University Park Press.
Fu, Qiang, Andrew C. Heath, Kathleen K. Bucholz, Elliot C. Nelson, Anne L.
Glowinski, J. Goldberg, M.J. Lyons, M.T. Tsuang, Theodore Jacob, M.R. True
and S.A. Eisen. 2002. “A Twin Study of Genetic and Environmental Inuences
on Suicidality in Men.” Psychological Medicine 32(1):11-24.
Girard, Chris. 1993. Age, Gender, and Suicide: A Cross-National Analysis.”
American Sociological Review 58(4):553-74.
Gould, Madelyn S., Sylvan Wallenstein, Marjorie H. Kleinman, Patrick O’Carroll
and James Mercy. 1990. “Suicide Clusters: An Examination of Age-Specic
Effects.” American Journal of Public Health 80(2):211-2.
Hall, Ellen M. 1992. “Double Exposure: The Combined Impact of the Home and
Work Environments on Psychosomatic Strain in Swedish Women and Men.”
International Journal of Health Services 22(2):239-60.
Hankoff, Leon D. 1961. An Epidemic of Attempted Suicide.” Comprehensive
Psychiatry 2(5):294-8.
Hazell, Philip, and Terry Lewin. 1993. “Friends of Adolescent Suicide Attempters
and Completers.” Journal of the American Academy of Child and Adolescent
Psychiatry 32(1):76-81.
Hedström, Peter 2005. Dissecting the Social: On the Principles of Analytical
Sociology. Cambridge University Press.
Hedström, Peter, and Peter Bearman. Editors. Forthcoming. The Oxford Handbook
of Analytical Sociology. Oxford University Press.
Hedström, Peter, and Richard Swedberg. Editors. 1998. Social Mechanisms: An
Analytical Approach to Social Theory. Cambridge University Press.
Heikkinen, Martti E., Hillevi M. Aro and Jouko K. Lonnqvist. 1994. “Recent
Life Events, Social Support and Suicide.” Acta Psychiatrica Scandinavica
Supplementum 89(s377):65-72.
738 • Social Forces 87(2)
Hezel, Francis X. 1985. “Trukese Suicide.” Pp. 112-24. Culture, Youth and Suicide in
the Pacic: Paper from an East-West Center Conference. Francis X. Hezel, Donald
H. Rubinstein and Geoffrey M. White, editors. University of Hawaii Press.
Ho, Ting-Pong, Patrick Wing-leung Leung, Se-Fong Hung, Chi-Chiu Lee and Chun-
Pan Tang. 2000. “The Mental Health of the Peers of Suicide Completers and
Attempters.” Journal of Child Psychology and Psychiatry 41(3):301-8.
Horton, Hayward, and Steven Stack. 1984. “The Effect of Television on National
Suicide Rates.” Journal of Social Psychology 123(1):141-2.
Jacobs, Douglas G., Margaret Brewer and Marci Klein-Benheim. 1999. “Suicide
Assessment: An Overview and Recommended Protocol.” Pp. 3-39. The
Harvard Medical School Guide to Suicide Assessment and Intervention. D.G.
Jacobs, editor. Jossey-Bass.
Johansson, Leena M., Jan Sundquist, Sven-Erik Johansson, Jan Qvist and B.
Bergman. 1997. “The Inuence of Ethnicity and Social and Demographic
Factors on Swedish Suicide Rates. A Four-Year Follow-Up Study.” Social
Psychiatry and Psychiatric Epidemiology 32(3):165-70.
Kessler, Ronald C., Geraldine Downey, Horst Stipp and J. Ronald Milavsky. 1989.
“Network Television News Stories about Suicide and Short-Term Changes in
Total U.S. Suicides.” Journal of Nervous and Mental Disease 177(9):551-55.
King, Gary, and Langche Zeng. 2000. “Logistic Regression in Rare Events Data.”
Political Analysis 9(2):137-63.
Lewinsohn, Peter M., Paul Rohde and John R. Seeley. 1994. “Psychosocial Risk
Factors for Future Adolescent Suicide Attempts.” Journal of Consulting and
Clinical Psychology 62(2):297-305.
Lewis, Glyn, and Andy Sloggett. 1998. “Suicide, Deprivation, and Unemployment:
Record Linkage Study.” British Medical Journal 317(7168):1283-6.
Linehan, Marsha M., Judith L. Goodstein, Stevan L. Nielsen and John A. Chiles.
1983. “Reasons for Staying Alive When You Are Thinking of Killing Yourself:
The Reasons for Living Inventory.” Journal of Consulting and Clinical
Psychology 51(2):276-86.
Luoma, Jason B., and Jane L. Pearson. 2002. “Suicide and Marital Status in the
United States, 1991-1996: Is Widowhood a Risk Factor?” American Journal
of Public Health 92(9):1518-22.
McKenzie, Nigel, Sabine Landau, Nanveet Kapur, Janet Meehan, Jo Robinson,
Harriet Bickley, Rebecca Parsons and Louis Appleby. 2005. “Clustering of
Suicides among People with Mental Illness.” British Journal of Psychiatry
187(5):476-80.
Interaction Domains and Suicide • 739
Michel, Konrad, and Ladislav Valach. 1997. “Suicide as Goal-Directed Action.”
Archives of Suicide Research 3(3):213-21.
Mäkinen, Ilkka H. 1997. “Are There Social Correlates to Suicide?” Social Science
and Medicine 44(12):1919-29.
Neugarten, Bernice L., and Gunhild O. Hagestad. 1976. “Age and the Life Course.”
Pp. 35-55. Handbook of Aging and the Social Sciences. Robert H. Binstock
and Ethel Shanas, editors. Van Nostrand Reinhold Co.
Pescosolido, Bernice A. 1994. “Bringing Durkheim into the Twenty-First Century:
A Network Approach to Unresolved Issues in the Sociology of Suicide.” Pp.
264-96. Emile Durkheim: Le suicide, One Hundred Years Later. David Lester,
editor. Charles Press.
Phillips, David P. 1974. “The Inuence of Suggestion on Suicide: Substantive
and Theoretical Implications of the Werther Effect.” American Sociological
Review 39(3):340-54.
. 1979. “Suicide, Motor Vehicle Fatalities, and the Mass Media: Evidence
toward a Theory of Suggestion.” American Journal of Sociology 84(5):1150-74.
. 1980. Airplane Accidents, Murder, and the Mass Media: towards a
Theory of Imitation and Suggestion.” Social Forces 58(4):1001-24.
Pirkis, Jane, and R. Warwick Blood. 2001. “Suicide and the Media. Part I: Reportage
in Nonctional Media.” Crisis 22(4):146-54.
Poijula, Soili, Karl-Erik Wahlberg and Atle Dyregrov. 2001. Adolescent Suicide
and Suicide Contagion in Three Secondary Schools.” International Journal of
Emergency Mental Health 3(3):163-8.
Qin, Ping, Espen Agerbo and Preben B. Mortensen. 2002. “Suicide Risk in Relation to
Family History of Completed Suicide and Psychiatric Disorders: A Nested Case-
Control Study Based on Longitudinal Registers.” Lancet 360(9340):1126-30.
. 2003. “Suicide Risk in Relation to Socioeconomic, Demographic, Psychiatric,
and Familial Factors: A National Register-Based Study of All Suicides in Denmark,
1981-1997.” American Journal of Psychiatry 160(4):765-72.
Roy, Alec, David Nielsen, Gunnar Rylander and Marco Sarchiapone. 2000. “The
Genetics of Suicidal Behaviour.” Pp. 210-21. The International Handbook of
Suicide and Attempted Suicide. K. Hawton and K. Van Heeringen, editors.
John Wiley & Sons.
Roy, Alec, and Nancy L. Segal. 2001. “Suicidal Behavior in Twins: A Replication.”
Journal of Affective Disorders 66(1):71-74.
Rudd, M. David 2000. “The Suicidal Mode: A Cognitive-Behavioral Model of
Suicidality.” Suicide and Life Threatening Behavior 30(1):18-33.
740 • Social Forces 87(2)
Runeson, Bo, and Marie Åsberg. 2003. “Family History of Suicide among Suicide
Victims.” American Journal of Psychiatry 160(8):1525-26.
Sainsbury, Peter, J. Jenkins and A. Levey. 1980. “The Social Correlates of Suicide
in Europe.” Pp. 38-53. The Suicide Syndrome. Richard Farmer and Steven
Hirsch, editors. Croom Helm.
Shneidman, Edwin S. 1969. On the Nature of Suicide. Jossey-Bass.
Stack, Steven 2000. “Suicide: A 15-Year Review of the Sociological Literature
Part II: Modernization and Social Integration Perspectives.” Suicide and Life
Threatening Behavior 30(2):163-76.
. 2005. “Suicide and the Media: A Quantitative Review of Studies Based on
Nonctional Stories.” Suicide and Life Threatening Behavior 35(2):121-33.
Sutherland, Edwin. 1947. Principles of Criminology. 4th edition. J.B. Lippincott.
Ward, J.A., and Joseph Fox. 1977. A Suicide Epidemic on an Indian Reserve.”
Canadian Psychiatric Association Journal 22(8):423-26.
White, Harrison C. 1965. “Notes on the Constituents of Social Structure.”
Unpublished manuscript. Department of Sociology. Harvard University.
WHO. 2000. “Preventing Suicide: A Resource for Media Professionals.” Geneva:
World Health Organization.
Zisook, Sidney, Yulia Chentsova-Dutton and Stephen R. Shuchter. 1998. “PTSD
Following Bereavement.” Annals of Clinical Psychiatry 10(4):157-63.
... In fact, exposure to suicide is per se a suicide risk factor (Agerbo, Nordentoft, & Mortensen, 2002;De Leo & Heller, 2008;Hedstrom, Liu, & Nordvik, 2008;Rostila, Saarela, & Kawachi, 2013;Song, Kwon, & Kim, 2015;WHO, 2014). For example, research based on Danish national health records has shown a strong association between a family history of suicide and suicide risk (Agerbo et al., 2002). ...
... De Leo and Heller (2008) found that suicide exposure increases the risk of suicidal behaviour and death by suicide in Australian young people. Hedstrom et al., (2008) found that Swedish men exposed to a suicide in their family or at the workplace were more likely to die by suicide. Rostila et al., (2013) also found an increased risk of mortality by suicide among those who had experienced sibling suicide death. ...
Article
Objectives: This study tested the mediation effects of two facets of psychache - bearable and unbearable - in the relationship between exposure to suicide in the family and suicidal ideation in Portugal during the Covid-19 pandemic. Methods: Two hundred and forty-four adults aged between 19 and 64 participated. Two groups were defined: one exposed to suicide in the family (n = 42) and a control group (n = 192). Results: Path analysis using structural equation modelling tested a mediation model. Results demonstrated that unbearable psychache fully mediated the relationship between exposure to suicide and suicidal ideation, even when controlling for the mediation effects of depressive symptoms, the presence of a psychiatric diagnosis, and years of education. Conclusions: These results suggest that rather than considering just the global experience of psychache in individuals exposed to suicide, researchers and clinicians should look to the presence of unbearable psychache given its contribution to suicidal ideation. Practitioner points: Unbearable psychache fully mediated the relationship between exposure to suicide in the family and suicidal ideation It is not the global experience of psychache that contributes to suicide ideation in individuals exposed to suicide in the family rather the presence of unbearable psychache.
... L'innovazione può essere rappresentata da una nuova pratica o da un comportamento che, dal punto di vista soggettivo, viene percepita come positiva. Non mancano, del resto, esempi di interdipendenza sociale legati a comportamenti autodistruttivi, come il suicidio (Hedstrom et al. 2008). ...
... • substance-use disorders. 8,25,35,[38][39][40][41] Suicide-bereaved children are also at increased risk of depression, anxiety and PTSD. 42 The social stigma that many suicide-bereaved individuals experience can be a major inhibiting factor to help-seeking and may prevent participation in suicide postvention interventions. ...
Article
Background: Managing the completed suicide of a patient in general practice has long been a taboo and neglected subject. Doctors and staff are too frequently unprepared for the crisis and its sequelae. The wellbeing of the doctor, practice staff and bereaved family are often neglected, with detrimental consequences. Objective: The aim of this article is to develop a guideline for a whole-of-practice strategy to support general practitioners and practices through the immediate aftermath of a patient suicide, with a view to improving outcomes for the doctor, practice staff and bereaved family; and to offer this guideline for further research and development, with a view to it leading to a national guideline. Discussion: In this article, the authors outline the background of the guideline and the difficulties and limitations in its development. Suggestions for future research are offered, along with its potential contribution to patient care and suicide prevention in the future.
... Societal exposure to suicide has also been shown to play a role in suicide causation. Hedström et al. (2008) highlighted that those who are exposed to suicide in their family or workplace are significantly more likely to complete suicide: men who were exposed to suicide in the family were seen to be 8.3 times more likely to complete suicide themselves and were 3.5 times more likely to complete suicide if exposed to suicide in the workplace. Further research has shown that there are also links between media reporting of suicide and suicide rates, which additionally underlines the effects of social exposure to suicide ). ...
Book
“Suicide through a peacebuilding not only fills a significant gap in our wider understanding of conflict transformation around the challenges of suicide, Katerina offers us a significant step forward in how building peace requires a praxis of friendship. A book well worth the read that echo into many spheres of our peacebuilding development.” —Professor John Paul Lederach, Professor Emeritus, University of Notre Dame, USA. “In this accomplished scholarship, Katerina Standish has written a must-read primer for anyone seeking to understand suicide (from any field) and the unique opportunity to peacebuild suicide via relationship. —Professor Sean Byrne, Foundational Director and Director of the PACS Graduate Program at the Arthur V. Mauro Centre for Peace and Justice Studies, University of Manitoba, Canada. “Suicide through a Peacebuilding Lens is a ground-breaking study. Meticulously researched, this book throws new light on the nature & prevalence of suicide. It is a ‘must’ read for peace-building practitioners and a pioneering work of scholarship.” —Professor Padraig O’Malley, the John Joseph Moakley Distinguished Professor of Peace and Reconciliation, University of Massachusetts Boston, USA. This book, as the first exploration of suicide in Peace and Conflict Studies (PACS), illustrates the scarcity of suicide research in the discipline and argues that the leading cause of violent death worldwide is a multifaceted phenomenon that needs to be fully comprehended as a significant and often preventable form of world-wide violence. The author supplies a theoretical framework for assessing suicide as medical or instrumental, posits interdisciplinary complementarity and offers future lines of inquiry that challenge established notions of prevention. The book presents a PACS meta-theory termed ‘encounter theory’ and supplies a suicidal peacebuilding platform via relationship. This book questions why more PACS scholars aren’t turning their attention to suicide when more people die by suicide than ethnic, religious or ‘terroristic’ violence combined. Katerina Standish is Deputy Director and Senior Lecturer at the National Centre for Peace and Conflict Studies at the University of Otago, in New Zealand.
... This mechanism is also known in the sociology of diffusion literature (Rogers, 2003): the more a previously unknown practice becomes popular, the more it gains legitimacy. It is the increased legitimacy of a given practice that spurs its imitation and further diffusion (on the diffusion of suicide via social contagion, see Abrutyn and Mueller, 2014;Baller and Richardson, 2009;Bearman and Moody, 2004;Hedström et al., 2008). Imitation forms the main mechanism in most research on the Werther effect. ...
Article
Anomie and imitation have been prominent mechanisms explaining the Werther effect, i.e., the effect of celebrity suicides on a general population's suicide rate. This study presents a new approach to empirically disentangle both mechanisms. Imitation theory suggests that celebrities act as role models, and that the Werther effect is triggered by the status of the celebrity in question. Anomie theory, on the other hand, suggests that the Werther effect is triggered by the unexpectedness of the event. To this end, we empirically compare the effects of celebrity suicides with the effects of celebrities who died unexpectedly from causes other than suicide (accidents, illnesses, alcohol abuse). Based on language and page-link data from 3855 Wikipedia pages of the 495 celebrities who died from suicide between 1960 and 2014, we measure the status a celebrity has in a particular country and calculate the potential country-specific imitation effect of their suicide. In the same manner, we measure the status of celebrities who died unexpectedly from accidents, illnesses, or alcohol abuse to reflect anomie-related effects. We use these measures in an ecological study based on a time-series cross-sectional dataset for 34 OECD countries to assess their effects on a country's overall annual suicide rate. Fixed-effects analyses reveal that the country-specific status of celebrity suicides is associated with significant increases in overall suicide rates, while anomie-related, unexpected celebrity deaths are not associated with the overall suicide rates. The findings remain robust across a number of alternative specifications, such as controlling for further anomic factors at the macro level (divorce or unemployment rate, for instance). We conclude that the results support the imitation mechanism as an essential social explanation for the Werther effect.
... Societal exposure to suicide has also been shown to play a role in suicide causation. Hedström et al. (2008) highlighted that those who are exposed to suicide in their family or workplace are significantly more likely to complete suicide: men who were exposed to suicide in the family were seen to be 8.3 times more likely to complete suicide themselves and were 3.5 times more likely to complete suicide if exposed to suicide in the workplace. Further research has shown that there are also links between media reporting of suicide and suicide rates, which additionally underlines the effects of social exposure to suicide (Milner et al. 2013). ...
Chapter
This chapter defines the distinctions between social, cultural and political types of violence and investigates how these forms of violence relate to medical suicide and instrumental suicide. The goal of this chapter is to articulate the full complexity of phenomena that involve life-ending acts of self-killing so that they can be problematized and considered in full. There is a distinct difference in the causes of violence in these three human domains of engagement and much can be learned from the fields of sociology, social work, criminal justice, anthropology, political studies and philosophy that delineate and comprehensively consider aspects and incarnations of social, cultural and political violence.
... Societal exposure to suicide has also been shown to play a role in suicide causation. Hedström et al. (2008) highlighted that those who are exposed to suicide in their family or workplace are significantly more likely to complete suicide: men who were exposed to suicide in the family were seen to be 8.3 times more likely to complete suicide themselves and were 3.5 times more likely to complete suicide if exposed to suicide in the workplace. Further research has shown that there are also links between media reporting of suicide and suicide rates, which additionally underlines the effects of social exposure to suicide ). ...
Chapter
This chapter will identify forms of suicide that are instrumental, i.e. life-ending acts connected to a particular aim that involve or include other people. This chapter diverges from the anthropological dimensions of monologic (inward) or dialogic (expressive) suicide to include the object (affected agent and/or accessories) in life-ending acts. Monologic and dialogic suicide refers to the intention of a life-ending act while medical suicide done by individuals (or on behalf of individuals) and instrumental suicides are acts that involve others. While suicide can be inward (monologic) or expressive (dialogic), these terms do not indicate the affected/impacted people from an act. In this chapter, homicide-suicide, martyrdom/altruistic suicide, daredevil suicide and protest suicide will be explored in a manner similar to the previous chapter, with definitions and patterns of the forms, and investigations of the dominant themes within the surrounding literature.
... Societal exposure to suicide has also been shown to play a role in suicide causation. Hedström et al. (2008) highlighted that those who are exposed to suicide in their family or workplace are significantly more likely to complete suicide: men who were exposed to suicide in the family were seen to be 8.3 times more likely to complete suicide themselves and were 3.5 times more likely to complete suicide if exposed to suicide in the workplace. Further research has shown that there are also links between media reporting of suicide and suicide rates, which additionally underlines the effects of social exposure to suicide ). ...
Chapter
This chapter describes intention, motivation and intervention in regard to suicide and separates these processes into medical suicide and instrumental suicide. The purpose of this chapter is to connect facets of understanding regarding suicide to the act of violence transformation. Learning from other fields, suicide, as a topical focus of attention, presents PACS pracademics with opportunities to develop strategies that decrease violence associated with life-ending acts. PACS is a field that seeks not only to recognize violence but to transform violence into nonviolence or ways of engaging with one another that are life-affirming and non-harmful. This chapter looks at how the processes of intention, motivation and intervention can inform transformative considerations and practices in PACS.
Chapter
Full-text available
Most stigma research to date has considered the stigma of mental illness to be a universal occurrence, but one that presents with different manifestations in different contexts. Yang et al., for example, observe that ‘stigma appears to be a universal phenomenon, a shared existential experience’ (Yang et al. 2007) (p. 1528). In a review of the global evidence on stigma and discrimination, Thornicroft concludes that ‘there is no known country, society or culture where people with mental illness (diagnosed or recognised as such by the community) are considered to have the same value or be as acceptable as persons who do not have mental illness’(Thornicroft 2006).
Article
Full-text available
Few suicide studies have examined the separation phase of marital breakdown or the influence of parenthood as predictors of suicide. This study tested the hypothesis that the acute disruption of attachments by separation might be associated with a different suicide rate compared with the longer phase of divorce. Further, we were interested in whether there might be gender differences. A complex methodology was used to circumvent obstacles to this investigation. Subjects were 1375 people who suicided in Queensland between 1990 and 1992 inclusive. Marital status was determined from the Suicide Research and Prevention Program’s suicide register and the Register-General’s records. Rates of suicide were calculated using population data for each marital group. Results showed that separated (compared with married) males were six times more likely to suicide, and this was greater in younger age groups. Separated female suicide rates were not significantly elevated but in the divorce phase both male and female rates were similarly elevated. Marriage was protective for both sexes, especially within the age range of 30 to 54 years. Females with more children had lower suicide rates. Married females who suicided did so later than married males. Males may be particularly vulnerable to suicide associated with interpersonal conflict in the separation phase. It is possible that females may be protected against suicide by child rearing responsibilities but that this protection declines as their children become independent. Further research is needed in this area.
Book
This book explores analytical sociology as an approach for explaining important social facts such as network structures, patterns of residential segregation, typical beliefs, and cultural tastes. It brings together some of the most prominent analytical sociologists in Europe and the United States in an effort to clarify the distinctive features of the approach and to further its development. The volume is organized into four parts. Part I describes the foundations of analytical sociology while Part II discusses the role of action and interaction in explaining diverse social processes such as emotions and beliefs. Part III looks at the macroscopic social dynamics brought on by the activation of the cog-and-wheel mechanisms, tackling topics ranging from segregation dynamics to divorce and social influence. Part IV concludes the book by asking how analytic sociology relates to other fields and approaches such as game theory, analytic ethnography, and historical sociology.
Article
Building on his earlier influential contributions to contemporary debates on social theory, Peter Hedstrom argues for a systematic development of sociological theory so that it has the explanatory power and precision to inform sociological research and understanding--qualities lacking in much of the grand social theorizing currently fashionable.
Article
This paper shows that suicides increase immediately after a suicide story has been publicized in the newspapers in Britain and in the United States, 1947-1968. The more publicity devoted to a suicide story, the larger the rise in suicides thereafter. The rise in suicides after a story is restricted mainly to the area in which the story was publicized. Alternative explanations of these findings are examined; the evidence indicates that the rise in suicides is due to the influence of suggestion on suicide, an influence not previously demonstrated on the national level of suicides. The substantive, theoretical, and methodological implications of these findings are examined.
Article
In recent years, there have been numerous quasi-experimental studies of aggregate mortality data. These studies conclude that mass media portrayals of violence cause imitative responses among the public. This paper examines the logic of this research, arguing that it does not meet the special burdens of proof associated with quasi-experimental studies that use aggregate data to make inferences about individual behavior. We present detailed evidence suggesting that imitation effects attributed to mass media events (prize fights and television news stories about suicides) are statistical artifacts of the mortality data, the timing of media events, and the methods employed in past research. The concluding section discusses some implications of our analysis for future studies of imitative violence and for other areas of research.
Article
Since the nineteenth century, social scientists have been unable to explain age and gender differentials in the risk of suicide. Almost universally, men have a greater risk of suicide than women. Furthermore, in economically developed countries, the risk tends to be highest for men in old age and for women in middle age. Age patterns of suicide in some Third World countries are fundamentally different than this. I test an interdisciplinary theory that focuses on role identities, economic development, and kinship institutions to account for these patterns.
Article
This paper presents evidence indicating that imitation and suggestion have a powerful impact on social behavior. The major findings of the paper are: (1) After publicized murder—suicide stories there is an increase in noncommercial plane crashes and an increase in airline crashes. (2) This increase in crashes persists for approximately nine days, and then the level of crashes returns to normal. (3) The greater the publicity given by the mass media to a murder—suicide story, the greater the increase in airline crashes and the greater the increase in noncommercial plane crashes. Alternative explanations for the findings are tested. The best available explanation is that publicized murder—suicide stories trigger additional, imitative murder—suicides, some of which are disguised as airplane accidents. The second half of the paper moves from the empirical findings towards a modern sociological theory of imitation and suggestion. Some nineteenth century sociologists began to theorize upon this topic, but modern sociologists have virtually ignored it. Both the empirical evidence and the theoretical discussion presented in this paper suggest that it may be worth reopening a line of research which has been closed since the turn of this century.