Unemployment as a Risk Factor for Mental Illness: Combining Social and Psychiatric Literature

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Advances in Applied Sociology
2013. Vol.3, No.2, 131-136
Published Online June 2013 in SciRes (http://www.scirp.org/journal/aasoci) http://dx.doi.org/10.4236/aasoci.2013.32017
Copyright © 2013 SciRes. 131
Unemployment as a Risk Factor for Mental Illness:
Combining Social and Psychiatric Literature
Shuo Zhang1, Vishal Bhavsar2
1King’s College Medical School, King’s College London, London, UK
2Institue of Psychiatry, King’s College London, London, UK
Email: shuo.s.zhang@kcl.ac.uk, vishal.2.bhavsar@kcl.ac.uk
Received February 15th, 2013; revised March 16th, 2013; accepted March 23rd, 2013
Copyright © 2013 Shuo Zhang, Vishal Bhavsar. This is an open access article distributed under the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
Unemployment has been shown to have wide ranging effects on physical and mental health. This review
looks to clarify the relationship between unemployment and mental illness specifically, in terms of estab-
lishing causality, effect size and moderating factors. The current rational for research combines an etio-
logical approach and interest in the social causation of disease with past work from a social psychological
perspective. For this review, PsychInfo, Medline and Embase databases were searched between the years
of 1970 and 2011, for prospective studies that include unemployment and mental illness terms. 10 studies
were found which matched the inclusion criteria. Studies were included if they studied the long term un-
employed, defined the age and gender of their study population, defined their outcome measurements in
medical terms, and followed a population prospectively over time. Overall unemployment did precede
mental illness; however the exact effect size is unclear. A quantitative meta-analysis was not conducted
due to the variability in study design. The discussion tries to point to methodological and theoretical limi-
tations that affect investigations into unemployment and mental illness. It concludes that the work has so
far been skewed by individual biases, and that there needs to be wider collaboration between the social
sciences and psychiatry.
Keywords: Unemployment; Mental Illness; Schizophrenia; Depression; Etiology
Introduction
Unemployment defines a section of the population who is not
currently at work but has the capacity to, and is actively seeking
to work (Collins English Dictionary, 2011). Unemployment has
been shown to negatively impact both physical and mental
health (Brenner, 1988). The first descriptive studies character-
ized mental health related outcomes as “depression, anxiety,
poor self-esteem, isolation and strain on the family” (Donovan
et al., 1987). Further many cross-sectional studies have demon-
strated an association between unemployment and mental ill-
ness (Paul & Moser, 2009). Perhaps it is because the impacts of
unemployment are so common sense and wide ranging that the
topic has attracted limited interest from psychiatry. There has
been much work on the mental health impacts of unemploy-
ment but very little on its relationship with clinically defined
mental illness. Work on unemployment and mental illness has
so far looked mainly at rates of employment in people who
already have a psychiatric diagnosis (Marwaha et al., 2007),
and re-employment as a positive goal in the recovery from dis-
ease episodes (Secker et al., 2001). Although work in looking at
general impacts of unemployment and mental health has been
fruitful, little has focused specifically on unemployment as a
prospective risk factor for mental illness.
Unemployment has been investigated in the broader context
of physical illness. Interest in the health consequences of un-
employment began in earnest in the 1980s with the last eco-
nomic depression. Unemployment has been found to be associ-
ated with overall morbidity and mortality as well as poorer
scores on a range of health outcome measurements (Graetz,
1993). Brenner (1979) previously inferred consequent cardio-
vascular impacts from the somatization of the stress response;
however investigations have not confirmed any significant
results (Kasl & Cobb, 1980). What is interesting is that health
seems to be mediated by factors like social support. Gore (1978)
found that the unemployed who also lacked social support had
the highest rise in blood cholesterol. Linn et al. (1983) found
that the unemployed visited the doctor more, took more medi-
cation, and spent more sick days in bed, even though they did
not have more diagnosis of physical illness than the employed.
This suggests that there is a significant psychological compo-
nent to physical illness in unemployment.
This paper reviews the studies conducted so far which look at
the effect of unemployment on mental illness prospectively and
assesses the potential of this approach in furthering the under-
standing of social factors in the etiology of mental illness. It
aims to summarize the findings of the studies, and critically
assess the underlying methodological and theoretical assump-
tions with the view of making recommendations for future re-
search. Research into unemployment and mental illness poses
many challenges in terms of the consistency of databases, out-
come measurements, and control of contextual factors. It also
raises important questions in terms of effect size, moderating
factors and direction of causality. These questions and chal-

S. ZHANG, V. BHAVSAR
lenges are common for other social etiological factors in mental
illness. It is hoped that a better understanding of unemployment
as a risk factor will inform the wider field.
Unemployment as a Prospective Risk Factor
The motivations for looking at unemployment specifically as
a social risk factor in the development of psychiatric illness
come from a few different rationales. Previously the bulk of the
work has been by social psychologists with a view of advocat-
ing socioeconomic policies that are cognizant of public mental
health consequences, and the subsequent healthcare and pro-
ductivity costs. The current shift in focus to investigating un-
employment as a risk factor comes from a synthesis of recent
developments within psychiatric epidemiology and the social
causation of mental illness with past work in social psychology.
Firstly there has been renewed interest in the social causation
of disease, and in the factors that increase the incidence of
mental illness (Ferrie, 2001; Marmot, 1978). Furthermore the
health impacts of unemployment offers a mechanism that links
social, psychological and biological impacts. Bartley (1994)
proposes four types of explanations for the impacts of unem-
ployment: poverty, stress, health related behavior and the effect
of unemployment on the rest of the work career. These mecha-
nisms have mixed impacts on physical and mental health; the
reactions to financial strain and change in status can have
physical health impacts directly or lead to the somatization of
stress response, and to poorer health behaviors such as sub-
stance abuse and less physical activity
At the same time, there has been a revival of interest into so-
cial factors in the etiology of diseases such as schizophrenia
(Tandon, 2008). Recent work on urbanicity and migration using
an epidemiological approach has been fruitful in understanding
the role of social stress in mental illness (Cantor-Graae & Sel-
ten, 2005). The current interest in unemployment and mental
illness comes in part from past interest in the role of social fac-
tors such as migration and urbanicity in the etiology of schizo-
phrenia. Many similarities can be drawn from looking at the
theoretical and methodological approaches of past investigation.
It also exposes the challenges of disentangling a web of com-
mon moderating factors and proposed mechanisms for migra-
tion, urbanicity and unemployment (Tandon, 2008). The envi-
ronmental factors which predisposes us to developing mental
illness is still not well understood. However epidemiological
risk factors are already used for clinical practice, for example
the presence of physical disease, social stresses, interpersonal
difficulties and lack of social support in the development of
depression (Semple & Smyth, 2009). Therefore any approach
which clarifies these interactions will also increase our under-
standing of the social causation of mental illness.
Previous Approaches from Social Psychology
There has been a century of work on the mental health im-
pacts of unemployment within a social psychology framework.
Important meta-analytic reviews which summarise the field
include (Paul & Moser, 2009, Murphy & Athanasou, 1999,
McKee-Ryan et al., 2005). In common they possessed a pro-
spective approach to clarify direction of causal effect, the effect
size and the interaction of unemployment with other variables
such as gender, employment duration and financial hardship.
Studies on unemployment and mental illness have so far all
been from a social psychological perspective, therefore it is
important to be aware of the theoretical and methodological
contexts of the field.
The theoretical basis of research has so far been framed in
terms of the work on unemployment and mental health by three
theorists. Jahoda’s (1982) deprivation theory first proposed a
mechanism by which unemployment caused mental distress
through negative affect on a range of 5 factors: time structure,
social contact, collective purpose, status and activity. Warr
(1987) developed this idea to include further environmental
factors termed “vitamins” that had more complex relationships
with the effects of unemployment. These “vitamins” varied
with subjective measures of wellbeing that vary with exposure
in a more complicated way. In contrast to the two, Fryer (1986)
emphasized the importance of human agency as a mediator of
the effect of unemployment on mental health, and also re-es-
tablishes a role for material deprivation as a significant contrib-
uting factor. All three theorists therefore conceptualize the im-
pact of unemployment as an effect of qualities of the external
environment upon an individual.
Methodologically this has led to an investigative approach
that looked to clarify the association and describe the nature
and extent of the impacts. Therefore past reviews have focused
on questions of effect size, moderator variables such as gender,
age and duration of unemployment, and the problem of causal-
ity. This review acknowledges the relevance of these concerns
on the more specific question at hand in clarifying causal
mechanisms. It aims to depart from previous reviews by as-
sessing the benefits and challenges of an epidemiological ap-
proach investigating unemployment as a risk factor in develop-
ing mental illness as opposed to clarifying its impacts on men-
tal health.
Methods
A comprehensive literature search was undertaken. The da-
tabases MEDLINE, psychINFO and EMBASE were used for
relevant publications from January 1970 to November 2011.
Key words “unemployment” and/or “employment” were used
to describe job status and “psychosis”, “schizophrenia”, “de-
pression” and/or “mental health” for the range of health conse-
quences. “Cohort” was added to limit our search to prospective
studies. These were combined for our total number of hits. Ta-
ble 1 illustrates the results retrieved according to keyword
categories and databases.
An initial literature search resulted in a total of 116 results.
Inclusion and exclusion criteria focused the results to the ques-
tion at hand: 1) subjects had to be long term unemployed, how
this is defined was database dependent but a minimum criterion
of longer than 12 weeks was thought reasonable; 2) Study had to
Table 1.
Number of results according to keyword categories and databases.
Database
Keyword Psych Info Medline Embase Total
Job status 14,371 37,474 54,303 106,148
Mental
disorders 253,416 18,5063 396,725 835,204
Cohort 58,809 129,566 104,174 292,549
And 41 65 10 116
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S. ZHANG, V. BHAVSA
Copyright © 2013 SciRes. 133
be prospective, therefore involving some sort of follow up over
time; 3) Outcome measures had to be clinically based, i.e. when
medical help was sought, or DSM and other diagnostic scoring
systems; 4) The population had to be defined in terms of gender,
and/or age and sociodemographic measures. Figure 1 illustrates
the search tree. 3 results came from our initial search, further
results came from cross referencing and hand searches.
population based studies from the 1990s.
Discussion
Unemployment as a Risk Factor, What Are the
Findings?
Effect Size
All the results show quantitatively that unemployment in-
Results
10 studies are included in our results. These results are sum-
marised in Table 2. Overall there were 4 studies from Scandi-
navian countries (Lamberg et al., 2010; Agerbo et al., 2010;
Hämäläinen et al., 2005; Agerbo et al., 1998), 2 from Britain
(Weiss & Lewis, 1998; Bolton & Oatley, 1987), 2 American
studies (Dew & Bromet, 1992; Dooley & Catalano, 1994), 1
German (Frese & Mohr, 1987) and 1 study from New Zealand
(Fergusson & Horwood, 1997). The studies used a mix of
clinical and self-report diagnostic criteria: 6 studies examined
depression (Lamberg et al., 2010; Hämäläinen et al., 2008;
Frese & Mohr, 1987; Bolton & Oatley, 1987; Dew & Bromet,
1992; Dooley & Catalano, 1994) whereas four looked at com-
mon mental disorders that included depression and anxiety
(Fergusson & Horwood, 1997; Weiss and Lewis, 1998; Agerbo
et al., 2010; Agerbo et al., 1998) There were none that focused
on schizophrenia specifically. There was a trend in study design
with the earlier studies from the late 1980s user smaller cohort
groups that were individually followed up to later large scale Figure 1.
Search tree.
Table 2.
Summary of Studies.
Author Year Country Data Source
Sample
Size Age Mental Illness Studied Diagnostic Criteria Other Factors
Investigated
Frese M., Mohr G., 1987 Germany Administered
questionnaires 51 over 45,
men depression Zung’s depression
scale hope for control,
financial problems
Bolton W., Oatley K. 1987 Britain interviews at job
centres 49 20 - 59,
men depression Beck’s depression
inventory
social support,
emotional support,
material assistance,
Dew A. M., Bromet E. J.
Penkower L. 1992 USA panel data from a
factory lay off 141 women depression and anxiety Hopkins Symptom
Checklist effects of gender
Dooley D., Catalano R. 1994 USA Epidemiologic
Catchment Area Study 8278 adult depression DSM-III reverse causality
Fergusson D.M., Horwood
L. J., Lynskey M. T. 1997 New
Zealand
Christchurch Health
and Development
Study 1265 up to 18
major depression, anxiety
disorders, conduct disorder,
other substance
abuse/dependence and
attempted suicide
DSM- IV time of exposure, also
social, family and
personal factors
Weich S., Lewis G., 1998 Britain British household
panel survey 7726 16 - 75 common mental disorders general health
questionnaire poverty
Agerbo E. Eriksson T.
Mortensen P.
Westergard-Nielsen, 1998 Denmark
merging Central
Psychiatric Case
register and data from
Danish administrative
registers
<15,000 16 - 75 common mental disorders admissions
income, gender, impact
of business
cycles/stigmatisation
hypotheses
Hämäläinen J., Poikolainen
K., Isometsä E., Kaprio J.,
Heikkinen M., Lindeman
S., Aro H.
2005 Finland 1996 Finnish Health
Care Survey 5993 major depression
institutionalization
and UM-CIDI
Short Form
frequent alcohol
intoxication
Agerbo E., Eriksson T.,
Mortensen P.,
Westergard-Nielsen, 2010 Denmark
merging Central
Psychiatric Case
register with data from
Danish administrator
registers
<15,000 16 - 65 common mental disorders admissions previous unemployment,
duration, business cycle
Lamberg T., Virtanen P.,
Vahtera J., Luukkaala T.,
Koskenvu. 2010 Finland Finnish HeSSup
population sample 14,487 depression
Beck’s depression
inventory retirement

S. ZHANG, V. BHAVSAR
creased the measures of mental disorders. The prospective de-
sign of the studies shows that unemployment precedes the de-
velopment of mental illness, therefore suggests a causal mecha-
nism. A meta-analysis was not undertaken because of the large
variation in study design and outcome measures. Only 3 papers
gave their results in terms of an odds ratio (Dooley & Catalano,
1994; Weiss & Lewis, 1998; Hämäläinen et al., 2005) which
was insufficient for further statistical analysis. The odds ratios
all fell within a comparable range, from ODs 1.78, 95% CI 1.38
- 2.29 (Hämäläinen et al., 2005 ) to 2.08, 95% CI 1.38 - 2.77
(Dooley & Catalano, 1994). From a theoretical perspective
clarifying the effect size is important in terms of assessing the
effect size of a particular risk factor, and its causal relatedness.
However, here it may be more useful to look at interactions
with confounding factors and the underlying motivations of the
authors in study design. The review goes on to discuss these
biases which form the context of methodological and theoreti-
cal limitations which effect the interpretation of unemployment
as a risk factor.
Reverse Causality
This has been a key concern of past studies (Paul & Moser,
2009). Symptoms of mental illness, such as social withdrawal
and behavioral disorders have been thought to lead to job loss.
Also mental illness might impede a person’s capacity to find a
job. In this review only Dooley and Catanalo (1994) explicitly
addressed the question that depression predisposes to unem-
ployment through quantitative analysis. They found no signifi-
cant association between depression and unemployment. How-
ever the authors were unconvinced, as they found that other
health diagnoses predict unemployment. They proposed that
discrimination labor laws prompted employers to give other
reasons for firing workers instead of their depression. This
therefore raises the problem of bias in the data captured.
Methodological limitations
Study Selection
Challenges in study selection comes mainly from the large
number of studies from social psychology and occupational
psychology which look at the effect of unemployment on men-
tal health using very general measures. Diversity in study de-
sign presented many results which satisfied the inclusion crite-
ria but also had other directions of interest. It was decided to
include this breadth. A limitation of the search is that some
studies could not be captured due to being in social science
databases, however it is hoped that with the addition of hand
searches and cross referencing the search was in the end com-
prehensive.
Outcome Measurements
The impacts of unemployment have been investigated in
terms of health and mental health outcomes, with mental illness
being a specific measure of wider mental health outcomes. The
papers used different outcome measurements due to the scope
and interests of their own studies. Dew and Bromet (1992)
looked at increases in symptomology. Others (Fergusson &
Horwood, 1997) divided data along the extent and duration of
unemployment, therefore illustrating the diversity of experi-
ences the category could encompass, thus complicating both
data collection and interpretation. Paul and Moser (2009) ad-
dressed this problem by segregating their results and looking at
the impact of moderator variables on effect size. In terms of
unemployment and mental health, motivations for research
have been so far focused on articulating the extent of these
mixed symptoms of distress as well as in putting forward tenta-
tive explanatory mechanisms. Clarifying the impacts of unem-
ployment on mental illness is limited by how mental illness is
measured. Mental illness is both a discrete diagnosis and varies
in severity, which means that it is often taken to be an increase
in symptomology and be more subjective. Further having
symptoms of mental illness may not lead to a clinical diagnosis.
This is particularly true in generalized conditions such as de-
pression and anxiety. Therefore the studies have tended to ig-
nore more strict clinical criteria, and instead focused on proving
negative affect. Agerbo et al. (1998, 2010) did use more direct
cut offs, like admissions to hospital and seeking medical service,
but two separate data sets had to be combined, one of admis-
sions and one of employment data. Other studies used self-
report scales, which although clinical captured a range of rat-
ings. A way of reducing this variance would be to look at a
mental illness such as schizophrenia which has a smaller spec-
trum of symptoms. A key question that needs to be addressed
first is whether measuring an increase in symptoms would be
useful for unemployment research.
Database
The collection of data poses many challenges as unemploy-
ment is a much more variable social factor, therefore it is more
difficult to capture and track. Prospective data sets for these
studies were captured on a population level with a long term
follow up (Lamberg et al., 2010; Weiss & Lewis, 1998), or
through recurrent interviews with a selected number of smaller
samples (Frese & Mohr, 1987; Bolton & Oatley, 1987; Dew &
Bromet, 1992). The methods selected perhaps depended on the
quality of data already available, for example the Scandinavian
studies (Lamberg et al., 2010; Agerbo et al., 2010; Hämäläinen,
2005; Agerbo et al., 1998) were able to make use of compre-
hensive social data set gathered centrally. However even this is
challenging, Agerbo et al. (1998, 2010) for example had to
combine data sources. The differences in data capture also
make it difficult to compare the effect of the duration of unem-
ployment.
Contextual Factors
There are country specific factors which influence the inter-
pretation and comparison of studies from across different socie-
ties and also time frames. Factors include year of data collec-
tion, the economic development of the country, and the level of
individualism/collectivism (Paul & Moser, 2009). These offer
both practical and conceptual challenges. These differences in
data, such as varying business cycles can provide evidence for
the economic stress hypothesis (Dooley & Catalano, 1983)
which proposes that negative impacts of unemployment are less
during an economic downturn when being unemployed is no
longer so stigmatizing. Therefore country specific factors such
as the level of social support, and general economic perform-
ance also effect the interpretation of theory.
Methodological Limitations
Moderator Variables
The effect of unemployment is mediated by many other
variables. These create challenges to understanding the causal
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S. ZHANG, V. BHAVSA
relationship between unemployment and mental illness. Each
study has its own theoretical basis from which different mecha-
nisms are clarified, as reflected by the diversity of study design.
Gender has been suggested to mediate the effect of unem-
ployment on mental illness through differences in perceived
identity, interpersonal relationships, and social stigmatization
(Paul & Moser, 2009). Papers (Frese & Mohr, 1987; Bolton &
Oatley, 1987) published in the late 1980s used single sex co-
horts; this perhaps reflected the lesser degree of gender equality
in the work force at that time. Dew and Bromet (1992) found
that that unemployment has a lesser impact on women and
proposed that this was due to different gender roles with
women valuing their jobs less and gaining more self-esteem
from their family. Interestingly one of the single sex male stud-
ies looked at the role of social support as mediating mental
illness (Bolton & Oatley, 1987). It is well established that gen-
der interacts with other variables, however it has yet to be de-
termined conclusively whether there is a gender bias in the
mediating effects of social or partner support; so far there has
been no studies that have looked at its impacts in both sexes.
Social support is also a moderating factor in its own right (Paul
& Moser, 2009). Hämäläinen et al. (2005) looked at unem-
ployment and alcohol intoxication, which is in itself a risk fac-
tor for depression. It also suggests a role for gender specific
behaviours in the reaction to unemployment.
Age was another factor of interest to some of the studies.
Fergusson and Horwood (1997) looked at young people,
whereas Lamberg et al. (2010) looked at those close to retire-
ment age. These two cohorts would have very different expec-
tations of employment. The papers also have different interests,
Fergusson and Horwood (1997) focusing on predisposing fac-
tors, and Lamberg et al. (2010) on the links with disability re-
tirement and its subsequent economic impact. Frese and Mohr
(1987) looked at the impact of financial deprivation, and tried
to assert the impact of financial stress, leading to learned help-
lessness and a stigmatizing status. These research directions
come from the theoretical context of social psychology in
clarifying causal mechanisms and relationships of unemploy-
ment and mental illness. Moderating factors such as gender,
social support, age and financial deprivation are also important
etiological factors in depression and schizophrenia. Importantly
this illustrates the wealth of information that studies on unem-
ployment and mental illness can contribute to clarifying causal
mechanisms of other risk factors. The recent AESOP paper
(Reininghaus et al., 2008) did try to synthesis results within a
theoretical framework. Proposed mechanisms for the effect of
migration involve increased social stress, expectation- reality
mismatch and change in social status and self-perception. Fur-
ther, both the effects of migration and urbanicity seem to be
moderated by other factors such as gender, age, and ethnicity.
This highlights the importance of understanding environmental
and experiential predisposing factors such as unemployment in
the broader etiological framework.
Quality of Employment?
Key theoretical assumptions that underpin research into un-
employment and mental illness depend on unemployment con-
ceptualized as a loss of certain qualities. Unemployment as a
variable presumes that employment provides the individual
with certain benefits, such as time structure, money, and status,
the lack of which will cause mental illness. However there has
been a recent shift in the field of social psychology into looking
at the qualities of employment, and how that impacts on mental
health. It has been argued that it is not employment per se that
is protective against mental distress, but the quality of that em-
ployment and the perceived security of that job (Burchell et al.,
2002).
Future Recommendations
Unemployment is a difficult risk factor to study due to
methodological and theoretical challenges. However, a com-
bined approach across the social and epidemiological sciences
to incorporate employment histories in prospective population
databases may offer a solution. Already databases such as
AESOP are beginning to incorporate such information, al-
though so far its analysis has used cross-sectional data and
therefore could not ascertain any causal relationships directly.
There should be greater collaboration between different studies
to include a breadth of measures that characterize a person’s
employment status. Further it might be conducive to set up
collaborations with social science. Important questions which
still need to be answered are: 1) should unemployment be in-
corporated as a confounder in other etiological studies that look
at for example migration, or urbanicity; 2) to what extent do
these factors interact with each other; and 3) to what extent can
we clarify these interactions through investigation.
Conclusion
Unemployment does increase the risk for going on to de-
velop mental illness. The evidence is strong for depression and
anxiety, although the exact effect size is unclear. No studies
were found that look at the unemployment and schizophrenia.
This review points to both the methodological and theoretical
challenges in trying to clarify such etiological relationship.
However it also emphasizes the benefits of collaboration be-
tween psychiatry and the social sciences. Understanding the
role of unemployment as a risk factor is beneficial for future
clinical and socioeconomic interventions. The focus should be
on developing a consistent methodological approach that clari-
fies the theory.
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