Annotated bibliography: Unemployment and mental health

 Bidargaddi, N., Bastiampillai, T., Schrader, G., Adams, R., Piantadosi, C., Strobel, J., & … Allison, S. (2015). Changes in monthly unemployment rates may predict changes in the number of psychiatric presentations to emergency services in South Australia. BMC Emergency Medicine, 15(1), 1-6.  

The aim of this paper was to establish if monthly presentation rates to Mental Health Emergency Departments (MHED) in South Australia Public Hospitals (SAPH) was associated with Australian Bureau of Statistics (ABS) unemployment rates. The data was collected using times series modelling of relationships between monthly MHED SAPH presentations obtained from the Integrated South Australian Activity Collection (ISAAC) and the ABS South Australia unemployment figures between January 2004 and June 2011. The study found that over 32% of MHED presentations in males could be predicted by male unemployment rates from the two months prior. Over 63% of MHED presentations in females could be predicted by male and female unemployment in the previous months. They concluded that small shifts in unemployment rates can increase MHED presentations particularly in women and that ABS unemployment statistics can be a useful tool for predicting future MHED. A limitation of this study is that it establishes an association between MHED presentations and unemployment but not causality, so increased unemployment might not be the cause of the increase in MHED presentations.

 Buffel, V., van de Straat, V., & Bracke, P. (2015). Employment status and mental health care use in times of economic contraction: a repeated cross-sectional study in Europe, using a three-level model. International Journal for Equity in Health, 14(1), 1-19.

 This study aimed to compare the mental health care use of the unemployed with that of the employed and whether the relationship between unemployment status and mental health care use varied across different economic climates. They wanted to establish whether the economic context affected mental health care use due to its impact on mental health or irrespective of mental health. Data from three waves of the Eurobarometer (2002, 2005/6 and 2010) was utilised, which consists of a repeated cross-sectional and cross-national design. The data was analysed using linear and logistic multi-level regression in which mental health and contacting a medical practitioner for mental health issues were considered variables. They found that mean unemployment rate was negatively associated with mental health, although in women this only applied to those employed. There was no association found in women between changes in the macro-economic climate and mental health.  Men’s care use however is associated with changes in the unemployment rate and gross domestic product (GDP) irrespective of mental health. This is true of both employed and unemployed men. They conclude that it is important to consider macro-economic conditions when studying mental health care use, particularly in men. A limitation noted in the study is that the Eurobarometer records employment status at the time of the interview and mental health in the twelve months preceding the interview. Therefore it is not able to distinguish between causation and reverse causation for any association between mental health and employment. 

Crowe, L., Butterworth, P., & Leach, L. (2016). Financial hardship, mastery and social support: Explaining poor mental health amongst the inadequately employed using data from the HILDA survey. SSM – Population Health, 2(1), 407-415.

 Data from the Household Income and Labour Dynamics in Australia (HILDA) Survey were analysed to try and establish if there was a relationship between employment status and mental health, along with the effects of financial hardship, mastery and support. They also wanted to explore how duration of unemployment impacted on mental health. Three waves of data were analysed from the HILDA Survey which encompassed 4965 adult respondents. The relationship between employment status and mental health was assessed using longitudinal population-averaged logistic regression models to explain associations between employment groups (unemployed vs. employed; employed vs. underemployed). The effect on duration of unemployment on mental health was evaluated using regression analysis. Unemployed or underemployed respondents exhibited poorer mental health than their employed counterparts. Mastery, financial hardship and social support ameliorated this association particularly in the underemployed. Transition to unemployment was associated with a decline in mental health among a broad age range of respondents.  The relationship between mental health and unemployment duration was not linear but mental health showed a marked decline in the first nine weeks. The study concluded that mastery, financial hardship and social support are important factors to consider in the understanding of the relationship of poor mental health and un- or underemployment. It also suggests intervention should commence immediately after job loss with deterioration in mental health being most severe in the first weeks before plateauing.  A limitation in this study is the possibility of reverse causation or low mastery and lack of social support causing unemployment.

 Limm, H., Heinmüller, M., Gündel, H., Liel, K., Seeger, K., Salman, R., & Angerer, P. (2015). Effects of a Health Promotion Program Based on a Train-the-Trainer Approach on Quality of Life and Mental Health of Long-Term Unemployed Persons. Biomed Research International, 2015(1),

 The authors of this study state that long-term unemployment is associated with poorer mental health. They therefore conducted this study to evaluate the effectiveness of a health promotion program to improve the mental health and health related quality of life (HRQL) utilising the train-the-trainer approach. A parallel-group study was performed using 287 unemployed participants (179 were in the intervention group and 108 in the control group), who were reassessed after 3 months. The intervention comprised individual sessions based on motivational interviewing and participatory group sessions, with the control group receiving no health promotion. Within 3 months HRQL improved and symptoms of depression and anxiety decreased in the intervention group, but not in the control group. The trainers were all professionals (mainly social workers) who had received three days training to deliver the interventions.  A limitation of this study was that participants were not “blinded” and the positive results may be influenced by this. 

Olesen, S., Butterworth, P., Leach, L., Kelaher, M., & Pirkis, J. (2013). Mental health affects future employment as job loss affects mental health: findings from a longitudinal population study. BMC Psychiatry, 13(1), 144.

 Internationally, participation in the workforce is regarded as an important factor in mental health policies and social inclusion. This study aimed to examine simultaneously the effects on mental health on unemployment and how mental health effects employment prospects and participation. The data was derived from respondents who completed the nine waves of the HILDA Survey in Australia. They were all of working age (20-55 years) at commencement of the study (n=7176). Simultaneous relationships between employment and mental health were tested over time using cross-lagged path analysis, whilst adjusting for sociodemographic differences. They found that poor mental health was both a result of and a predisposing factor for unemployment. Poorer mental health in people who are unemployed can be both attributable to the unemployment and existing mental health issues. In women both these factors had equal rating, whereas in men the impact of unemployment on mental health was weaker than mental health on subsequent unemployment. The data available in the HILDA survey meant that the researchers were limited to using the respondents’ concept of their mental health rather than diagnosed mental illnesses.

 Strandh, M., Winefield, A., Nilsson, K., & Hammarström, A. (2014). Unemployment and mental health scarring during the life course. The European Journal of Public Health, 24(3), 440.

 The long-term relationship between unemployment and mental health over the life course has been little researched. This study examined the relationship between youth unemployment along with periods of adult unemployment and mental health at several life stages (16, 18, 21, 30 and 42 years) who all graduated from compulsory school in a town in Sweden.  Originally there were 1083 participants and of those still living at the 27 year follow-up, 94.3% were still involved. The researchers measured mental health in three ways: nervous symptoms, depressive symptoms and trouble sleeping. These were analysed using a repeated measures linear mixed models approach at ages 16, 21, 30 and 42 years. Unemployment was measured using a period of unemployment of at least six months over three time periods: 18–21, 21–30 and 30–42 years. They found that youth unemployment was significantly associated with poor mental health at ages 21, 30 and 42 years. Later single unemployment periods did not appear to have the same long-term effects, although two or more periods of unemployment did have a significant relationship with poor mental health. A limitation of the study is its small geographical sample base, with consequent limits on sociodemographic variants.

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