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Depression Prevention in the Workplace: What the Research Shows About Interventions That Work

Disruption in the Workplace, Disability Management, Human Resources, Leadership, Mental Health, Occupational Health & Safety, Psychosocial Factors
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Depression is prevalent in workplace and has a huge impact on employee health and productivity. However, employers and organizations are struggling in finding measures for dealing with this significant health and economic issue. There are many strategies for reducing the burden of workplace depression. Dr. JianLi Wang’s team at the University of Ottawa Institute of Mental Health Research has conducted a systematic review and meta-analysis that identified evidence – based interventions that may be used as proactive measures for preventing workplace depression.

Learning Outcomes

Different types of public health strategies for preventing depression
Effective workplace interventions for depression [demonstrated by randomized controlled trials]


Dr. JianLi Wang, PhD
Dr. JianLi Wang is a Professor of the School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa. He holds the position of Senior Scientist and Director, Work & Mental Health Research Unit of the Institute of Mental Health Research affiliated with University of Ottawa. Prior to joining uOttawa in 2017, he was a Professor of the Departments of Psychiatry and of Community Health Sciences, University of Calgary. Dr. Wang received his PhD in Epidemiology at the University of Calgary. Dr. Wang’s research interests are in two areas: workplace mental health and risk prediction analytics. In the domain of workplace mental health, Dr. Wang is leading a national team project on early identification and prevention of major depression in male workers, funded by Movember Foundation. This project is to develop and evaluate e-mental health program to be used by male workers to reduce the risk of having major depression. In the risk prediction research funded by the Canadian Institutes of Health Research, Dr. Wang’s team developed and validated the first sex-specific prediction algorithms for the risk of developing major depression in the general population. Presently his team is conducting a national randomized controlled trial to examine the benefits and potential psychological harms associated with disclosing personalized depression risk information to users.

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