P246 Measurement and integration of work- and non-work-related psychosocial stressors

Research on work-related psychosocial stressors and workers’ mental health has primarily focused on a few dominant theoretical models (i.e., demand-control-support, effort-reward imbalance). Recognising that other components of a workers’ social environment (e.g., family, social network, community-level factors) and individual factors have been independently associated with mental health, a growing number of studies are attempting to integrate work, non-work, and individual determinants of mental health and stress. Yet including multiple categories of psychosocial stress exposure into a single analysis requires consideration of whether the measures employed are measuring distinct or overlapping concepts. Employing dimension reduction techniques may provide a data driven approach to measuring underlying constructs of stress. A conceptual and theoretical approach, however, may also help researchers gain clarity on which measures of stress to include and why. Here we propose a simple conceptual framework to evaluate the potential for conceptual overlap among commonly used psychometric scales and data sources used for measuring stress-related risk factors in work and non-work domains. We describe specific groups of measures that simultaneously provide information on a shared construct while keeping in mind both the importance of life course and different domains at which stressors may be measured. For example, stressors faced at the neighbourhood or contextual level may encompass features of the social, physical, or built environment and may work synergistically to impact mental health. On the other hand, measures of adversity faced during childhood are known to have long lasting mental health outcomes and may be distinct from measures of chronic stress related to a brief period of unemployment or other stressful life event. These findings inform how work- and non-work-related measurements are related, potentially improving exposure assessment and predictive ability of stress risk factors. Researchers are advised to consider conceptual overlap when assessing sources of stress exposure across multiple domains.