The Development of an Experience-Based Model of Work-Non-Work Adjustment in a Sample of Queensland Teachers

Abstract

Work-life balance (WLB) has emerged as an important field of research and practice over the last 20 years. Increased female participation in the workforce, an ageing population, and the changing nature of work, have all increased interest in how individuals balance their work and non-work roles. In particular, research and practice have focused on reducing the stress and role-conflict associated with participation in multiple roles. Although, no real consensus on the definition or conceptualisation of work-life balance has been reached, Frone’s model of WLB is the most widely accepted and researched conceptualisation of balance. Frone’s model focuses on the interaction between work-life conflict and work-life facilitation, whereby balance is a result of low conflict and high facilitation, and is similar to stress models, such as Karasek’s demands-control-support model or the job demands-resources model. Despite its popularity, little support has been published for Frone’s WLB model. In addition, research on WLB has mostly focused on how to reduce the occupational impact of workers engaging in multiple roles, so although the fit between demands and resources of the work environment have been addressed, other ideas from stress research have not been as well considered. Introducing non-work factors into pre-existing and well-established occupational stress models should provide a clearer understanding of work-life interactions. Specifically, the cognitive activation theory of stress (CATS) is relevant to the work-life interface as it refers to an individual’s appraisal and management of any stressors encountered, whether work- or non-work-related. Based on the similarities between occupational stress and WLB literatures, an experience-based model of work-non-work adjustment was developed and tested, which incorporated common variables across the occupational stress and WLB domains into a single model based on CATS.