THE IMPACT OF WORKLOAD ON PSYCHOLOGICAL WELL-BEING: THE MODERATING ROLE OF COPING STRATEGIES
Keywords:
Workload, Psychological Well-being, Coping Strategies, Job Demands-Resources Model, Stress Management, Burnout, Employee Mental Health, Workplace Interventions, Mindfulness, Structural Equation ModelingAbstract
Excessive workload has been reported to be one of the main occupational stressors which have negative psychological implications for the employees. This study examined the association between workload and psychological well-being with coping strategies as moderating variables of both. This research work is based on Job Demands-Resources (JD-R) and the Transactional Model of Stress and Coping. A quantitative research design was used where structured survey was also used to collect the data from 500 employees (250 male and 250 female) working in different industries in Pakistan i.e. education, healthcare and corporate. All the scales used in the study were validated including the NASA Task Load Index (Hart & Staveland, 1988) to measure workload, Ryff Psychological Well-being Scale (Ryff, 1989) to determine mental health and the Brief COPE Inventory (Carver, 1997) that was used to measure coping strategies. The moderating factors of coping strategies of workload and well-being were assessed by using Structural Equation Modeling (SEM). The results show that there is high correlation of exceeding workload with stress burnout and decreased psychological well-being. But workers that had participated in problem-centered coping that included control on time, prioritization of work had lower stresses. Mindfulness-based intervention and emotion-focused coping also proved to be a buffering influence on the distress caused by workload. The implications of the study are that organizational interventions, like optimization of workloads, training employees to manage stress, and flexibility at the workplace, helps improve the well-being of employees. To enhance employee performance, further studies must focus on the longitudinal outcomes, as well as the integration of an AI-related workload control system.
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