Determinants of Depression Among Retirees Elderly: Application of the Gelberg-Andersen Behavioral Model

Abstract

Background: Depression is currently the main reason for disability globally and the most prevalent mental illness among elderly. As the population continues to age, the number of elderly individuals experiencing depression is expected to rise significantly. This study aimed to identify psychological factors that can predict depression in elderly, using the Gelberg-Andersen behavioral model. Methods: This cross-sectional study was conducted on 538 retired elderly individuals aged 60 to 75 years old in western Iran during 2022. Data was collected through written questionnaires based on interviews with the participants. The collected data was then analyzed using SPSS version 16. Results: Overall, 55.8% of the elderly population experienced varying degrees of depression. Factors such as education level (Beta= -0.085), economic status (Beta= -0.170), recent exposure to a stressful event (Beta= 0.104), self-efficacy (Beta= -0.146), barriers (Beta= 0.086), and help-seeking (Beta= -0.173) significantly influenced the occurrence of depression. The Gelberg-Andersen behavioral model variables explained 36% of the variation in depression levels. Conclusion: There is evidence supporting the use of the Gelberg-Andersen model for designing and implementing interventions to prevent depression in the elderly. When developing prevention programs, it is important to prioritize the disadvantaged elderly population. In order to prevent depression, it can be helpful to focus on strategies that reduce barriers to accessing mental health services, enhance self-efficacy, and encourage mental health help-seeking.

Keywords: Depression, Aging, Mental Health, Help-Seeking, Barriers, Self-Efficacy