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

Background: Depression is currently the leading cause of disability globally and the most prevalent mental illness among the 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 predict depression among the elderly using the Gelberg-Andersen Behavioral Model. Methods: This cross-sectional study was conducted among 538 retired elderly individuals aged 60 to 75 years old in western Iran in 2022. Data were collected through structured questionnaires based on interviews with the participants. The collected data were 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 to care (Beta=0.086), and help-seeking behavior (Beta=-0.173) were significantly influenced the occurrence of depression. Variables within the Gelberg-Andersen Behavioral Model explained 36% of the variation in depression levels. Conclusion: The findings support the applicability of the Gelberg-Andersen model in designing and implementing interventions to prevent depression in the elderly. Preventive programs should prioritize disadvantaged elderly populations. To effectively prevent depression, strategies should focus on reducing barriers to accessing mental health services, enhancing self-efficacy, and promoting mental health help-seeking behaviors.