Objectives: This study investigates mental health (MH) through the dual-factor model, emphasizing both well-being and ill-being. Our objectives were to (1) identify MH profiles based on this model; (2) track these profiles over time; and (3) explore socio-demographic and physical health factors associated with these profiles.
Methods: We employed Latent Transition Analysis on data from 5,561 individuals aged 39-92, using two waves from the Survey of Health, Ageing, and Retirement in Europe. Well-being was assessed via life satisfaction and quality of life, while ill-being was measured through depression and loneliness. The predictors were socio-demographic and physical health variables.
Results: Four distinct MH profiles emerged, each with unique levels of well-being and ill-being. Stability was more common in adaptive profiles. Physical health was key in predicting transition.
Conclusions: Identifying MH profiles in old age enhances our understanding of how MH adapts with aging. This approach reveals the complexity of MH beyond traditional ill-being, underscoring the importance of well-being.
Clinical implications: • The majority of older adults maintain good MH, suggesting a need for a paradigm shift toward enhancing well-being rather than solely treating ill-being.• Effective MH interventions should integrate both well-being and ill-being assessments to offer understanding and support.
Keywords: Aging populations; long-term mental health; mental health profiles.