Date of Conferral







Sandra Caramela-Miller


Identifying depressive symptoms in community-dwelling elders has been problematic, due to a lack of resources and training for health clinicians. Previous researchers have indicated that older adults who engage in physical activities can prevent, or mitigate depression, but no model has included this variable in conjunction with factors such as lifestyle or sociodemographic characteristics. In this study, a predictive design was used with a regression analysis. The purpose of this quantitative study was to investigate the relationship between depressive symptoms and the different factors identified in the literature as significant contributors to its prevalence among older community-dwelling adults. Erikson's theory of psychosocial development, Beck's cognitive model of depression, and the learned helplessness model were used as the theoretical foundations to determine whether lifestyle activities, perceived social support, sociodemographic variables, and comorbidities can predict depressive symptoms. The sample consisted of 156 older adults who were 60 years of age and older and living in Northern Louisiana. Pearson correlation analysis and multiple regression analyses were used to investigate whether (a) daily lifestyle activities, (b) community setting (rural or urban), (c) gender, (d) perceived social support, (e) marital status, and (f) comorbidities can predict depressive symptoms. The 2 primary predictors of depression among older adults were low activity levels and low perceived social support. Positive social implications include improving counselors' and mental health practitioners' knowledge of the ways to lessen the depressive symptoms experienced by the elderly population.