Wellness Engagement in Older Adults

Abstract

The purpose of this study is to identify predictors of engagement in wellness activities, including life satisfaction, depression, and social networks, in order to increase wellness offerings. Methods: Participants who were part of this study were older adults at a continuing care retirement community in Tulsa, Oklahoma. A total of 106 females (62.4%) and 64 males (37.6%) participated in the study. The study was conducted through a demographic questionnaire along with four empirically tested questionnaires. The Assessing your Wellness questionnaire was used to observe engagement in wellness activities. Depression was measured using the Geriatric Depression Scale Short Form (GDS-SF) questionnaire, which asked the participants to self-rate how they felt emotionally over the past week. Life satisfaction was measured using the Satisfaction with Life Scale (SWLS), which asked the participants to self-rate their subjective well-being. Social networks were measured using the Lubben Social Network Scale-18 (LSNS-18), which asked participants about the frequency of interaction with other people and what kind of relationships they have with family, neighbors, and friends. Pearson's chi-squared test (X2) was calculated to determine the cumulative probability of wellness engagement and how it relates to the expectations of depression, life satisfaction, and social networks. The Pearson�s chi-squared tests results showed how each variable was associated to wellness. The results indicated that GDS-SF was significantly associated to wellness (p<0.05), SWLS was significantly associated to wellness (p<0.05), and LSNS-18 approached statistical significance in association with wellness (p<0.1). Conclusion: Residents who participated in this study were more likely to engage in activities if they understood how the dimensions of wellness influence one another, and feel as though there was a benefit by engaging in wellness activities to improve depression, life satisfaction, and social networks.