A Mixed-Method Study on Strategies in Everyday Personal Goals among Community-Dwelling Older Adults.

Introduction: Although it is well known that preference for selection, optimization, and compensation (SOC) strategies is associated with indicators of successful aging and well-being, very little is known about what predicts the use of SOC as goal management strategies in the daily lives of older adults. The present study investigates predictors of self-reported use of SOC strategies in community-dwelling adults. We expected selection and especially compensation to be higher in individuals with worse subjective health and cognitive performance. On the contrary, given that optimization is an anticipatory strategy to increase goal-relevant means in the absence of resource losses, we did not expect optimization to be related to either health or cognition. Methods: We performed hierarchical regression to predict use of SOC strategies to achieve everyday personal goals (assessed qualitatively via semi-structured interviews exploring participants’ personal goals) from subjective health and objective cognitive performance, controlling for age, apathy, and depression. Results: Poorer self-rated health and worse cognitive performance positively predicted compensation as a goal management strategy (R2 = 20%), whereas self-rated health just failed to significantly predict selection rates. None of the variables of interest predicted optimization. Discussion/Conclusion: Whereas previous research suggests associations between reduced resources and decreased absolute frequency of compensation use, the present study found that poorer cognitive status and perceived health are both linked to increased reliance on compensation in order to preserve well-being. In line with their anticipatory nature, the use of optimization strategies was independent from health and cognitive resources in our sample. We discuss the absence of conclusive effects regarding selection in this study in light of the distinction between elective and loss-based selection.