GAIT SPEED PREDICTS ENGAGEMENT IN PROBLEM SOLVING THERAPY IN OLDER ADULTS WITH DEPRESSION

Autor: Mary Amanda Dew, Meryl A. Butters, Ariel G. Gildengers, Charles F. Reynolds, Jordan F. Karp, Stewart J. Anderson, Steve Albert, Sarah T. Stahl
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Popis: To determine the acceptability of clinical interventions for depression prevention, identifying clinical characteristics associated with its engagement is needed. The purpose of this study is to describe baseline correlates of engagement in Problem Solving Therapy (PST) in adults 60 and older who reported subthreshold depression and high disability burden. PST involved 6–8 sessions in which participants learn skills to solve self-selected problems that are contributing to stress and reduced quality of life. During PST, interventionists completed 3 rating scales that asked about patients’ level of participation in problem solving activities, understanding of the process, and session homework effort in order to measure patients’ engagement with PST. Using multivariate regression, we tested associations among demographics (age, sex, race, education), mental health (depression), physical health (medical illness, gait speed), and cognitive function as correlates of engagement in the PST intervention of our depression prevention trial (n=50). Faster gait speed was significantly associated with more effort and motivation during intervention sessions and greater understanding of PST concepts. Faster gait speed was also significantly associated with more effort in completing homework material, as rated by interventionists. These findings suggest that healthier older adults may be more likely to engage in PST. These findings raise questions about whether therapists should consider gait speed when deciding to offer therapy like PST. Discussion will focus on the role of reporting intervention engagement in the clinical trial literature and whether an indicator of intervention engagement should serve a moderator or a mediator in trial outcome analyses.
Databáze: OpenAIRE