OBJECTIVE: This study examined differential trajectories of exercise-related self-efficacy beliefs across a 12-month randomized controlled exercise trial. METHOD: Previously inactive older adults (N = 144; M age = 66.5) were randomly assigned to one of two exercise conditions (walking, flexibility-toning-balance) and completed measures of barriers self-efficacy (BARSE), exercise self-efficacy (EXSE), and self-efficacy for walking (SEW) across a 12-month period. Changes in efficacy were examined according to efficacy type and interindividual differences. Latent growth curve modeling was employed to (a) examine average levels and change in each type of efficacy for the collapsed sample and by intervention condition and (b) explore subpopulations (i.e., latent classes) within the sample that differ in their baseline efficacy and trajectory. RESULTS: Analyses revealed two negative trends in BARSE and EXSE at predicted transition points, in addition to a positive linear trend in SEW. Two subgroups with unique baseline efficacy and trajectory profiles were also identified. CONCLUSION: These results shed new light on the relationship between exercise and self-efficacy in older adults. They also highlight the need for strategies for increasing and maintaining efficacy within interventions, namely targeting participants who start with a disadvantage (lower efficacy) and integrating efficacy-boosting strategies for all participants prior to program end. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
RCT Entities:
OBJECTIVE: This study examined differential trajectories of exercise-related self-efficacy beliefs across a 12-month randomized controlled exercise trial. METHOD: Previously inactive older adults (N = 144; M age = 66.5) were randomly assigned to one of two exercise conditions (walking, flexibility-toning-balance) and completed measures of barriers self-efficacy (BARSE), exercise self-efficacy (EXSE), and self-efficacy for walking (SEW) across a 12-month period. Changes in efficacy were examined according to efficacy type and interindividual differences. Latent growth curve modeling was employed to (a) examine average levels and change in each type of efficacy for the collapsed sample and by intervention condition and (b) explore subpopulations (i.e., latent classes) within the sample that differ in their baseline efficacy and trajectory. RESULTS: Analyses revealed two negative trends in BARSE and EXSE at predicted transition points, in addition to a positive linear trend in SEW. Two subgroups with unique baseline efficacy and trajectory profiles were also identified. CONCLUSION: These results shed new light on the relationship between exercise and self-efficacy in older adults. They also highlight the need for strategies for increasing and maintaining efficacy within interventions, namely targeting participants who start with a disadvantage (lower efficacy) and integrating efficacy-boosting strategies for all participants prior to program end. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
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