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Visualization of Intensity Levels to Reduce the Gap Between Self-Reported and Directly Measured Physical Activity
Published on: March 7, 2019
Predictors of physical activity in persons with mental illness: Testing a social cognitive model
Michelle R Zechner1, Kenneth J Gill1
1Department of Psychiatric Rehabilitation and Counseling Professions, Rutgers, The State University of New Jersey.
Objective:
This study examined whether the social cognitive theory (SCT) model can be used to explain the variance in physical exercise among persons with serious mental illnesses.
Method:
A cross-sectional, correlational design was employed. Participants from community mental health centers and supported housing programs (N = 120) completed 9 measures on exercise, social support, self-efficacy, outcome expectations, barriers, and goal-setting.
Results:
Hierarchical regression tested the relationship between self-report physical activity and SCT determinants while controlling for personal characteristics. The model explained 25% of the variance in exercise. Personal characteristics explained 18% of the variance in physical activity, SCT variables of social support, self-efficacy, outcome expectations, barriers, and goals were entered simultaneously, and they added an r2 change value of .07. Gender (β = -.316, p = .001) and Brief Symptom Inventory Depression subscale (β = -2.08, p < .040) contributed significantly to the prediction of exercise. In a separate stepwise multiple regression, we entered only SCT variables as potential predictors of exercise. Goal-setting was the single significant predictor, F(1, 118) = 13.59, p < .01), r2 = .10.
Conclusions And Implications For Practice:
SCT shows promise as an explanatory model of exercise in persons with mental illnesses. Goal-setting practices, self-efficacy, outcome expectations and social support from friends for exercise should be encouraged by psychiatric rehabilitation practitioners. People with more depressive symptoms and women exercise less. More work is needed on theoretical exploration of predictors of exercise. (PsycINFO Database Record
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