Predictors of change in satisfaction with body appearance and body function in mid-life and older adults: Active for Life®.

BACKGROUND: Body satisfaction has not been well studied among mid-life and older adults despite age-related changes in body appearance and function. PURPOSE: The objective of this study is to examine predictors of change in body appearance satisfaction and body function satisfaction in an adult sample (n = 1,839; mean age= 69). METHODS: Participants took part in a physical activity behavior change program. Simultaneous regression analyses examined predictors of change in body function satisfaction and body appearance satisfaction. RESULTS: Greater improvements in body function satisfaction were associated with being younger and white, better baseline health ratings, greater reductions in body mass index (BMI) and depressive symptoms, and greater increases in physical activity. Greater improvements in body appearance satisfaction were associated with being white, obtaining a college degree, greater reductions in BMI and depressive symptoms, and greater increases in physical activity. CONCLUSIONS: These findings suggest the importance of physical activity in enhancing body satisfaction in mid-life and older adults. Future research aimed to better understand effective methods for increasing physical activity remains essential.

Measuring physical activity self-regulation strategies in older adults.

BACKGROUND: Theoretically, self-regulatory strategies (e.g., goal setting, self-monitoring) are an important influence of behavior change, but very little research has examined the relationship between self-regulation and physical activity (PA) behavior. Petosa's (1993) 43-item PA self-regulation scale (PASR-43) affords the opportunity for studying this construct in the context of PA; however the PASR-43 has not been tested for structural aspects of validity. Therefore, this study examines the structural validity of the PASR-43 in older adults. METHODS: The structural validity of the PASR-43 was tested in a large sample of older adults from North and South Carolina and Ohio (N = 460) using maximum likelihood estimation and confirmatory factor analysis in AMOS 5.0. RESULTS: The original 6-factor model for the PASR-43 scale did not represent an acceptable fit to the data (chi2 = 4732.25, df = 845, P < .0001, RMSEA = 0.10, NNFI = 0.67, CFI = 0.71). Based on a post hoc specification search, iterative model modifications resulted in a 12-item PA self-regulation scale (PASR-12) that represented an excellent fit to the data (chi2 = 70.75, df = 39, P = .001, RMSEA = 0.04, NNFI = 0.98, CFI = 0.99). CONCLUSIONS: The PASR-12 provides a concise and valid measure of PA self-regulation for use with older adults. Future studies should cross-validate the PASR-12 and examine invariance across time and between age, ethnic, gender, and geographical groups.

Self-regulation and physical activity: the relationship in older adults.

OBJECTIVES: To examine the relationship between self-regulation and physical activity (PA) in older adults. METHODS: A convenience sample (N=284) of older adults (M age=70.4 years) was surveyed. RESULTS: Multivariate analyses controlling for self-efficacy and socio-demographic variables revealed that using self-regulatory strategies more extensively, being male, and having better self-report health were significantly related to greater PA engagement. Supportive of a social cognitive perspective, results were also consistent with mediation, where self-regulation partially mediated the relationship between self-efficacy and PA. CONCLUSIONS: Further examination of these relationships using prospective and experimental designs is recommended. Practical implications of these findings are discussed.

Correlates of self-regulation for physical activity among older adults.

OBJECTIVES: To examine correlates of self-regulation (personal regulation of goal-directed behavior or performance) for physical activity (PA) in older adults. METHODS: A convenience sample (N=296) of older adults was surveyed (M age=70.4 years). RESULTS: Hierarchical regression analyses revealed current PA engagement and sets of sociodemographic, health-related, and theoretical variables as independent correlates of self-regulation (model R2 = 37%, P < 0.0001). In the final model, female gender, older age, social support, self-efficacy, and greater PA were positive, independent correlates. CONCLUSIONS: Self-regulatory strategies are vital to PA promotion across the life span. Therefore, it is important to understand factors associated with self-regulation and use this information for intervention design and implementation.