Old age is associated with increased risk of several debilitating diseases. Physical activity and exercise have been identified as behaviours to preserve physical and mental health in older adults. The aim of the study was to test the Integrated Behavioral Change model in exercise and physical activity behaviors on two samples of older adults. A first sample comprised older adults engaged in exercise class (N=192; meanage= 71.13 years; SD = 6.58), the second comprised older adults doing physical activity (N-100; mean age= 75.78 years; SD= 7.53). The key analyses relied on Variance-Based Structural Modeling (VB-SEM-also known as Partial Least Squares analysis), which were performed by means of the WARP PLS v.6.0 statistical software. These analyses estimated the Integrated Behavioral Change model linking perceived autonomy support, autonomous motivation, attitudes, subjective norms, perceived behavioral control, intention and planning in predicting exercise and physical activity, across two months. The tested models exhibited a good fit with the observed data derived from the model focusing on exercise, as well as with those derived from the model focusing on physical activity. Results showed, also, some effects and relations specific to each behavioral context. Results may form a starting point for future experimental and intervention research.

Active lifestyles in older adults: An integrated predictive model of physical activity and exercise

Girelli L.;
2017

Abstract

Old age is associated with increased risk of several debilitating diseases. Physical activity and exercise have been identified as behaviours to preserve physical and mental health in older adults. The aim of the study was to test the Integrated Behavioral Change model in exercise and physical activity behaviors on two samples of older adults. A first sample comprised older adults engaged in exercise class (N=192; meanage= 71.13 years; SD = 6.58), the second comprised older adults doing physical activity (N-100; mean age= 75.78 years; SD= 7.53). The key analyses relied on Variance-Based Structural Modeling (VB-SEM-also known as Partial Least Squares analysis), which were performed by means of the WARP PLS v.6.0 statistical software. These analyses estimated the Integrated Behavioral Change model linking perceived autonomy support, autonomous motivation, attitudes, subjective norms, perceived behavioral control, intention and planning in predicting exercise and physical activity, across two months. The tested models exhibited a good fit with the observed data derived from the model focusing on exercise, as well as with those derived from the model focusing on physical activity. Results showed, also, some effects and relations specific to each behavioral context. Results may form a starting point for future experimental and intervention research.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4741622
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