Mary A Nies1, Yiyuan Sun. 1. Health Sciences Center, State University of New York at Stony Brook, Stony Brook, NY, 11794, USA. maryannnies@yahoo.com
Abstract
PURPOSE: Increasing evidence has indicated that people might be differentially influenced by intervention programs. The purpose of this secondary analysis was to identify groups of women who responded differently to a walking intervention. Data used in this secondary analysis were collected in a longitudinal study of a counseling intervention to increase walking among 248 initially sedentary women. METHOD: A latent growth-mixture modeling approach was used to assess treatment effects on growth in physical activity and mood over time. Subgroups of participants who were responsive versus those who were nonresponsive to intervention were also identified. Logistic-regression analysis was conducted to confirm group membership and identify predictors associated with the identified subgroups. RESULTS: Two subgroups (responders, nonresponders) were identified separately for physical activity and mood. Using several variables as predictors of group memberships, 92%-95% of the cases were correctly classified. The current study indicated that predictors for group membership were associated with the outcome variables. CONCLUSIONS: These findings indicated that optimal interventions should be tailored to not only the physical, psychosocial, and environmental variables of each woman, but also to outcome variables of interest to the woman. CLINICAL RELEVANCE: Nurses practicing in community and public health settings should determine physical activity interventions that are based on scientific findings and on outcomes that are important for the individual woman.
PURPOSE: Increasing evidence has indicated that people might be differentially influenced by intervention programs. The purpose of this secondary analysis was to identify groups of women who responded differently to a walking intervention. Data used in this secondary analysis were collected in a longitudinal study of a counseling intervention to increase walking among 248 initially sedentary women. METHOD: A latent growth-mixture modeling approach was used to assess treatment effects on growth in physical activity and mood over time. Subgroups of participants who were responsive versus those who were nonresponsive to intervention were also identified. Logistic-regression analysis was conducted to confirm group membership and identify predictors associated with the identified subgroups. RESULTS: Two subgroups (responders, nonresponders) were identified separately for physical activity and mood. Using several variables as predictors of group memberships, 92%-95% of the cases were correctly classified. The current study indicated that predictors for group membership were associated with the outcome variables. CONCLUSIONS: These findings indicated that optimal interventions should be tailored to not only the physical, psychosocial, and environmental variables of each woman, but also to outcome variables of interest to the woman. CLINICAL RELEVANCE: Nurses practicing in community and public health settings should determine physical activity interventions that are based on scientific findings and on outcomes that are important for the individual woman.
Authors: Mary O Whipple; Erica N Schorr; Kristine M C Talley; Ruth Lindquist; Ulf G Bronas; Diane Treat-Jacobson Journal: J Aging Phys Act Date: 2018-06-20 Impact factor: 1.961