ArticleBMC women's health2025
Determinants physical activity in middle-aged women: application trans theoretical model.
Article in BMC women's health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND AND
aimsPhysical activity is one of the most important indicators of health in the society and plays an important role in the lives of people, especially women. Nevertheless, one of the major challenges in modern society is the inactivity and lack of optimal physical activity of women, which has caused a rising prevalence in chronic diseases. Models and theories help to better understand these behaviors and better planning for behavior change in target groups. This study was conducted with the aim of investigating the predictors of regular physical activity among middle-aged women based on the trans-theoretical model.
designThe present study was conducted cross-sectionally on 250 middle-aged women (age range 45-59) covered by comprehensive health databases.
methodInclusion conditions included willingness to participate, living in the area under study, not having certain diseases and disorders that would cause changes in lifestyle or physical activity. The random sampling method was simple. In this study, questionnaires of transtheoretical model constructs and short international questionnaire of physical activity were used. Data were analyzed using SPSS version 26 and Amos 24 software.
resultsIn path analysis, change methods with path coefficient β = 0.20 are the strongest predictors of physical activity behavior in middle-aged women, and it clearly shows a significant positive relationship with the amount of physical activity (P < 0.05). Also, the stimulus control substructure with a factor loading of β = 0.17 and a confidence interval (CI) of 95% also has a high predictive power of the tendency to physical activity behavior. Chi-square ratio to degrees of freedom (χ²/DF) < 3 and RMSEA = 0.065 indicate a good fit of the model with the data (GFI = 0.91, CFI = 0.98).
conclusionThe path analysis revealed that the proposed model by Prochaska fits well with the research data, indicating that change processes are strong predictors of physical behavior. These findings can serve as a foundation for developing targeted, evidence-based interventions to promote physical activity among middle-aged women.
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