<p>Physical activity (PA) is essential for health and well-being, yet college students often struggle to maintain consistent engagement. This study employed the Theory of Planned Behavior (TPB) and latent profile analysis (LPA) to investigate how TPB constructs attitude, subjective norm, perceived behavioral control, and intention combine within individuals to form distinct motivational configurations among Chinese college students, moving beyond variable-centered approaches that assume uniform relationships. We aimed to identify these subgroups, examine gender and age differences in subgroup membership, and compare physical activity levels across subgroups.We recruited 313 Chinese college students (<i>M</i> = 19.56, <i>SD</i> = 1.18) and used LPA to identify subgroups based on TPB constructs. A three-step method with BCH examined how gender and age related to profile membership and how profiles differed in PA.LPA identified four optimal profiles: Disengaged (9.1%), Moderately Driven (31.2%), Autonomously Active (34.2%), and Fully Integrated (25.6%). Gender significantly predicted profile membership, with female students less likely to belong to more active profiles. Age showed no significant effect. The BCH method showed that the Autonomously Active and Fully Integrated profiles had significantly higher PA than the Disengaged and Moderately Driven profiles.These four motivational configurations reveal heterogeneity in how TPB constructs combine within individuals to influence physical activity. The findings support tailoring interventions to specific profiles rather than using a one-size-fits-all approach, offering a refined foundation for both research and practice.</p>

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Motivational profiles for physical activity in Chinese university students based on the theory of planned behavior

  • Ying Zhao,
  • Qinghua Wu,
  • Yueqiang Dai

摘要

Physical activity (PA) is essential for health and well-being, yet college students often struggle to maintain consistent engagement. This study employed the Theory of Planned Behavior (TPB) and latent profile analysis (LPA) to investigate how TPB constructs attitude, subjective norm, perceived behavioral control, and intention combine within individuals to form distinct motivational configurations among Chinese college students, moving beyond variable-centered approaches that assume uniform relationships. We aimed to identify these subgroups, examine gender and age differences in subgroup membership, and compare physical activity levels across subgroups.We recruited 313 Chinese college students (M = 19.56, SD = 1.18) and used LPA to identify subgroups based on TPB constructs. A three-step method with BCH examined how gender and age related to profile membership and how profiles differed in PA.LPA identified four optimal profiles: Disengaged (9.1%), Moderately Driven (31.2%), Autonomously Active (34.2%), and Fully Integrated (25.6%). Gender significantly predicted profile membership, with female students less likely to belong to more active profiles. Age showed no significant effect. The BCH method showed that the Autonomously Active and Fully Integrated profiles had significantly higher PA than the Disengaged and Moderately Driven profiles.These four motivational configurations reveal heterogeneity in how TPB constructs combine within individuals to influence physical activity. The findings support tailoring interventions to specific profiles rather than using a one-size-fits-all approach, offering a refined foundation for both research and practice.