{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T17:23:13Z","timestamp":1793380993591,"version":"4.5.0"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T00:00:00Z","timestamp":1761177600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study investigates how combinations of factors lead to high physical activity levels among Chinese female university students.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Grounded in Social Cognitive Theory (SCT), we developed an \u201cIndividual-Behavior-Environment\u201d triadic reciprocity framework. Using fuzzy-set Qualitative Comparative Analysis (fsQCA), we performed a configurational analysis of physical activity behaviors among 115 Chinese female university students. The study assessed six antecedent conditions across three dimensions: capability cognition (exercise self-efficacy, perceived value of exercise), motivational drive (exercise motivation, subjective exercise experience), and environmental interaction (friend support, social anxiety).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>None of the six individual conditions were necessary for high physical activity behavior. Instead, high activity levels emerged from synergistic interactions among multiple conditions. We identified eight distinct equifinal configurations leading to high physical activity, with an overall solution consistency of 0.888 and coverage of 0.722, indicating strong model robustness. These configurations formed four typical driving modes: Immersive Enjoyment, Autonomous Drive, Dual Core Reinforcement, and Efficacy Anxiety Compensation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This study confirms the characteristics of \u201cmultiple conjunctural causation\u201d and \u201ccausal asymmetry\u201d in forming physical activity behaviors among Chinese female university students. It extends SCT by revealing complex compensatory and substitutive mechanisms among factors, moving beyond traditional linear models. The findings offer a novel configurational perspective for understanding this population\u2019s physical activity behaviors and provide crucial evidence for designing targeted health behavior interventions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2025.1695542","type":"journal-article","created":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T05:37:58Z","timestamp":1761197878000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Influencing factors of physical exercise behavior among Chinese female university students: a configurational analysis based on 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