ArticleBehavioral sciences (Basel, Switzerland)2026
Network Analysis of Physical Activity, Personality, Goal Orientation and Depressive Subdimensions in College Students: Behavioral-Personality-Motivation Profiles.
Article in Behavioral sciences (Basel, Switzerland), 2026. 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
Depressive symptoms are prevalent among college students. This study examined cross-domain associations among depressive symptom dimensions, physical activity, Big Five personality traits, and goal orientation using network analysis, latent profile analysis (LPA), multi-group network analysis, and multiple linear regression. LPA was conducted using behavioral, personality, and motivational variables only, with depressive symptom indicators excluded from class extraction. Data from 911 Chinese undergraduates were analyzed. The results showed that psychological equivalents, a cognitive-related depressive subdimension, had the highest strength centrality in the overall network, while neuroticism showed prominent positive bridge expected influence between personality traits and depression-related indicators. In the regression models, task orientation, agreeableness, conscientiousness, and openness were negatively associated with depressive symptoms to varying degrees. MVPA and sedentary time were not significantly associated with depressive symptoms in the total-sample model, whereas walking showed a subgroup-specific negative association only in the maladaptive, low-motivation, inactive profile. Three behavioral-personality-motivation profiles were identified, and the maladaptive profile showed relatively higher depressive symptom levels and stronger neuroticism-related associations. These findings provide associative, network- and profile-based evidence for understanding depressive symptoms among college students and may inform future longitudinal and intervention studies targeting behavioral-personality-motivation heterogeneity.
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