Abstract
PurposeAdolescent behavior is closely linked to personality, a key predictor of physical activity. Due to inconsistent findings on how personality dimensions influence physical activity, focusing on combinations of personality traits is more valuable for theoretical and practical guidance. This study aims to examine potential categories of adolescent personality and their relationship with physical activity. MethodsUsing data from the 2014–2015 China Education Panel Survey (CEPS), 9212 adolescents reported their “Big Five” personality and physical activity levels after excluding samples with missing core values. Latent profile analysis with Mplus 8.3 determined the optimal model by comparing model fits to categorize personality types. Bolck-Croon-Hagenaars (BHC) analysis was used to compared physical activity across personality profiles based on the resulting class differences and its significance. ResultsLatent profile analysis identified five personality trait types among adolescents based on fit indices such as AIC, BIC, aBIC, and Entropy: Low-control conservative group (5.0 %), Balanced development group (45.1 %), Optimistic action group (40.4 %), Independent avoidant group (4.5 %), and Introverted vulnerable group 5.0 %). Significant differences in physical activity were found among these profiles (p < 0.001), with individuals in the Optimistic action group tending to be more physically active and those in the Independent avoidance group being less physically active. ConclusionAdolescent personality can be classified into five categories, and different combinations of personality traits can predict physical activity. The findings help identify adolescents who lack physical activity based on their personality profiles, allowing for the design of targeted psychological interventions to promote exercise motivation and foster healthy exercise habits. However, the study has limitations include a narrow age range and a single evaluation method. Future research could incorporate diverse evaluation methods and long-term tracking.
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