Latent profile analysis of adolescents’ active health behaviors and the predictive factors

This study aimed to explore the latent profiles of adolescents’ active health behaviors and analyze the predictive factors of different latent profiles of active health behaviors. In December 2024, a survey was conducted among 1,093 middle school students from two rural schools in Anhui Province, China, using convenience sampling. The Adolescent Active Health Behavior Scale (AAHES), Family Functioning Scale (FF), and modified eHealth Literacy Scale (m-eHEALS) were adopted. Latent Profile Analysis (LPA) was used to identify the latent profiles of active health behaviors, and multivariable logistic regression analysis was applied to explore the relevant factors of active health behaviors. The active health behaviors of adolescents could be divided into three latent profiles: Negative Coping Type (27.5%), Unstable Type (46.1%), and Positive Development Type (26.3%). The predictive factors of adolescents’ active health behaviors included family functioning, digital health literacy, class cadre status, father’s educational level, exercise habits, dietary habits, electronic product usage, frequency of electronic product use, and frequently focused online information types. It is recommended that families and educators develop and implement targeted interventions based on the relevant factors to enhance adolescents’ active health behaviors.