Background: Appearance anxiety and weight self-stigma have become increasingly prominent issues among female university students. However, existing studies have primarily concentrated on direct associations at the variable level, with limited exploration of heterogeneous subgroups from a person-centered perspective. This study aimed to examine the mediating role of body image in the relationship between weight self-stigma and appearance anxiety and to identify potential latent categories of weight self-stigma and body image, thereby providing scientific guidance for the prevention and improvement of appearance anxiety in female university students. Methods: From November 2024 to March 2025, a purposive sampling strategy was employed. A total of 1,368 female university students were recruited from 12 comprehensive universities located in six provinces of central and southern China (Hunan, Guizhou, Yunnan, Guangdong, Jiangxi, and Jiangsu). Participants completed the appearance anxiety scale, the weight self-stigma questionnaire, and the body image scale. Results: (1) Weight self-stigma positively predicted appearance anxiety among female university students, with body image playing a partial mediating role ( β = 0.250, p < 0.001); (2) Three latent patterns of weight self-stigma and body image were identified: low stigma—high body image (23.4%), moderate stigma-moderate body image (27.7%), and high stigma—low body image (48.9%); (3) Compared with the “low stigma—high body image” group, the other two categories significantly and positively predicted appearance anxiety ( p < 0.001). Conclusion: Weight self-stigma and body image among female university students demonstrate notable heterogeneity, and body image serves as a mediator in the relationship between weight self-stigma and appearance anxiety.

Background: This study investigates the impact of generative artificial intelligence health knowledge acquisition (GAI-HKA) on adolescents’ physical activity (PA), with a focus on the mediating role of exercise self-efficacy (ESE) and the moderating role of health information literacy (HIL). Methods: Using stratified cluster random sampling, a total of 2,306 valid questionnaires were collected from 10 secondary schools across five cities in southern China. Data were obtained using the self-developed Generative AI Health Knowledge Acquisition Scale, the Adolescent Exercise Self-Efficacy Scale, the Health Information Literacy Scale, and Liang’s revised Physical Activity Rating Scale. Structural equation modelling with PROCESS v3.5 macro (5,000 bootstraps) was employed to test direct, mediating, and moderating effects. Results: GAI-HKA was significantly and positively associated with adolescents’ PA ( β = 0.376, p < 0.001). ESE partially mediated this relationship (indirect effect = 0.065, 95% CI [0.052, 0.079]). HIL positively moderated the pathway from GAI-HKA to ESE (interaction term β = 0.079, p < 0.001); the effect was more substantial among adolescents with high HIL ( β = 0.367) compared with those with low HIL ( β = 0.209). Conclusion: GAI-HKA directly enhances adolescents’ PA and indirectly promotes exercise behavior through strengthening ESE. Moreover, higher HIL amplifies the positive effect of AI-based health knowledge on ESE. These findings suggest that schools and families should integrate efforts to cultivate adolescents’ information literacy and efficacy beliefs when promoting AI-based health interventions, thereby maximizing the benefits of digital technologies in fostering youth physical activity.