A new integrated approach for adolescent health and well-being: the AVATAR project

青少年健康与福祉的全新综合方法:AVATAR 项目

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Abstract

BACKGROUND: Limited number of studies examined the relationship between factors (lifestyle, social, emotional, cognitive) affecting adolescents' health and well-being. The aims of this study were to identify the more important variables of the different components affecting adolescents' health [lifestyle habits (LH); emotional status (ES); social context (SC); and cognitive abilities (CA)], and explore the relationship between the aforementioned components. METHODS: Data were collected between 2017 and 2018 from 756 eligible students, recruited from 5 Italian junior high school, by using KIDSCREEN-52 and cognitive processing using the Stroop Test. School engagement was estimated through questions concerning the scholastic achievement. RESULTS: Of 756 adolescents, 395 were boys with a mean (SD) age of 12.19 (0.81) years. Compared to International T-value of reference group for KIDSCREEN-52, autonomy, bullying, psychological well-being and mood were lower than the reference groups, while self-perception score was higher. For LH, the most important predictor was autonomy (p < .0001). The most important aspects in the SC were the relationship with the parents (p < .0001), and the adolescent's relationships with peers (p < .0001). For ES, mood variables had the greatest contribution (p < .0001). The School performance related to Language & Literature (p < .0001) was the most important predictor in the CA latent variable. LH was positively associated with SC (p < .0001), ES (p < .0001), and CA (p < .0001). SC was positively associated with ES (p < .0001) and with CA (p < .0001). CONCLUSIONS: This study suggests the importance of an integrated approach to characterize adolescents' health and well-being. The approach suggested here may highlight additive synergistic effects of the various components in health and well-being assessment that may not be considered with a late approach and focused only on single factors.

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