Patterns of health-risk behaviors among Chinese adolescents during the COVID-19 pandemic: a latent class analysis DOI Creative Commons
Mingxiu Liu,

Xiaolei Tang,

Qingyun Xia

и другие.

BMC Public Health, Год журнала: 2025, Номер 25(1)

Опубликована: Март 25, 2025

Abstract Background Adolescent health-risk behaviors are prevalent and tend to co-occur. This study aimed identify patterns of among Chinese adolescents during the COVID-19 pandemic explore effects individual social factors on patterns. Methods cross-sectional investigated 1607 from four high schools in 2021 through stratified cluster random sampling. Latent class analysis was conducted logistic regression used examine risk protective latent membership. Results Four classes were identified: “Low risk” (81.6%), “Problematic Internet use” (7.8%), “Alcohol (8.5%), “High (2.1%). Relative risk”, with higher levels sensation seeking, deviant peer affiliation, childhood abuse more likely be assigned class, while those degrees parental monitoring school connectedness less class. Those seeking lower scores compared risk”. Students report abuse, but than Conclusions identified multiple students found that multi-level affected adolescent behaviors. These findings provide clues for designing effective interventions reduce adolescents.

Язык: Английский

Psychiatric Disorders and Adverse Life Events as Suicidality Predictors in Disadvantaged Youth from a Leading Institution of Mental Health: A Machine Learning Approach DOI Creative Commons
María Elena Márquez-Caraveo, Blanca Estela Barcelata Eguiarte, Hortensia Moreno-Macías

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Янв. 28, 2025

Abstract Suicide continues to be a major public health concern among youth globally, particularly in low- and middle-income countries. However, predictive studies focusing on marginalized populations remain limited. This study aimed analyze the contribution of psychiatric disorders adverse life events suicidality within clinical sample economically disadvantaged Mexican youth. A total 127 inpatient adolescents, aged 10 17 years, completed MINI-KID interview assess Life Events Questionnaire for Adolescents. Machine learning techniques included classification tree, random forest, XGBoost logistic regression. The mean area under ROC curve XG-Boost, regression models was .796, .820, .737, .776, respectively. analysis identified affective social, family, events, losses, victimization, as critical factors suicidality. Addressing adolescent entail evaluating disorders, with particular focus low-income families receiving mental care, especially context developing

Язык: Английский

Процитировано

0
Patterns of health-risk behaviors among Chinese adolescents during the COVID-19 pandemic: a latent class analysis DOI Creative Commons
Mingxiu Liu,

Xiaolei Tang,

Qingyun Xia

и другие.

BMC Public Health, Год журнала: 2025, Номер 25(1)

Опубликована: Март 25, 2025

Abstract Background Adolescent health-risk behaviors are prevalent and tend to co-occur. This study aimed identify patterns of among Chinese adolescents during the COVID-19 pandemic explore effects individual social factors on patterns. Methods cross-sectional investigated 1607 from four high schools in 2021 through stratified cluster random sampling. Latent class analysis was conducted logistic regression used examine risk protective latent membership. Results Four classes were identified: “Low risk” (81.6%), “Problematic Internet use” (7.8%), “Alcohol (8.5%), “High (2.1%). Relative risk”, with higher levels sensation seeking, deviant peer affiliation, childhood abuse more likely be assigned class, while those degrees parental monitoring school connectedness less class. Those seeking lower scores compared risk”. Students report abuse, but than Conclusions identified multiple students found that multi-level affected adolescent behaviors. These findings provide clues for designing effective interventions reduce adolescents.

Язык: Английский

Процитировано

0