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Development and validation of a prediction nomogram for academic burnout among Chinese adolescents: a cross-sectional study

医学 逻辑回归 倦怠 列线图 横断面研究 接收机工作特性 人口学 多元分析 临床心理学 内科学 病理 社会学
作者
Sheng Ye,Rui Wang,Huiqing Pan,Feiyang Zhao,Weijia Li,Jingjing Xing,Jinting Wu
出处
期刊:BMJ Open [BMJ]
卷期号:13 (5): e068370-e068370 被引量:1
标识
DOI:10.1136/bmjopen-2022-068370
摘要

Objectives This study aimed to screen the potential risk factors for academic burnout among adolescents during the COVID-19 pandemic, develop and validate a predictive tool based on the risk factors for predicting academic burnout. Design This article presents a cross-sectional study. Setting This study surveyed two high schools in Anhui Province, China. Participants A total of 1472 adolescents were enrolled in this study. Outcome measures The questionnaires included demographic characteristic variables, living and learning states and adolescents’ academic burnout scale. Least absolute shrinkage and selection operator and multivariate logistic regression analyses were employed to screen the risk factors for academic burnout and develop a predictive model. The receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to assess the accuracy and discrimination of the nomogram. Results In this study, 21.70% of adolescents reported academic burnout. Multivariable logistic regression analysis showed that single-child family (OR=1.742, 95% CI: 1.243 to 2.441, p=0.001), domestic violence (OR=1.694, 95% CI: 1.159 to 2.476, p=0.007), online entertainment (>8 hours/day, OR=3.058, 95% CI: 1.634 to 5.720, p<0.001), physical activity (<3 hours/week, OR=1.686, 95% CI: 1.032 to 2.754, p=0.037), sleep duration (<6 hours/night, OR=2.342, 95% CI: 1.315 to 4.170, p=0.004) and academic performance (<400 score, OR=2.180, 95% CI: 1.201 to 3.958, p=0.010) were independent significant risk factors associated with academic burnout. The area under the curve of ROC with the nomogram was 0.686 in the training set and 0.706 in the validation set. Furthermore, DCA demonstrated that the nomogram had good clinical utility for both sets. Conclusions The developed nomogram was a useful predictive model for academic burnout among adolescents during the COVID-19 pandemic. It is essential to emphasise the importance of mental health and promote a healthy lifestyle among adolescents during the future pandemic.
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