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Development and validation of a prediction nomogram for academic burnout among Chinese adolescents: a cross-sectional study.
Ye, Sheng; Wang, Rui; Pan, Huiqing; Zhao, Feiyang; Li, Weijia; Xing, Jingjing; Wu, Jinting.
  • Ye S; Emergency Department, The Second Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Wang R; Institute of Physical Education, Anhui Polytechnic University, Wuhu, Anhui, China.
  • Pan H; Emergency Department, The Second Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Zhao F; College of Clinical Medicine, Wannan Medical College, Wuhu, Anhui, China.
  • Li W; College of Clinical Medicine, Wannan Medical College, Wuhu, Anhui, China.
  • Xing J; Emergency Department, The Second Affiliated Hospital of Wannan Medical College, Wuhu, Anhui, China.
  • Wu J; Department of Psychology, Wannan Medical College, Wuhu, Anhui, China wjt99561@163.com.
BMJ Open ; 13(5): e068370, 2023 05 02.
Article in English | MEDLINE | ID: covidwho-2320664
ABSTRACT

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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Full text: Available Collection: International databases Database: MEDLINE Main subject: Students / Nomograms / Burnout, Psychological / COVID-19 / East Asian People Type of study: Observational study / Prognostic study / Qualitative research / Randomized controlled trials Limits: Adolescent / Humans Language: English Journal: BMJ Open Year: 2023 Document Type: Article Affiliation country: Bmjopen-2022-068370

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Students / Nomograms / Burnout, Psychological / COVID-19 / East Asian People Type of study: Observational study / Prognostic study / Qualitative research / Randomized controlled trials Limits: Adolescent / Humans Language: English Journal: BMJ Open Year: 2023 Document Type: Article Affiliation country: Bmjopen-2022-068370