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

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.

Social Distancing, Health Concerns, and Digitally Empowered Consumption Behavior Under COVID-19: A Study on Livestream Shopping Technology.

During the COVID-19 pandemic, livestream shopping has provided consumers with a way to maintain social distancing while offering an alternative to offline shopping. This study aims to understand the impact of COVID-19 and other public health crises on the behavioral intentions of consumers using livestream shopping technology. A theoretical model was designed that combines the health belief model, trust theory, and the theory of planned behavior. Empirical data were collected from 358 residents in China and then analyzed using structural equation modeling. The results showed that perceived susceptibility, perceived severity, perceived benefits, and perceived obstacles had a significant impact on consumer trust. Consumer trust in turn had a direct impact on behavioral intention and an indirect impact on behavioral intention via attitude. These research results have practical implications for livestream shopping merchants, platform decision-makers, and service designers.