Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model.

ABSTRACT:

Background

In March 2022, a new outbreak of COVID-19 emerged in Quanzhou, leading to the implementation of strict lockdown management measures in colleges. While existing research has indicated that the pandemic has had a significant impact on sleep quality, the specific effects of containment measures on college students' sleep patterns remain understudied.

Objective

This study aimed to understand the sleep quality of college students in Fujian Province during the epidemic and determine sensitive variables, in order to develop an efficient prediction model for the early screening of sleep problems in college students.

Methods

A cross-sectional survey was conducted April 5-16, 2022 to survey college students in Quanzhou. A total of 4959 college students in Quanzhou we

SUBMITTER: Chen L 

PROVIDER: S-EPMC11846199 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature