Predicting sleep quality among college students during COVID-19 lockdown using a LASSO-based neural network model
In Quanzhou, under COVID-19 quarantine management, the sleep quality of college students was affected to a certain extent, and their PSQI scores were higher than the national average in China. The artificial neural network model had the best performance, and it is expected to be used to provide early interventions to prevent sleep disorders.
Authors
- Jiajing Zhuang (ORCID: https://orcid.org/0000-0001-7021-7852)
- Yixiang Zhang (ORCID: https://orcid.org/0000-0003-2499-5770)
- Jimin Fan (ORCID: https://orcid.org/0009-0003-3610-2412)
- Zhimin Huang (ORCID: https://orcid.org/0009-0006-6179-2306)
- Ling Yao (ORCID: https://orcid.org/0000-0003-1086-5641)
- Yifu Zeng (ORCID: https://orcid.org/0000-0003-4239-3693)
- Haibin Lu (ORCID: https://orcid.org/0000-0001-6576-7059)
- Lufeng Chen (ORCID: https://orcid.org/0000-0002-0854-3144)
- Qingquan Chen
- Ailing Song
Institutions
- Fujian Medical University (CN)
- Shanghai Jiao Tong University (CN)
- Ruijin Hospital (CN)
- Guangzhou University (CN)
- Second Affiliated Hospital of Fujian Medical University (CN)
Publication Details
- Journal
- BMC Public Health
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1186/s12889-025-21746-z
- Primary Topic
- COVID-19 and Mental Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Fujian Provincial Health and Family Planning Commission
- Natural Science Foundation of Fujian Province
- Quanzhou City Science and Technology Program