Evidence map›Paper›PMID 41908865›Full record

ArticleNature and science of sleep2026

Current Status and Influencing Factors of Insomnia Severity in Adolescents: A Cross-Sectional Study.

Hai-Shan Huang, Zhuo-Yan Zhang, Rong Xv

Abstract read
In one paragraph

Article in Nature and science of sleep, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Hai-Shan HuangNursing Department, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.ORCID 0000-0002-7094-9786
Zhuo-Yan ZhangSchool of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.ORCID 0009-0004-6720-9375
Rong XvNursing Department, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: To investigate the status and influencing factors of insomnia severity among Chinese urban adolescents and to develop a predictive model for early identification. Design: A multi-center cross-sectional study. Methods: A survey was conducted with 4288 secondary school students from Wuhan, China. A nested case-control sampling method was used within the cross-sectional survey to enhance statistical power for predictive modeling. Data were collected using standardized scales including the Insomnia Severity Index (ISI), the Three-dimensional Psychological Pain Scale (TDPPS), and the Patient Health Questionnaire-9 (PHQ-9). Statistical analyses included univariate analysis, correlation analysis, and multivariable binary logistic regression to identify independent predictors and construct a prediction model. Results: Psychological pain was the strongest risk factor (OR=1.444), followed by depression (OR=1.292) and parental absence >3 months (OR=1.290). Increasing age (OR=0.361) and higher paternal education (OR=0.644) were protective. The final optimized prediction model demonstrated excellent goodness-of-fit (Nagelkerke Conclusion: This study identifies psychological pain as the strongest predictor of adolescent insomnia, exceeding the influence of depression and anxiety. We developed a streamlined 9-variable prediction model with high accuracy (88.6%), offering a practical tool for efficient, large-scale insomnia screening in school settings. This enables early identification and paves the way for targeted, preventive interventions. Implications for Practice: Clinical assessments for adolescent insomnia should incorporate the evaluation of psychological pain. The model enables school nurses and mental health professionals to efficiently identify at-risk adolescents, promoting precision-based preventive care. Impact: This study addresses the multifactorial nature of adolescent insomnia and the lack of practical screening tools. Findings will benefit school health systems and mental health practitioners. Reporting Method: This study was reported in accordance with the STROBE guidelines for cross-sectional studies. Patient or Public Contribution: Patients or the public were not involved in the design, conduct, analysis, interpretation, or preparation of the manuscript for this study.

Indexed as

adolescentbinary logistic regressioninsomniaprotective factorsrisk factors

Identifiers

PMID41908865
PMCPMC13025696

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.