Early warning model for depression and anxiety among adolescent students

An empirical study based on Guilin

Datos Bibliográficos

ID22073096
AutoresQingpo Ma (Guangxi Normal University), Xuemei Xu (0000-0001-6697-7816, Guangxi Normal University), Lin Lü (0000-0003-0742-9072, Guangxi Normal University), Mochen Zhang (autor de correspondencia), X Chen (0000-0002-3373-1737, Shenzhen Third People’s Hospital, autor de correspondencia), Ruizhe Wang (0009-0009-3899-4219, Shenzhen Third People’s Hospital, autor de correspondencia), Qiuhong Liao, Qianwen Liao (0009-0009-2800-5093, Shenzhen Third People’s Hospital), Hao Wang (0000-0003-3392-1562, Shenzhen Third People’s Hospital), Hongwei Wang (0000-0001-7474-8271), Yijun Wang (0000-0001-5815-7172, Guangzhou University), Yingxin Tan (0000-0003-0184-1381, Guangxi Normal University), Yangxizi Tan, Na Li (0000-0002-1103-6864, Guangxi Normal University), Niannian Li
Año2026
Volumen13
Páginas1685203-1685203
Fecha de publicación2026-01-07
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaFrontiers in Public Health (JOURNAL)
Identificadores de la revistaISSN: 2296-2565 • E-ISSN: 2296-2565
EditorialFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1685203
PMID41573789
OpenAlexW7118408518
IdiomaEN
Referencias citadas45

Objective To analyze the occurrence of depression and anxiety in Guilin and verify the early warning model of depression and anxiety in Guilin. Methods Using multi-layer sampling method, 10 middle schools were selected from September 2022 to September 2023, with a total of 1,245 middle and high school students in an anonymous self-filled questionnaire survey. A total of 1,150 valid young students were obtained as the survey object, which was randomly divided into training set (920 cases) and verification set (230 cases). Using hospital anxiety and depression scale (HADS) to evaluate the occurrence of Guilin adolescent students depression anxiety, in the form of a questionnaire to understand and analyze the factors affecting Guilin adolescent students depression anxiety, establish the influence of Guilin adolescent students depression anxiety prediction model of occurrence and model validation and efficiency evaluation. Results In the training set of 920 adolescent students, 164 patients developed depressive anxiety, or 17.83%, and 756 patients did not develop depressive anxiety. In the validation set, among 230 adolescent students, 44 patients developed depressive anxiety, with an incidence of 19.13%, and 186 patients did not develop depressive anxiety. Logistic Regression analysis showed that OR (95%CI) = 3.44 (1.98, 5.97), Chinese version of the Family Adaptation and Cohesion Scale (FACESCV) [OR (95% CI) = 1.67 (1.07, 2.61)], and the Connor-Davidson Resilience Scale (CDRISC) score for adolescent students [OR (95% CI) = 1.83 (1.15, 2.92)]were the factors that affected the occurrence of depression and anxiety in adolescents in Guilin ( p < 0.05). The ROC curve results of the training set showed that the nomogram model predicted the sensitivity of depression and anxiety with 80.25%, specificity of 80.09% and AUC of 0.849. Conclusion High risk of depression and anxiety, academic stress, FACESCV and CDRISC score are the influencing factors affecting the occurrence of depression and anxiety in adolescent students in Guilin

Anxiety · Early warning system · Empirical research · Mental health · Suicide prevention · Warning system · Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes · Child and Adolescent Psychosocial and Emotional Development · Mental Health Research Topics