A study on classification features of depressive symptoms in adolescents

Abstract

Although extensive literature has addressed depression among adolescents, few studies have emphasized the classification features of depressive symptoms in adolescents. To gain insight into the hierarchy and heterogeneity of depression in adolescents based on symptoms, 5086 adolescents completed the Chinese version of the Center for Epidemiological Studies Depression Scale (CES-D). Using Latent Class Analysis (LCA), we identified different subgroups of adolescents based on depressive symptoms. Multivariate logistic regression analysis was implemented to examine the relations between latent classes and demographic covariates. Four latent classes of individuals with depressive symptoms displaying a pattern of hierarchical organization were identified. The four classes were ordered by the degree of severity, ranging from the students reporting the highest number of depressive symptoms to the lowest number: “probable clinical depression”, “subthreshold depression”, “mild depression” and “low depression”, accounting for 8.2%, 19.2%, 41.8% and 30.8% of total sample respectively. Further analyses revealed that compared to the “mild depression” class, the rest of three classes differed significantly across age groups and only child (vs. sibling) status. In conclusion, classifying the groups of adolescents based on features of depressive symptoms is potentially useful for understanding risk factors and developing tailored prevention and intervention programs for this age group.

Keywords:

• Adolescents
• depressive symptoms
• latent class analysis
• Center for Epidemiologic Studies Depression Scale

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Educational College of Hunan Agricultural University Institutional Review Board and with the 1964 Helsinki declaration as well as its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Author contributors

Caili Liu conceived of the study, coordinated data collection, performed statistical analyses, and drafted the manuscript; Yu Ling provided guidance on study design, data collection, statistical analyses, and manuscript revisions; Scott Huebner, Yifang Zeng, Na Zhao, and Zhihua Li participated in the data analysis and interpretation of the results. All authors read and approved the final manuscript.

Additional information

Funding

This research was supported by Hunan Provincial Natural Science Foundation of China [Grant No. 2019JJ40131] awarded to Dr. Yu Ling.