A study on classification features of depressive symptoms in adolescents. (4th March 2021)
- Record Type:
- Journal Article
- Title:
- A study on classification features of depressive symptoms in adolescents. (4th March 2021)
- Main Title:
- A study on classification features of depressive symptoms in adolescents
- Authors:
- Ling, Yu
Liu, Caili
Scott Huebner, E.
Zeng, Yifang
Zhao, Na
Li, Zhihua - Abstract:
- 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 ageAbstract: 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. … (more)
- Is Part Of:
- Journal of mental health. Volume 30:Number 2(2021)
- Journal:
- Journal of mental health
- Issue:
- Volume 30:Number 2(2021)
- Issue Display:
- Volume 30, Issue 2 (2021)
- Year:
- 2021
- Volume:
- 30
- Issue:
- 2
- Issue Sort Value:
- 2021-0030-0002-0000
- Page Start:
- 208
- Page End:
- 215
- Publication Date:
- 2021-03-04
- Subjects:
- Adolescents -- depressive symptoms -- latent class analysis -- Center for Epidemiologic Studies Depression Scale
Mental health -- Periodicals
Mental health services -- Periodicals
362.2 - Journal URLs:
- http://informahealthcare.com/journal/jmh ↗
http://informahealthcare.com ↗ - DOI:
- 10.1080/09638237.2019.1677865 ↗
- Languages:
- English
- ISSNs:
- 0963-8237
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5017.670000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25334.xml