Predictive factors for the development of depression in children and adolescents: a clinical study
BackgroundThe prevalence of depression among adolescents has been gradually increasing with the COVID-19 pandemic, and the purpose of this study was to develop and validate logistic regression models to predict the likelihood of depression among 6-17 year olds.MethodsWe screened participants from th...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2024-10-01
|
| Series: | Frontiers in Psychiatry |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1460801/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832589609109815296 |
|---|---|
| author | Hong Zhang Peilin Yu Xiaoming Liu Xiaoming Liu Ke Wang Ke Wang Ke Wang Ke Wang |
| author_facet | Hong Zhang Peilin Yu Xiaoming Liu Xiaoming Liu Ke Wang Ke Wang Ke Wang Ke Wang |
| author_sort | Hong Zhang |
| collection | DOAJ |
| description | BackgroundThe prevalence of depression among adolescents has been gradually increasing with the COVID-19 pandemic, and the purpose of this study was to develop and validate logistic regression models to predict the likelihood of depression among 6-17 year olds.MethodsWe screened participants from the National Center for Health Statistics (NCHS) in 2022. Independent risk factors were identified via univariate logistic regression analyses and least absolute shrinkage and selection operator (LASSO) for feature screening. Area under the curve (AUC) and decision curve analysis (DCA) were used to compare the predictive performance and clinical utility of these models. In addition, calibration curves were used to assess calibration.ResultsMultivariate logistic regression analyses revealed that risk factors for depression included girls, higher age, treated/judged based on race/ethnicity, ever lived with anyone mentally ill, experienced as a victim of/witnessed violence, and ever had autism, ever had attention-deficit disorder (ADD), etc. Afterwards, the results are visualized using a nomogram. The AUC of the training set is 0.731 and the AUC of the test set is 0.740. Also, the DCA and calibration curves demonstrate excellent performance.ConclusionValidated nomogram can accurately predict the risk of depression in children and adolescents, providing clues for clinical practitioners to develop targeted interventions and support. |
| format | Article |
| id | doaj-art-166bbef11340421d9f57c27d1679e208 |
| institution | Kabale University |
| issn | 1664-0640 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj-art-166bbef11340421d9f57c27d1679e2082025-01-24T11:05:18ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402024-10-011510.3389/fpsyt.2024.14608011460801Predictive factors for the development of depression in children and adolescents: a clinical studyHong Zhang0Peilin Yu1Xiaoming Liu2Xiaoming Liu3Ke Wang4Ke Wang5Ke Wang6Ke Wang7The Second Clinical Medical School, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaDepartment of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaThe Second Clinical Medical School, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaXuzhou Children’s Hospital Affiliated to Xuzhou Medical University, Xuzhou, Jiangsu, ChinaDepartment of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaCenter for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaJiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, ChinaResearch Center for Psychological Crisis Prevention and Intervention of college in Jiangsu Province, Xuzhou, Jiangsu, ChinaBackgroundThe prevalence of depression among adolescents has been gradually increasing with the COVID-19 pandemic, and the purpose of this study was to develop and validate logistic regression models to predict the likelihood of depression among 6-17 year olds.MethodsWe screened participants from the National Center for Health Statistics (NCHS) in 2022. Independent risk factors were identified via univariate logistic regression analyses and least absolute shrinkage and selection operator (LASSO) for feature screening. Area under the curve (AUC) and decision curve analysis (DCA) were used to compare the predictive performance and clinical utility of these models. In addition, calibration curves were used to assess calibration.ResultsMultivariate logistic regression analyses revealed that risk factors for depression included girls, higher age, treated/judged based on race/ethnicity, ever lived with anyone mentally ill, experienced as a victim of/witnessed violence, and ever had autism, ever had attention-deficit disorder (ADD), etc. Afterwards, the results are visualized using a nomogram. The AUC of the training set is 0.731 and the AUC of the test set is 0.740. Also, the DCA and calibration curves demonstrate excellent performance.ConclusionValidated nomogram can accurately predict the risk of depression in children and adolescents, providing clues for clinical practitioners to develop targeted interventions and support.https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1460801/fulllogistic regressionNCHSadolescentsdepressionnomogramprediction |
| spellingShingle | Hong Zhang Peilin Yu Xiaoming Liu Xiaoming Liu Ke Wang Ke Wang Ke Wang Ke Wang Predictive factors for the development of depression in children and adolescents: a clinical study Frontiers in Psychiatry logistic regression NCHS adolescents depression nomogram prediction |
| title | Predictive factors for the development of depression in children and adolescents: a clinical study |
| title_full | Predictive factors for the development of depression in children and adolescents: a clinical study |
| title_fullStr | Predictive factors for the development of depression in children and adolescents: a clinical study |
| title_full_unstemmed | Predictive factors for the development of depression in children and adolescents: a clinical study |
| title_short | Predictive factors for the development of depression in children and adolescents: a clinical study |
| title_sort | predictive factors for the development of depression in children and adolescents a clinical study |
| topic | logistic regression NCHS adolescents depression nomogram prediction |
| url | https://www.frontiersin.org/articles/10.3389/fpsyt.2024.1460801/full |
| work_keys_str_mv | AT hongzhang predictivefactorsforthedevelopmentofdepressioninchildrenandadolescentsaclinicalstudy AT peilinyu predictivefactorsforthedevelopmentofdepressioninchildrenandadolescentsaclinicalstudy AT xiaomingliu predictivefactorsforthedevelopmentofdepressioninchildrenandadolescentsaclinicalstudy AT xiaomingliu predictivefactorsforthedevelopmentofdepressioninchildrenandadolescentsaclinicalstudy AT kewang predictivefactorsforthedevelopmentofdepressioninchildrenandadolescentsaclinicalstudy AT kewang predictivefactorsforthedevelopmentofdepressioninchildrenandadolescentsaclinicalstudy AT kewang predictivefactorsforthedevelopmentofdepressioninchildrenandadolescentsaclinicalstudy AT kewang predictivefactorsforthedevelopmentofdepressioninchildrenandadolescentsaclinicalstudy |