Evidence map›Paper›PMID 36823044›Full record

ArticleEnvironmental health and preventive medicine2023

How adverse and benevolent childhood experiences influence depression and suicidal ideation in Chinese undergraduates: a latent class analysis.

Jie Tang, Jingjing Wang, Yifei Pei, Shiferaw Blen Dereje, Qian Chen, Na Yan, Yunjiao Luo, Yuhao Wang, Wei Wang

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Article in Environmental health and preventive medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

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12citing papers in PubMed, 2 pooled it
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1 · What the graph read from it

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3 · Its place in the literature

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12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Jie TangSchool of Public Health, Xuzhou Medical University.
Jingjing WangSchool of Public Health, Xuzhou Medical University.
Yifei PeiSchool of Public Health, Xuzhou Medical University.
Shiferaw Blen DerejeSchool of Public Health, Xuzhou Medical University.
Qian ChenSchool of Public Health, Xuzhou Medical University.
Na YanSchool of Public Health, Xuzhou Medical University.
Yunjiao LuoSchool of Public Health, Xuzhou Medical University.
Yuhao WangSchool of Public Health, Xuzhou Medical University.
Wei WangSchool of Public Health, Xuzhou Medical University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere has been minimal research on the role of benevolent childhood experiences (BCEs) and how such events may offer protection from the insidious effects of adverse childhood experiences (ACEs) or later in life.

objectivesThis research aims to learn how BCEs and ACEs interact to affect adolescents' psychological distress.

methodsCross-sectional survey was conducted in three cities (Xuzhou, Nanjing, and Wuhan) in China from March 2021 to May 2021. Latent class analysis (LCA) was used to classify the patterns of ACEs and BCEs. We adopted hierarchical multivariable regression to examine the influences of ACEs and BCEs on depression and suicidal ideation.

resultsTo explore the relationship between childhood experience and suicidal ideation and depression, LCA revealed three patterns of ACEs: (1) emotional abuse (10.57%); (2) high ACEs (0.55%); and (3) low ACEs classes (88.88%). Adolescents with emotional abuse (depression: OR = 3.82, 95%CI = 2.80-5.22, P < 0.001; suicidal ideation: OR = 5.766, 95%CI = 3.97-8.38, P < 0.001) and high ACEs class (suicidal ideation: OR = 5.93, 95%CI = 1.19-29.66, P < 0.05) had an increased risk of psychological distress (reference: low ACEs). LCA revealed four patterns of BCEs: (1) relationship support (14.54%); (2) low BCEs (4.85%); (3) high BCEs (55.34%); and (4) high quality of life classes (25.28%). Adolescents with a high quality of life (depression: OR = 0.09, 95%CI = 0.05-0.16, P < 0.001; suicidal ideation: OR = 0.22, 95%CI = 0.12-0.40, P < 0.001) and high BCEs (depression: OR = 0.05, 95%CI = 0.03-0.09, P < 0.001; suicidal ideation: OR = 0.15, 95%CI = 0.09-0.26, P < 0.001) protected the mental health of adolescents (reference: low BCEs).

conclusionsHigh ACEs and emotional abuse classes were significantly associated with poorer mental health symptoms, including suicidal ideation and depression. In contrast, high BCEs and high quality of life classes were associated with better mental health. These findings point out that it is more necessary to identify and support victims of ACEs, and it is urgent to increase BCEs in early childhood.

Indexed as

DepressionSuicidal IdeationAdolescentAdverse Childhood ExperiencesCross-Sectional StudiesEast Asian PeopleHumansLatent Class AnalysisQuality of LifeAdverse childhood experiencesBenevolent childhood experiencesPsychological distressUndergraduates

Identifiers

PMID36823044
PMCPMC9989774

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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.