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Record W4389078479 · doi:10.3390/future1030009

Association of Adverse Childhood Experiences with Non-Suicidal Self-Injury and Suicidality: Baseline Survey of the Chinese Adolescent Health Growth Cohort

2023· article· en· W4389078479 on OpenAlexaff
Shuangshuang Guo, Ting Jiao, Ying Ma, Stephen P. Lewis, Brooke A. Ammerman, Ruoling Chen, Erica Thomas, Yizhen Yu, Jie Tang

Bibliographic record

VenueFuture · 2023
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Guelph
FundersNational Center for Research ResourcesAarhus Universitet
KeywordsSuicidal ideationPsychiatryPsychological abuseClinical psychologyPoison controlAnxietyMedicineChild abusePsychologySuicide preventionMedical emergency

Abstract

fetched live from OpenAlex

Many studies have identified that adverse childhood experiences (ACEs) are associated with non-suicidal self-injury (NSSI) and suicidality. However, most studies have been restricted to a few types of ACEs. This study aims to investigate the association of 13 common types of ACEs with NSSI, suicidal ideation (SI), and suicide attempts (SA), as well as the mediation of depressive and anxiety symptoms therein. A total of 1771 (994 male, 777 female) students aged 11–16 (12.9 ± 0.6) years who participated in the baseline survey of the Chinese Adolescent Health Growth Cohort study were included in the analysis. ACEs, including childhood maltreatment, other common forms of ACEs, and smoking, were measured via the Chinese version of the Child Trauma Questionnaire (CTQ) and a series of valid questionnaires that were derived from previous studies. NSSI was measured using the Chinese version of the Functional Assessment of Self-mutilation. SI and SA were measured using questions derived from the Global School Based Student Health Survey. Depressive symptoms were measured via the Chinese version of the Center for Epidemiologic Studies Depression Scale, and anxiety symptoms were measured via the General Anxiety Disorder-7. Of the included participants, 92.0% reported one or more category of ACEs. Smoking, parent–child separation, emotional abuse, physical abuse, and being bullied were positively associated with NSSI; smoking, parent–child separation, emotional abuse, physical abuse, emotional neglect, and being bullied were positively associated with SI; smoking, emotional abuse, and being bullied were positively associated with SA. The associations of ACEs with NSSI, SI, and SA were each partially or completely mediated through depressive and anxiety symptoms. Children and adolescents who had experiences of smoking, physical abuse, and being bullied during childhood are consistently and independently associated with NSSI and suicidality, and these associations may be largely mediated through depressive and anxiety symptoms. In conclusion, not all the types of ACEs are independently associated with NSSI, and suicidality and other associations may mediate through depressive and anxiety symptoms. Target interventions for adolescents’ NSSI and suicidality should focus on those who have a history of ACEs and depressive and anxiety symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.285
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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