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Record W4406439553 · doi:10.3390/children12010099

The Relationship Between Self-Control and Non-Suicidal Self-Injury in Adolescent Psychiatric Outpatients: Exploring the Role of Self-Control

2025· article· en· W4406439553 on OpenAlexaboutno aff
Zhenhua Chen, Jie Xu, Ronghua Zhang, Yuxuan Wang, Ziwei Shang

Bibliographic record

VenueChildren · 2025
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSelf-controlPsychologyClinical psychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Background: Non-suicidal self-injury (NSSI) is a significant public health concern that threatens the physical and mental health of adolescents. Given its high prevalence among adolescents, understanding the characteristics and contributing factors of NSSI is crucial. This study aimed to characterize NSSI and examine the relationship between self-control and NSSI among adolescent psychiatric outpatients. Method: This study was conducted in a psychiatric department of a hospital in Hubei Province, China, involving 206 adolescent psychiatric outpatients (135 females, 12–18 years old). Assessments included the Ottawa Self-Injury Inventory (OSI), the Self-Control Scale (SCS), and a self-designed sociodemographic questionnaire. Result: In this sample, 77.18% reported a history of NSSI. The prevalence of NSSI was significantly higher in females than in males (χ2 = 19.059, p < 0.01). The NSSI group had significantly lower self-control scores compared to the non-NSSI group (F = 27.458, p < 0.01). In the NSSI group (n = 156), self-control was negatively associated with NSSI frequency and fully mediated by NSSI function. Conclusions: These findings highlight the complete mediating role of NSSI function between self-control and NSSI frequency, offering insights for future prevention and intervention efforts.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.274
Teacher spread0.257 · 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 teacher head, 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

Citations1
Published2025
Admission routes1
Has abstractyes

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