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Record W4404291677 · doi:10.2147/ndt.s476992

Correlation Between Family Dysfunction and Nonsuicidal Self-Injury in a Sample of Chinese Adolescents: The Mediating Effect of Alexithymia and circRNA_103636

2024· article· en· W4404291677 on OpenAlexaboutno aff
Shaoli Shi, Guangyao Li, Xiaoli Zhu, Lingming Kong

Bibliographic record

VenueNeuropsychiatric Disease and Treatment · 2024
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaMedicineClinical psychologyCorrelationSample (material)Psychiatry

Abstract

fetched live from OpenAlex

Background: Adolescent group may be prone to a variety of behavioral disorders, one of which is nonsuicidal self-injury (NSSI), NSSI intervention is limited for its unknown mechanism, so this study aimed to explore the factors associated with and pathological mechanism underlying NSSI from the perspective of family dysfunction, alexithymia, circRNA_103636 in a sample of Chinese adolescents. Methods: A total of 200 MDD adolescents with NSSI and 200 healthy controls were enrolled via a convenient sampling method in clinical settings. The Family APGAR Index (APGAR), Toronto Alexithymia Scale (TAS-20), and Adolescent Nonsuicidal Self-injury Assessment Questionnaire (ANSSIAQ) were used for mental assessment of the study group and control group participants. Real-time quantitative reverse transcription PCR (qRT-PCR) was utilized to detect circRNA_103636 expression in peripheral blood mononuclear cells (PBMCs). Results: There were significant between-group differences of 134 patients (67%) in the study group and 42 patients in the control group (21%) with moderate or severe family dysfunction (P<0.01). The APGAR score was lower, and the difficulty identifying feeling (DIF), difficulty describing feeling (DDF) and externally oriented thinking (EOT) scores of the TAS-20 and ΔCt value of circRNA_103636 were greater in the study group than in the control group. NSSI behavior and NSSI function were negatively correlated with the APGAR score and positively correlated with DIF, DDF, and the EOT of TAS-20 and the ΔCt value of circRNA_103636. Multiple regression analysis confirmed that EOT, circRNA_103636 expression, and APGAR were predictors of ANSSIAQ, which could explain 40.5% of the variance. Similarly, the alexithymia and circRNA_103636 expression mediated the correlation between family dysfunction and NSSI in the study group, and these mediating effects accounted for 27.25% and 23.33%, respectively, of the total effect. Taken together, family dysfunction, alexithymia, and circRNA_103636 expression have predictive effects on NSSI and alexithymia, circRNA_103636 expressions are mediators between family dysfunction and NSSI in Chinese adolescent. Conclusion: Here, we established a new model for NSSI in which exposure to family dysfunction could induce pathological process by modulating personality traits and epigenetic regulators.

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)0.000
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.276
Teacher spread0.266 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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