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Record W3136584482 · doi:10.1177/08862605211001466

Child Sexual Abuse, Self-esteem, and Delinquent Behaviors During Adolescence: The Moderating Role of Gender

2021· article· en· W3136584482 on OpenAlexafffundabout
Amélie Gauthier-Duchesne, Martine Hébert, Martin Blais

Bibliographic record

VenueJournal of Interpersonal Violence · 2021
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité du Québec à Montréal
FundersCanadian Institutes of Health Research
KeywordsJuvenile delinquencySelf-esteemPsychologyMediationDevelopmental psychologyPoison controlIntervention (counseling)Injury preventionSexual abuseClinical psychologySuicide preventionHuman factors and ergonomicsMedicinePsychiatryMedical emergency

Abstract

fetched live from OpenAlex

To reflect the complex phenomena of child sexual abuse (CSA), studies should examine possible gender specificities and explore potentially explanatory mechanisms. The current study aimed to test the moderating effect of gender in the mediated relationship between CSA, self-esteem, and delinquency during adolescence. A moderated mediation model was tested among a representative sample of 8,194 high school students (57.8% girls and 42.2% boys) age 14 to 18 in the province of Quebec in Canada. Results showed that self-esteem has an indirect effect on the relationship between CSA and delinquency. Gender (being a boy) was associated with a higher level of self-esteem and an increased risk of delinquent behaviors. Among victims of CSA, boys reported lower levels of self-esteem than girls, which was associated with an increased risk of displaying delinquent behaviors. Self-esteem may be an important target of intervention for sexually abused youth, especially for boys. Focusing on promoting positive self-esteem may also reduce the risk for male adolescents struggling with the deleterious consequences of delinquency.

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)0.003
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 score0.137
Threshold uncertainty score0.272

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.276
Teacher spread0.262 · 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

Citations32
Published2021
Admission routes3
Has abstractyes

Explore more

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