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Record W2149071031 · doi:10.1177/088626000015010006

Mediators of the Link Between Childhood Sexual Abuse and Adult Depressive Symptoms

2000· article· en· W2149071031 on OpenAlexaff
Valerie E. Whiffen, Janice Thompson, Jennifer Aubé

Bibliographic record

VenueJournal of Interpersonal Violence · 2000
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsSimon Fraser UniversityUniversity of Ottawa
Fundersnot available
KeywordsPsychologyDepression (economics)AssertivenessInterpersonal communicationClinical psychologyPoison controlSuicide preventionSexual abuseHistory of depressionInjury preventionSexual orientationPsychiatryMedicineCognitionPsychotherapistSocial psychologyMedical emergency

Abstract

fetched live from OpenAlex

A history of childhood sexual abuse (CSA) is strongly associated with adult depression. The goal of the present study was to explore potential mediators of the CSA-depression link. The potential mediators were variables known to be associated with depression: interpersonal problems, gender role orientation, sociotropy, and self-silencing. The participants were 109 women and 83 men recruited from the community, approximately one third of whom had a history of CSA. The results indicated that gender role orientation, sociotropy, and self-silencing were not associated with a history of CSA. However, both men and women with a history of CSA reported more inter-personal problems than did individuals without this history. Whereas women reported being distant and controlling, men reported lacking assertiveness and taking too much responsibility in their relationships. These interpersonal variables partially mediated the link between CSA and depressive symptoms. Thus, in part, CSA survivors may be at risk for depression because they experience interpersonal problems.

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)0.006
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.255
Teacher spread0.248 · 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

Citations63
Published2000
Admission routes1
Has abstractyes

Explore more

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