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Record W2558664841 · doi:10.1080/0092623x.2016.1266539

Anxiety Mediates the Relation Between Childhood Sexual Abuse and Genito-Pelvic Pain in Adolescent Girls

2016· article· en· W2558664841 on OpenAlexaff
Marie Santerre-Baillargeon, Pascale Vézina-Gagnon, Isabelle Daigneault, Tina Landry, Sophie Bergeron

Bibliographic record

VenueJournal of Sex & Marital Therapy · 2016
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPelvic painAnxietySexual abuseClinical psychologyPopulationPsychologyMedicinePsychiatryPoison controlInjury preventionMedical emergencySurgery

Abstract

fetched live from OpenAlex

Previous research has demonstrated associations between child sexual abuse, anxiety, and genito-pelvic pain, but no study to date has examined whether sexual abuse may be associated with genito-pelvic pain through victims' elevated anxiety. The present study aimed to determine whether anxiety mediates the relationship between child sexual abuse and genito-pelvic pain. Using self-report questionnaires, data were gathered from 218 sexually active adolescent girls recruited from seven metropolitan high schools. As expected, results revealed a significant indirect effect of sexual abuse on the development of genito-pelvic pain through trait anxiety. This study thus suggests that anxiety may be one of the mechanisms by which child sexual abuse leads to an increased risk of developing genito-pelvic pain in this population.

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)0.005
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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

Citations27
Published2016
Admission routes1
Has abstractyes

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