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Record W3183346814 · doi:10.3389/fpsyg.2021.646680

Post-traumatic Stress Disorder in Sexually Abused Children: Secure Attachment as a Protective Factor

2021· article· en· W3183346814 on OpenAlexaff
Karin Ensink, Peter Fonagy, Lina Normandin, Abby Rozenberg, Christina Marquez, Natacha Godbout, Jessica L. Borelli

Bibliographic record

VenueFrontiers in Psychology · 2021
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPsychologyAttachment theorySexual abuseInsecure attachmentClinical psychologyProtective factorChild Behavior ChecklistChild abuseChildhood abusePosttraumatic stressChecklistPsychological resilienceAttachment measuresChild sexual abusePsychiatryPoison controlInjury preventionDevelopmental psychologyMedicineMedical emergencyPsychotherapist

Abstract

fetched live from OpenAlex

The aim of the present study was to examine the hypothesis that attachment and childhood sexual abuse (CSA) interacted such that school aged CSA survivors with insecure attachment to parents would be at an elevated risk of developing post-traumatic stress disorder (PTSD) and trauma symptoms. Participants (n= 111, ages 7–12) comprised two groups, child CSA survivors (n= 43) and a matched comparison group of children (n= 68) recruited from the community. Children completed the Child Attachment Interview (CAI) as well as the Trauma Symptom Checklist for Children (TSCC). There was a significant interaction between sexual abuse history and attachment security, such that sexually abused children with insecure attachment representations had significantly more PTSD and trauma symptoms than sexually abused children with secure attachment to parents. The findings show that using a dual lens of attachment and CSA can facilitate the identification of children most at risk and has important implications for understanding risk and resilience processes.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.013
GPT teacher head0.317
Teacher spread0.304 · 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

Citations21
Published2021
Admission routes1
Has abstractyes

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