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Record W2154889913 · doi:10.3200/bmed.33.4.125-136

Direct and Indirect Links Between Childhood Maltreatment, Posttraumatic Stress Disorder, and Women's Health

2008· article· en· W2154889913 on OpenAlexaff
Ariel J. Lang, Gregory A. Aarons, James Gearity, Charlene Laffaye, Leslie E. Satz, Timothy R. Dresselhaus, Murray B. Stein

Bibliographic record

VenueBehavioral Medicine · 2008
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsChild, Adolescent and Family Mental Health
FundersNational Institute of Mental Health
KeywordsSexual abuseMental healthClinical psychologyPsychologyOccupational safety and healthPoison controlInjury preventionSuicide preventionPsychiatryPosttraumatic stressVictimologyChild abuseMedicineMedical emergency

Abstract

fetched live from OpenAlex

The authors evaluated the relationships among childhood maltreatment, sexual trauma in adulthood, posttraumatic stress disorder (PTSD), and health functioning in women. Female Veterans' Affairs (VA) primary care patients (N = 200) completed self-report measures of childhood maltreatment, adult sexual trauma, PTSD symptoms, and current health functioning. The authors used structural equation modeling to test models of the relationship among these variables. Childhood nonsexual maltreatment and adult sexual assault were positively associated with PTSD. Childhood nonsexual maltreatment (beta = -.20) and PTSD (beta = -.75) were significantly associated with poorer physical and mental health functioning. Adult sexual assault negatively affected health functioning through its association with PTSD. Thus, poor health outcomes associated with childhood maltreatment in women may be conveyed through PTSD. These findings should strengthen efforts directed at identifying and treating PTSD in female victims of childhood maltreatment with the aim of preventing or attenuating poor health outcomes.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.057
GPT teacher head0.344
Teacher spread0.287 · 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

Citations95
Published2008
Admission routes1
Has abstractyes

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