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Record W2589876068 · doi:10.1177/0886260517693001

Childhood Victimization and Physical Health in Women: The Mediating Role of Adult Attachment

2017· article· en· W2589876068 on OpenAlexaff
Lianne Rosen, Marsha Runtz, Erin M. Eadie, Carolyn Mirotchnick

Bibliographic record

VenueJournal of Interpersonal Violence · 2017
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsHospital for Sick ChildrenUniversity of Victoria
Fundersnot available
KeywordsStructural equation modelingAttachment theoryPhysical abusePhysical healthPsychologySexual abuseInsecure attachmentIntervention (counseling)Occupational safety and healthInjury preventionMedicinePoison controlClinical psychologyDevelopmental psychologyMental healthPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

Research has shown that female survivors of childhood abuse (CA) are more likely than nonabused women to experience long-term physical health concerns. Adult attachment may influence this relationship given that attachment insecurity has been linked to poorer physical health and postulated mechanisms of action are similar. This study used structural equation modeling to investigate whether adult attachment insecurity mediates the relationship between four types of CA and self-reported physical health in 538 undergraduate women. CA prevalence rates ranged from 11.7% (sexual abuse) to 34.9% (psychological abuse). In separate structural equation models, direct pathways were significant between CA and adult attachment insecurity, CA and adult physical health, and adult attachment insecurity and adult physical health. Adult attachment insecurity was found to partially mediate health outcomes in CA survivors, S–B χ 2 = 116.60 (58), p < .001; comparative fit index = .95; Tucker–Lewis index = .94; root mean square error of approximation = .05; and confidence interval = [.03, .06]. Physical health is a significant concern for survivors of CA, and these results suggest improving attachment security may represent an important avenue of intervention.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.305
Teacher spread0.297 · 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 teacher head, 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

Citations9
Published2017
Admission routes1
Has abstractyes

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