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Record W2084553056 · doi:10.1080/10926771.2011.566035

Functional Somatic Syndromes and Childhood Physical Abuse in Women: Data From a Representative Community-Based Sample

2011· article· en· W2084553056 on OpenAlexaffabout
Esme Fuller‐Thomson, Joanne Sulman, Sarah Brennenstuhl, Moeza Merchant

Bibliographic record

VenueJournal of Aggression Maltreatment & Trauma · 2011
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsMount Sinai HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsConfoundingFibromyalgiaMedicineIrritable bowel syndromeSocioeconomic statusChronic fatigue syndromePhysical abusePsychiatryChildhood abuseStressorMental healthClinical psychologyChild abusePoison controlInjury preventionEnvironmental healthInternal medicinePopulation

Abstract

fetched live from OpenAlex

This study investigated whether childhood physical abuse was associated with functional somatic syndromes (FSS) in women while controlling for age, race, and four clusters of potentially confounding factors: (a) Other childhood adversities, (b) adult health behaviors, (c) socioeconomic status and stressors, and (d) mental health. A regional subsample of the 2005 Canadian Community Health Survey of 7,342 women was used. Women reported whether they had been diagnosed with chronic fatigue syndrome (CFS), fibromyalgia (Fm), irritable bowel syndrome (IBS), or multiple chemical sensitivities (MCS). Fully 749 reported having been physically abused by someone close to them during their youth. When controlling for potentially confounding factors, childhood physical abuse was significantly associated with CFS (OR = 2.11; 95% CI = 1.22, 3.65), Fm (OR = 1.65; 95% CI = 1.08, 2.52), and MCS (OR = 2.82; 95% = CI 1.90, 4.17). Clinicians using reattribution and stepped care approaches in the management of FSS should assess for a history of abuse.

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)0.002
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 score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.099
GPT teacher head0.327
Teacher spread0.228 · 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

Citations14
Published2011
Admission routes2
Has abstractyes

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