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Record W2119912784 · doi:10.1176/appi.ajp.158.1.73

Childhood Abuse and Psychiatric Disorders Among Single and Married Mothers

2001· article· en· W2119912784 on OpenAlexaffabout
Ellen L. Lipman, Harriet L. MacMillan, Michael H. Boyle

Bibliographic record

VenueAmerican Journal of Psychiatry · 2001
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsMcMaster UniversityHamilton Health SciencesMcMaster Children's Hospital
Fundersnot available
KeywordsPsychiatrySexual abuseMental healthAnxietySubstance abuseChild abuseMarital statusPopulationMedicinePhysical abuseClinical psychologyPsychological abusePsychologyPoison controlSuicide prevention

Abstract

fetched live from OpenAlex

OBJECTIVE: This study examined the prevalence of, and association between, childhood abuse and psychiatric disorders in single and married mothers. METHOD: Single and married mothers who participated in the Ontario Health Survey, a province-wide study derived from a probability sample of the general population of Ontario aged 15 years and older (N=1,471), were included. Sociodemographic and mental health characteristics were collected by means of interviewer-administered questionnaires. A self-administered questionnaire was used to collect information on childhood physical and sexual abuse. RESULTS: Compared with married mothers, single mothers reported substantially lower incomes as well as higher rates of childhood abuse and all psychiatric morbidities examined (current and lifetime affective or anxiety disorders and substance use disorders). Childhood abuse had a consistent and significant association with adult mental health, even when other risk variables were controlled. No interaction among childhood abuse and marital status and outcome was found. CONCLUSIONS: Single mothers reported more childhood abuse and experienced higher levels of poverty and psychiatric disorders than married mothers. Childhood abuse was associated with more psychiatric problems in both single and married mothers. Research, clinical, and policy implications of these findings are discussed.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.851

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 head0.005
GPT teacher head0.237
Teacher spread0.232 · 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

Citations54
Published2001
Admission routes2
Has abstractyes

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