Childhood Abuse and Psychiatric Disorders Among Single and Married Mothers
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".