Childhood Abuse and Lifetime Psychopathology in a Community Sample
Bibliographic record
Abstract
OBJECTIVE: The authors assessed lifetime psychopathology in a general population sample and compared the rates of five psychiatric disorder categories between those who reported a childhood history of either physical or sexual abuse and those who did not. METHOD: A modified version of the Composite International Diagnostic Interview and a self-completed questionnaire on child abuse were administered to a probability sample (N=7,016) of Ontario residents 15 to 64 years of age. RESULTS: Those reporting a history of childhood physical abuse had significantly higher lifetime rates of anxiety disorders, alcohol abuse/dependence, and antisocial behavior and were more likely to have one or more disorders than were those without such a history. Women, but not men, with a history of physical abuse had significantly higher lifetime rates of major depression and illicit drug abuse/dependence than did women with no such history. A history of childhood sexual abuse was also associated with higher rates of all disorders considered in women. In men, the prevalence of disorders tended to be higher among those who reported exposure to sexual abuse, but only the associations with alcohol abuse/dependence and the category of one or more disorders reached statistical significance. The relationship between a childhood history of physical abuse and lifetime psychopathology varied significantly by gender for all categories except for anxiety disorders. Although not statistically significant, a similar relationship was seen between childhood history of sexual abuse and lifetime psychopathology. CONCLUSIONS: A history of abuse in childhood increases the likelihood of lifetime psychopathology; this association appears stronger for women than men.
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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".