Prevalence of Childhood Sexual Abuse and Timing of Disclosure in a Representative Sample of Adults from Quebec
Bibliographic record
Abstract
OBJECTIVE: Our study sought to explore patterns of disclosure of child sexual abuse (CSA) in a sample of adult men and women. METHOD: A telephone survey conducted with a representative sample of adults (n = 804) from Quebec assessed the prevalence of CSA and disclosure patterns. Analyses were carried out to determine whether disclosure groups differed in terms of psychological distress and symptoms of posttraumatic stress, and a logistic regression was used to examine factors associated with prompt disclosure. RESULTS: Prevalence of CSA was 22.1% for women and 9.7% for men. About 1 survivor out of 5 had never disclosed the abuse, with men more likely not to have told anyone, than women. Only 21.2% of adults reported prompt disclosure (within a month of the first abusive event), while 57.5% delayed disclosure (more than 5 years after the first episode). CSA victims who never disclosed the abuse and those who delayed disclosure were more likely to obtain scores of psychological distress and posttraumatic stress achieving clinical levels, compared with adults without a history of CSA. In the multivariate analysis, experiencing CSA involving a perpetrator outside the immediate family and being female were factors independently associated with prompt disclosure. CONCLUSION: A significant number of adult women and men reported experiencing CSA, and most victims attested to either not disclosing or significantly delaying abuse disclosure.
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 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 | 0.001 |
| 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 | 0.000 |
| 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".