A Meta-Analysis of the Published Research on the Effects of Child Sexual Abuse
Bibliographic record
Abstract
A meta-analysis of the published research on the effects of child sexual abuse (CSA) was undertaken for 6 outcomes: posttraumatic stress disorder (PTSD), depression, suicide, sexual promiscuity, victim-perpetrator cycle, and poor academic performance. Thirty-seven studies published between 1981 and 1995 involving 25,367 people were included. Many of the studies were published in 1994 (24; 65%), and most were done in the United States (22; 59%). All six dependent variables were coded, and effect sizes (d) were computed for each outcome. Average unweighted and weighted ds for each of the respective outcome variables were .50 and .40 for PTSD, .63 and .44 for depression, .64 and .44 for suicide, .59 and .29 for sexual promiscuity, .41 and .16 for victim-perpetrator cycle, and .24 and .19 for academic performance. A file drawer analysis indicated that 277 studies with null ds would be required to negate the present findings. The analyses provide clear evidence confirming the link between CSA and subsequent negative short- and long-term effects on development. There were no statistically significant differences on ds when various potentially mediating variables such as gender, socioeconomic status, type of abuse, age when abused, relationship to perpetrator, and number of abuse incidents were assessed. The results of the present meta-analysis support the multifaceted model of traumatization rather than a specific sexual abuse syndrome of CSA.
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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 | 0.027 | 0.065 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.050 |
| Bibliometrics | 0.018 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".