The epidemiological patterns of childhood sexual abuse and bullying in 204 countries and territories during past decades
Bibliographic record
Abstract
Abstract Background This study presents an image of childhood sexual abuse and bullying (CSAB) longitudinal trends in summary exposure rates from 1990 to 2019 in 204 countries and territories. Methods The CSAB summary exposure rates in 1000000 people were extracted from the Institute for Health Metrics and Evaluation and analyzed using latent growth approaches. Results Our results showed, globally, at the beginning of the study, the summary exposure rate was higher in boys and was increased in both genders over time (increasing rate of 16.6 in boys and 17.8 in girls, P < .001). Also, during past decades, the CSAB summary exposure rate for boys and girls had a significant increasing trend in both developed and low developed countries (p < 0.001). The increasing rate in low developed countries was more than in developed ones, in boys and girls. The CSAB rates among boys in Chile, Spain, and Sweden, and girls in Chile, Lithuania, Netherlands had the sharpest decreasing rate among world countries (decreasing rate of 19.5 and 13.9 per 1000000 persons, respectively, p < .001). The longitudinal trend of CSAB rates in other countries has been mostly increasing in boys and girls. Conclusion This study showcases the trend of CSAB rates were heterogeneous among countries and have not decreased during past decades and in most countries. In both developing and developed countries, special attention from relevant policymakers is required, and implementation of national survey, facilitating reporting, and knowledge of the CSAB at a population level are recommended.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".