Prevalence of Adverse Childhood Experiences in Child Population Samples
Bibliographic record
Abstract
Importance: Exposure to adverse childhood experiences (ACEs) before the age of 18 years is a major contributor to the global burden of disease and disability. Objective: To meta-analyze data from samples with children 18 years or younger to estimate the average prevalence of ACEs, identify characteristics and contexts associated with higher or lower ACE exposure, and explore methodological factors that might influence these prevalence estimates. Design, Setting, and Participants: Studies that were published between January 1, 1998 and February 19, 2024, were sourced from MEDLINE, PsycINFO, CINHAL, and Embase. Inclusion criteria required studies to report the prevalence of 0, 1, 2, 3, or 4 or more ACEs using an 8- or 10-item ACEs questionnaire (plus or minus 2 items), include population samples of children 18 years or younger, and be published in English. Data from 65 studies, representing 490 423 children from 18 countries, were extracted and synthesized using a multicategory prevalence meta-analysis. These data were analyzed from February 20, 2024, through May 17, 2024. Main Outcomes and Measures: ACEs. Results: The mean age of children across studies was 11.9 (SD, 4.3) years, the age range across samples was 0 to 18 years, and 50.5% were female. The estimated mean prevalences were 42.3% for 0 ACEs (95% CI, 25.3%-52.7%), 22.0% for 1 ACE (95% CI, 9.9%-32.7%), 12.7% for 2 ACEs (95% CI, 3.8%-22.3%), 8.1% for 3 ACEs (95% CI, 1.4%-16.8%), and 14.8% for 4 or more ACEs (95% CI, 5.1%-24.8%). The prevalence of 4 or more ACEs was higher among adolescents vs children (prevalence ratio, 1.16; 95% CI, 1.04-1.30), children in residential care (1.26; 95% CI, 1.10-1.43), with a history of juvenile offending (95% CI, 1.29; 1.24-1.34), and in Indigenous peoples (1.63; 95% CI, 1.28-2.08), as well as in studies where file review was the primary assessment method (1.29; 95% CI, 1.23-1.34). The prevalence of 0 ACEs was lower in questionnaire-based studies where children vs parents were informants (0.85; 95% CI, 0.80-0.90). Conclusions: In this study, ACEs were prevalent among children with notable disparities across participant demographic characteristics and contexts. As principal antecedent threats to child and adolescent well-being that can affect later life prospects, ACEs represent a pressing global social issue. Effective early identification and prevention strategies, including targeted codesigned community interventions, can reduce the prevalence of ACEs and mitigate their severe effects, thereby minimizing the harmful health consequences of childhood adversity in future generations.
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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 | 0.037 | 0.074 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.018 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".