Author comment: A bibliometric analysis of scientific literature on adverse childhood experiences (2004–2024) — R1/PR6
Bibliographic record
Abstract
Adverse childhood experiences (ACE) significantly impact physical, mental and social well-being, making them a critical area of research. This study analyzed the emerging trends and intellectual structure of ACE research and identified key contributors, including the most productive nations, journals and authors. Using bibliometric tools and VOSviewer software (version 1.6.20), 1,957 articles from the Scopus database (2004 to March 2024) were systematically analyzed. A notable finding was the surge in ACE-related publications during the COVID-19 pandemic, potentially reflecting increased global attention on childhood adversity amid heightened social and economic challenges. The analysis also revealed a striking dearth of studies from the Global South, with the field predominantly shaped by Western nations, like the United States, the United Kingdom, Australia and Canada. Leading journals, such as the Journal of Interpersonal Violence, and prolific authors, like Kevin T. Wolff, played a central role in advancing the field. Co-citation analysis uncovered four thematic clusters: (1) conceptualization and assessment of ACE, (2) health implications, (3) mental health impacts and (4) juvenile delinquency. These clusters, though distinct, showed significant thematic overlaps, reflecting the interconnected nature of ACE research and its intellectual structure. These findings underscore the need for more regionally diverse and interdisciplinary approaches to understanding global childhood adversity.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.174 | 0.312 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 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; both teacher heads agree on what is shown here.
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".