Routine screening for adverse childhood experiences (ACEs) still doesn't make sense
Bibliographic record
Abstract
When a serious health or social problem is identified as both prevalent and in need of attention, a common response is to propose that various systems implement routine identification, such as universal screening. However, these well-intentioned responses often fail to consider the key requirements necessary to determine whether benefits outweigh harms. Unfortunately, this continues to be the case for calls to implement routine screening for Adverse Childhood Experiences (ACEs). Persistent evidence gaps for this type of screening include the lack of any randomized controlled trials demonstrating that ACEs screening programs lead to any benefits. Rather than being informed by established screening principles, the calls to proceed with ACEs screening appear to rely on the assumption that simply identifying risk factors can lead to beneficial outcomes that outweigh any risk of harms. This may reflect a gap in understanding that patterns identified at the population level (e.g., that more ACEs are associated with more health and social problems) cannot be directly translated to practices at the level of the individual. This commentary does not question the importance of ACEs; rather it identifies that directing limited resources to screening approaches for which there is no evidence that benefits outweigh harms is problematic. Instead, we advocate for the investment in high-quality trials of prevention interventions to determine where best to direct limited resources to reduce the occurrence of ACEs, and for the prioritization of evidence-based treatment services for those with existing health and social conditions, whether or not they are attributed to ACEs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 teacher head, 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".