Preventing abusive head trauma resulting from a failure of normal interaction between infants and their caregivers
Bibliographic record
Abstract
Head trauma from abuse, including shaken baby syndrome, is a devastating and potentially lethal form of infant physical abuse first recognized in the early 1970s. What has been less recognized is the role of the early increase in crying in otherwise normal infants in the first few months of life as a trigger for the abuse. In part, this is because infant crying, especially prolonged unsoothable crying, has been interpreted clinically as something wrong with the infant, the infant's caregiver, or the interactions between them. Here, we review an alternative developmental interpretation, namely, that the early increase in crying is a typical behavioral development in normal infants and usually does not reflect anything wrong or abnormal. We also review evidence indicating that this normal crying pattern is the most common trigger for abusive head trauma (AHT). Together, these findings point to a conceptualization of AHT as the consequence of a failure in an otherwise common, iterative, and developmentally normal infant-caregiver interaction. They also imply that there is a window of opportunity for prevention of AHT, and potentially other forms of infant abuse, through a public health primary universal prevention strategy aimed at changing knowledge and behaviors of caregivers and society in general concerning normal development of infants and the significance of early increased infant crying. If effective, there may be important implications for prevention of infant abuse nationally and internationally.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".