Spanking and adult mental health impairment: The case for the designation of spanking as an adverse childhood experience
Bibliographic record
Abstract
Adverse Childhood Experiences (ACEs) such as child abuse are related to poor health outcomes. Spanking has indicated a similar association with health outcomes, but to date has not been considered an ACE. Physical and emotional abuse have been shown in previous research to correlate highly and may be similar in nature to spanking. To determine if spanking should be considered an ACE, this study aimed to examine 1): the grouping of spanking with physical and emotional abuse; and 2) if spanking has similar associations with poor adult health problems and accounts for additional model variance. Adult mental health problems included depressive affect, suicide attempts, moderate to heavy drinking, and street drug use. Data were from the CDC-Kaiser ACE study (N=8316, response rate=65%). Spanking loaded on the same factor as the physical and emotional abuse items. Additionally, spanking was associated with increased odds of suicide attempts (Adjusted Odds Ratios (AOR)=1.37; 95% CI=1.02 to1.86), moderate to heavy drinking (AOR)=1.23; 95% CI=1.07 to 1.41), and the use of street drugs (AOR)=1.32; 95% CI=1.4 to 1.52) in adulthood over and above experiencing physical and emotional abuse. This indicates spanking accounts for additional model variance and improves our understanding of these outcomes. Thus, spanking is empirically similar to physical and emotional abuse and including spanking with abuse adds to our understanding of these mental health problems. Spanking should also be considered an ACE and addressed in efforts to prevent violence.
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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 | 0.030 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.010 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".