Harsh Physical Punishment in Childhood and Adult Physical Health
Bibliographic record
Abstract
BACKGROUND: The use of physical punishment is controversial. No studies have comprehensively examined the relationship between physical punishment and several physical health conditions in a nationally representative sample. The current study investigated possible associations between harsh physical punishment (ie, pushing, grabbing, shoving, slapping, and hitting) in the absence of more severe child maltreatment (ie, physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect, and exposure to intimate partner violence) and several physical health conditions. METHODS: Data were from the National Epidemiologic Survey on Alcohol and Related Conditions collected in 2004 and 2005 (n = 34,226 in the current analysis). The survey was conducted with a representative US adult population sample (20 years or older). Eight past year physical health condition categories were assessed. Models were adjusted for sociodemographic variables, family history of dysfunction, and Axis I and II mental disorders. RESULTS: Harsh physical punishment was associated with higher odds of cardiovascular disease (borderline significance), arthritis, and obesity after adjusting for sociodemographic variables, family history of dysfunction, and Axis I and II mental disorders (adjusted odds ratios ranged from 1.20 to 1.30). CONCLUSIONS: Harsh physical punishment in the absence of child maltreatment is associated with some physical health conditions in a general population sample. These findings inform the ongoing debate around the use of physical punishment and provide evidence that harsh physical punishment independent of child maltreatment is associated with a higher likelihood of physical health conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".