Parenting Interventions to Prevent and Reduce Physical Punishment: A Scoping Review
Bibliographic record
Abstract
Physical punishment is the most common form of violence against children worldwide and is associated with an increased risk of long-term adverse outcomes. Interventions targeting parents/caregivers are frequently implemented to prevent and reduce the use of physical punishment. This scoping review aimed to map the existing literature on evidence-informed parenting interventions targeting physical punishment. A scoping review following the World Health Organization (WHO) Review Guide, the Joanna Briggs Institute (JBI) 2020 Guide for scoping reviews, was conducted to address the objective of this review. An academic health sciences librarian systematically searched electronic databases (EBSCO, MEDLINE, EMBASE, SCOPUS) for peer-reviewed journal articles. Two reviewers independently screened titles and abstracts, followed by a full-text review according to inclusion and exclusion criteria following the Participants, Concept, and Context framework. Eighty-one studies were included for full-text eligibility. The results suggest that most interventions examined were conducted in North America, targeted mothers and fathers, and were delivered in person. The results from this scoping review describe the state of evidence-informed parenting interventions to prevent and reduce physical punishment. This review found opportunities for future research to implement effective parenting interventions on a larger societal scale and use mixed methods approaches to evaluate parenting interventions.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".