The effects of level 2 Positive Parenting Program (Triple P) on parental use of physical punishment, non-physical forms of punishment, and non-punitive parenting responses
Bibliographic record
Abstract
Child maltreatment is a significant public health issue. Reducing prevalence of coercive parenting is one means to reducing risk of maltreatment and negative developmental outcomes for children. Parental use of physical punishment has been associated with adverse consequences in childhood and adulthood. Parent education programs, such as the Positive Parenting Program (Triple P), that promote alternatives to using physical punishment with children may reduce coercive parenting. In this study, parental use of physical punishment, non-physical forms of punishment, and non-punitive parenting responses were compared before and after parents attended Level 2 Triple P parent education seminars. International Parenting Survey-Canada (IPS-C) data were used to examine Belsky’s (1984) theoretical proposition that parental factors are the strongest predictor of parenting behaviour followed by contextual and child factors. Independent samples t-tests, Wilcoxon Signed Rank Tests, and a series of regression models were used to examine the study’s hypotheses. A total of 27 parents attended the Triple P sessions. Parental use of physical punishment decreased on only one of the four physical punishment items (shaking) post- intervention. Although there were no significant differences in overall use of non-physical forms of punishment and non-punitive parenting strategies pre and post-intervention, there were significant increases in frequency of use of individual scale items pre- to post-intervention. IPS-C sample of 2,340 Canadian parents was used to examine Belsky’s postulate. Results were mixed and provided partial support for the postulate. Child behaviour problems, participation in parent education programs, parent employment status, and parent age predicted coercive parenting. Findings highlight the need to further examine these hypotheses.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".