Effects of Cognitive-Based Problem-Solving skills On Changing Parenting Styles and Reducing Parental Anger
Bibliographic record
Abstract
Objective: The current study aims to examine the effect of cognitive problem-solving skills training on parents' parenting styles and their anger reduction towards their children. Method: The method of this research is quasi-experimental with a pretest-posttest single-group design without follow-up. The sample group consisted of 69 mothers of children aged 4 to 7 years, selected through convenience sampling. In these workshops, which were held over 9 two-hour sessions across 9 weeks, parents were made aware of effective and ineffective methods of dealing with children's behaviors, and practiced exercises to improve their response style to challenging behaviors of children. To evaluate the effectiveness of the training program, two questionnaires were used: the Parenting Styles questionnaire (Shokoohi Yekta & Parand, 2007) and the Anger Assessment questionnaire (Shokoohi Yekta & Zamani, 2007). The research data were analyzed with ANOVA and t-test methods using SPSS software. Findings: The results showed that participation in the problem-solving workshop had a positive effect on participants' performance regarding their parenting styles. Such that, this program led to an increase in the problem-solving parenting style and a decrease in parents' use of other ineffective parenting styles such as advising without explanation, and punishment and scolding (P<0.05). However, the analysis of the findings did not show a significant difference in terms of reducing mothers' aggression towards their children (P>0.05). Conclusion: Accordingly, it can be inferred that training in problem-solving skills can be used to improve parenting styles and the quality of interpersonal communications within the family.
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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 | 0.000 | 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) | 0.002 | 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".