The Effect of Group Play Therapy on Social-Emotional Skills in Pre-School Children
Bibliographic record
Abstract
BACKGROUND: Childhood is important and critical period in human life. The foundation of ego is shaped in childhood. Play therapy is one of the successful strategies to help children with inner conflicts problems. This method of psychotherapy is base on the normal learning processes of children, provides solutions to relieve feelings of stress, and expands self-expression. Group play therapy can enhance the self-awareness, self- regulation, social communication, empathy and adoptability in children. METHODS: Present study investigated the effects of play therapy on relational and emotional skills of pre-school children. For this purpose, the total numbers of 372 pre-school children were randomly selected, and divided into two equal groups (case and control). In next step, the BUSSE-SR methodology was used for evaluation and comparison of self-awareness, self-regulation, social interaction, empathy, adoptability, and control groups. Pre-test were performed for both groups and case group was involved in-group play therapy. According to the results of post-test, correlation of variables between case-control groups was examined by multivariate analysis of covariance. RESULTS: Frequency of boys and girls in our sample were 51.3 and 48.7 percent, respectively. The mean age of children was 5.1±0.6 year. According to the results of present study, play therapy significantly enhanced the social-emotional skills (P< 0.001). Our findings are consistent with the results of previous studies in other nations with different environmental and cultural properties. In conclusion, it seems that play therapy can be used in pre-school centers to help children learn problem-solving skills and communicate with others.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".