The Curative Power of Play: The Voices of Therapists around the World
Bibliographic record
Abstract
It is important for all therapists to be culturally sensitive to children and their eco-systems as well as to be aware of the current trends and the changing application of play as a healing agent. The focus of this study is on the development of a current description of play by therapists from a global perspective through a thematic analysis of focus groups resulting in an explanation of how play contributes to healing and the practice of therapy. In this study, the naturalistic method of qualitative research (Bowers, 2009; Lincoln & Guba, 1985) was applied to the study of play around the world, resulting in a new description of “play”. The analyses of focus group meetings in Morocco, Singapore, Hong Kong, Canada and Europe resulted in the emergence of 8 themes: productivity through play, contribution to development, facilitation of the relationship through play, honouring diversity, collaboration between children and caregivers, stimulation through technology-based play, relaxation provided by play, and the devaluation of play. These themes, which are presented through the “voices of the participants”, together with the literature review, serve to enrich the changing description of play. With participants from all continents, a current global perspective highlights the changes that play, both as a concept and as a healing agent, has undergone and will continue to do so. New information emerged suggesting that technology has become a worldwide focus for children but has a paradoxical effect on their relationships.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.021 | 0.036 |
| Scholarly communication | 0.030 | 0.017 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".