Promoting playfulness through a play-based occupational therapy intervention: A study protocol
Bibliographic record
Abstract
Background: Play is integral to optimal childhood development. Occupational therapists often use play to improve play skills. However, when it comes to learners with autism spectrum disorder (ASD) in South Africa, there is limited research regarding play-based interventions that address the underlying motivators of play, namely, social play and playfulness. Objectives: In this study, the authors present a rationale for the development of a protocol for a study aiming to measure the impact of the Playbox Africa Intervention. This is a play-based occupational therapy intervention with the aim of enhancing the playfulness, social play and occupational performance of South African children with ASD. Method: The study will utilise a within-subject, repeated measures design and will be implemented over 16 weeks with 8-10 learners (aged 3-8 years) with ASD attending a developmental-centre environment in Johannesburg, South Africa. The playfulness and social play of the learners will be assessed using the Test of Playfulness (ToP). The modified Canadian Occupational Performance Measure (M-COPM) will be used to measure occupational performance factors. Results: Given that this protocol outlines an intervention that has not yet been implemented, there are no results to report on. Conclusion: The development of this protocol could encourage the adaption of existing play-based protocols, for children with ASD, perhaps within different settings or varying support needs. Contribution: Additionally, it could lay the foundation for future clinical trials and culturally relevant play-based interventions to be developed in the South African special needs context.
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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 | 0.029 | 0.017 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.042 | 0.010 |
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".