The influence of disclosure of an autism diagnosis on peer engagement and interactions for a child with autism in summer camps: a case study
Bibliographic record
Abstract
PURPOSE: Little research has evaluated how disclosure of an autism diagnosis influences peer engagement and understanding of children with autism in community recreation programs. This study describes outcomes of disclosing an autism diagnosis for a child with autism participating in mainstream, community summer camps. METHODS: This case study includes a 9-year-old boy diagnosed with autism who participated in two camps, one in which he disclosed and one in which he did not disclose. Quantitative data on peer engagement states and reciprocal interactions were coded through structured behavioral observation of video recorded on the first, second, and last day of each program. Qualitative interviews about perceived outcomes of disclosure were completed with the child with autism, camp leaders, and peers in the disclosure camp. RESULTS: Peer engagement and reciprocal interactions improved following the disclosure protocol and continued to improve on the final day of the camp, which was not observed in the non-disclosure camp. A key qualitative theme revealed that changed behavioral attribution was the main contributor to improved inclusion following disclosure. CONCLUSIONS: This study provides preliminary data to support that disclosure may be a simple intervention to improve peer engagement and understanding of children with autism in community programs.IMPLICATIONS FOR REHABILITATIONChildren with Autism Spectrum Disorder are at high risk of experiencing social exclusion, especially in community programs.A disclosure protocol (disclosure + explanation for behaviors) could be a simple intervention to facilitate peer acceptance and inclusion of children with autism, however this intervention has not been evaluated in a real life context.This study provides preliminary evidence to support the use of a simple disclosure protocol for families who want to disclose, within short-term community programs.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".