The ‘Work Rehabilitation and Adaptation Profile’ for Adults with Autism, a Validated French-Canadian Observation Grid
Bibliographic record
Abstract
Background There is a critical absence of standardized assessment tools necessary for comprehensively evaluating the skills and competencies of adults with autism to establish their employability profile and support them in the development of their socio-professional skills, in pre-employment transitions services (Pre-ETS). Objective To validate the ‘Work Rehabilitation and Adaptation Profile’ for adults with Autism Spectrum Disorder (WRAP-ASD) by assessing its psychometric properties and confirming its suitability across multiple Pre-ETS. Method A scale development and validation method was applied across day activity center, workshops, work programs and internships (n = 41 trainees with autism, n = 19 vocational rehabilitation professionals). Work functioning was observed with WRAP-ASD for motivation, attendance, peer relationships, communication, cognitive skills, rules/safety, independence, physical demand, tool/machinery handling, productivity/quality. WRAP-ASD is an Excel-based observation grid (≈3-h-over-2-weeks) with 59 items using 4-point scales from 3-almost always to 0-never. Results The WRAP-ASD demonstrated strong construct and convergent validities and high internal consistency. Predictive validity identified key items exclusive for each Pre-ETS. The WRAP-ASD was updated with 49 items, by removing 8 items, merging 4, and revising 4. Conclusion WRAP-ASD is sensitive to the different vocational needs and support requirements for Autism Levels 1–3. This is an added value over the six existing measurement tools.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".