Content validity and reliability of the Exploring EXPRESSions of Autism through Body Language (EXPRESS) tool
Bibliographic record
Abstract
Abstract Children with autism spectrum disorder (ASD) participate in less physical activity than the recommended physical activity guidelines. This may be attributable, in part, to community program instructors’ limited knowledge of ASD, specifically, their awareness of the nonverbal expression differences and consequent challenges with understanding these children’s experiences and reactions during program activities. We developed the Exploring EXPRESSions of Autism through Body Language (EXPRESS) observational rating tool to increase awareness of body language communication of children with ASD, and through its use, hopefully enhance the relationship between instructors and children with ASD within community physical activity programs. The purpose of this study was to assess two key psychometric aspects of the 12-item EXPRESS-Code. Three parents of children with ASD participated in interviews to evaluate content validity related to item interpretation (positive/negative body language cue categories). Inter-rater reliability was assessed by having two raters use the EXPRESS-Code to score videos of 26 children with ASD (6–12 years) performing an advanced gross motor assessment. The EXPRESS-Code met the target for content validity with 88.5% agreement on item categorization, although parents recommended renaming the body language categories as ‘engaged’ and ‘not engaged’. Intra- and inter-rater reliability estimates were excellent for the ‘engaged’/ ‘not engaged’ cue categories (ICCs 0.95–0.97). Next steps for the EXPRESS-Code include assessment of the impact of use on: 1) the relationship of a child with ASD and their instructor, 2) instructors’ confidence working with children with ASD, and 3) engagement and enjoyment of the child with ASD within a physical activity program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.039 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".