A review of participation instruments based on the International Classification of Functioning, Disability and Health
Bibliographic record
Abstract
PURPOSE: To identify and review instruments which assess participation as defined by the International Classification of Functioning, Disability and Health (ICF). METHODS: A systematic search of the literature was conducted. Data related to the content, administration, scoring, reliability, validity and responsiveness was abstracted. RESULTS: Eleven instruments met the inclusion criteria. Seven instruments include questions with content from Chapters 4 to 9 in the ICF activities and participation component. Four instruments exclude Chapter 5 (self-care). Most of the instruments assess subjective aspects of participation. Evidence on reliability was available for 10 instruments and the majority met the criteria for group level comparisons for internal consistency and reproducibility in the health conditions assessed. In terms of validity, dimensionality was assessed in eight instruments, with six using modern measurement methods. Participation instruments have been compared with various generic and/or disease-specific instruments, but they have not been compared with each other. Evidence on responsiveness was only available for four instruments. CONCLUSIONS: There has been considerable interest in developing instruments to measure participation. To date, the World Health Organisation Disability Assessment Schedule II has undergone the most psychometric testing. Future research must continue to assess these instruments in persons with various health conditions to advance the conceptualisation and measurement of participation.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.017 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".