Content comparison of occupation‐based instruments in adult rheumatology and musculoskeletal rehabilitation based on the International Classification of Functioning, Disability and Health
Bibliographic record
Abstract
OBJECTIVE: To compare the content of clinical, occupation-based instruments that are used in adult rheumatology and musculoskeletal rehabilitation in occupational therapy based on the International Classification of Functioning, Disability and Health (ICF). METHODS: Clinical instruments of occupational performance and occupation in adult rehabilitation and rheumatology were identified in a literature search. All items of these instruments were linked to the ICF categories according to 10 linking rules. On the basis of the linking, the content of these instruments was compared and the relationship between the capacity and performance component explored. RESULTS: The following 7 instruments were identified: the Canadian Occupational Performance Measure, the Assessment of Motor and Process Skills, the Sequential Occupational Dexterity Assessment, the Jebson Taylor Hand Function Test, the Moberg Picking Up Test, the Button Test, and the Functional Dexterity Test. The items of the 7 instruments were linked to 53 different ICF categories. Five items could not be linked to the ICF. The areas covered by the 7 occupation-based instruments differ importantly: The main focus of all 7 instruments is on the ICF component activities and participation. Body functions are covered by 2 instruments. Two instruments were linked to 1 single ICF category only. CONCLUSION: Clinicians and researchers who need to select an occupation-based instrument must be aware of the areas that are covered by this instrument and the potential areas that are not covered at all.
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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 | 0.022 | 0.096 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".