Protocol for the development and validation of a Core Set for exercise-based rehabilitation of adults with multiple long-term conditions (multimorbidity) based on the World Health Organization’s International Classification of Functioning, Disability, and Health (ICF) framework
Bibliographic record
Abstract
Background: Core outcome sets for people with multiple long-term conditions (multimorbidity) intervention studies offer an opportunity to compare data across studies and countries. However, a key research gap remains: the development of the World Health Organization (WHO) International Classification of Functioning, Disability and Health (ICF) Core Set for multimorbidity rehabilitation. ICF Core Sets are a selection of essential categories from the full ICF classification that are considered most relevant for describing the functioning of a person with a specific health condition or in a specific healthcare context. This study aims to develop and validate an ICF Core Set for exercise-based multimorbidity rehabilitation. Unlike system- or disease-specific rehabilitation, multimorbidity rehabilitation entails using a modified structure that accommodates all conditions that an individual with multimorbidity has. Methods: The three-phase, multi-method process created by the WHO and ICF Research Branch will be followed. The process will involve conducting four preparatory studies (phase 1), including (i) a systematic literature review (to examine researcher perspectives), (ii) a qualitative study (to examine patient perspectives), (iii) an expert survey (to examine health professional perspectives), and (iv) an empirical study (to examine clinical perspectives). This will be followed by an international consensus conference (phase 2) where lists of ICF categories resulting from phase 1 studies will be consolidated into a first version of an ICF Core Set for multimorbidity rehabilitation, which will be validated using an international comparative data analysis (phase 3). Conclusion: An ICF Core Set created for multimorbidity rehabilitation will (1) benefit patients with multimorbidity who are often excluded from clinical trials of single-disease rehabilitation programs, (2) ensure precise and comprehensive assessment and documentation of functioning and disability relevant to this patient population, (3) help rehabilitation providers and their patients and/or caregivers when setting rehabilitation goals and planning rehabilitative interventions to achieve those goals, (4) help researchers in the synthesis of evidence for multimorbidity rehabilitation and facilitate the comparability of data across studies and countries, and (5) provide the scientific basis from which assessment tools can be derived for use in clinical and research settings and health care administration. Trial Registration: COMET database (https://www.comet-initiative.org/Studies/Details/3266).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".