Applicability of a toolkit for geriatric rehabilitation outcomes
Bibliographic record
Abstract
Purpose. To field test the applicability of a multidimensional toolkit for geriatric rehabilitation outcomes which includes nine standardized tools. Applicability is defined as context- and population-specific pragmatic qualities of an assessment tool such as respondent and examiner burden, score distribution and format compatibility.Method. A sample of 48 older adults representing four diagnostic groups, as well as 26 caregivers, were assessed at home in the first month after discharge from intensive rehabilitation (T1) and 2 months later (T2). Pre-determined qualitative and quantitative applicability criteria were coded and compared at T1 and T2, as well as responsiveness.Results. A higher respondent burden was found for three self-report tools, as well as a ceiling effect on social functioning tools. Respondent burden, examiner burden and score distribution remained stable or diminished at T2. Format compatibility deteriorated only for the mobility test due to a higher proportion of non ambulatory participants (17%). Low to moderate associations between the tools corroborated that they were not redundant (rPearson ≤ 0.77). Responsiveness estimates confirmed that mean scores were stable between T1 and T2.Conclusion. Overall, the toolkit was found to be applicable at home after geriatric rehabilitation. Modifications are proposed to further improve its applicability. This study highlighted practical aspects that could alleviate the burden on research participants and facilitate the use of those tools for community follow-up for clinical and research purposes.
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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 | 0.041 | 0.152 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".