O3‐07‐06: Adapting the tinetti tool for balance and gait for persons with dementia
Bibliographic record
Abstract
A recent review of the literature reveals an absence of standardized measures to assess mobility in persons with advanced dementia. Persons with moderate to severe dementia have significant difficulty adhering to instructions. The aim of the study was to develop a standardized measure of gait and balance for use with persons with dementia. We chose to modify the ‘Tinetti Assessment Tool for Balance and Gait’ (Tinetti, 1986) because many of the items are based on observation. Two items were omitted (covering eyes, push) and one was revised to a more easily observable task (turning 360 degrees to turning 180 degrees). Modification of these items requires analysis of reliability prior to establishing validity. We aim to determine the inter-rater and test-retest reliability of ‘Tinetti Assessment Tool for Balance and Gait- Dementia’ Recruitment—Potential participants were identified by members of their care team and consent sought from substitute decision makers (SDMs). Participants with dementia were included and excluded with delirium or medical instability. Data collection—Inter-rater reliability: Participants were observed and scored simultaneously by two raters familiar with the written instructions (physiotherapy, occupational therapy or nursing staff). Test-retest reliability—The test was re-administered after 10 to 30 minutes. A total of n=20 participants were recruited and included. The mean age of participants was 75, with the majority being female (n=11, 55%). All were diagnosed with dementia or cognitive impairment. Secondary diagnoses include heart disease, diabetes and Parkinson's disease. The mean cognitive assessment (SMMSE) score was 8.5/30 (n=12). Inter-rater reliability of the total score was high (ICC= 0.85) as was test-retest reliability (ICC=0.92). These results are comparable to established reliability of the original Tinetti tool (ICC>0.8) (Kekelmeyer, Kloos, Thomas & Kostyk, 2007). The results indicate that the modified measure has sufficient reliability to commence validity testing. Developing a measure that assesses functional changes in this population is important for determining the impact of mobilization and least restraint programs for people with dementia in long term care. Further study will establish validity of the cut score for predicting falls risk.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".