Virtual Assessment Protocols for Timed-Up-and-Go, 5-Repetition Chair Rise, and 1-Minute Sit-to-Stand Tests in Community-Dwelling Older Adults: Investigating Feasibility, Reliability, and Validity
Bibliographic record
Abstract
OBJECTIVE: To develop and evaluate virtual assessment protocols for the Timed-Up-and-Go usual and fast pace, Chair Rise-5 repetition, and the 1-minute Sit-to-Stand tests and examine their feasibility, reliability, and validity. DESIGN: This was a prospective cohort study, where participants engaged in up to 2 virtual assessments and data were collected prospectively for 1 year. SETTING: Assessments took place in participants' homes in the community. Toolkits were delivered that included the required equipment and internet-enabled tablet. PARTICIPANTS: Participants included a random sample of adults ≥65 years old who could walk 10 m without assistance from another person and communicate in English. MAIN OUTCOME MEASURES: Falls and health care utilization data were collected for 1 year after initial assessments. Descriptive data were used to examine feasibility; intraclass correlation (ICC), and Pearson's/Spearman's correlation and areas under the curve (AUCs) were used to evaluate reliability and validity, respectively. RESULTS: Sixty participants (mean age 76.6±5.6; 55% female) completed visit 1 and 52 completed visit 2. Technology issues were relatively common, yet no safety incidents occurred. All the virtual mobility tests demonstrated excellent test-retest (ICCs=0.86-0.95) and inter-rater (ICC=0.98-0.99) reliability. The tests had weak-to-moderate correlations with measures of physical function (r=-0.14 to -0.43) and physical activity (r=-0.19 to 0.32). Fifty-seven total falls were recorded by 28 participants (46%) over 1 year. The virtual mobility tests did not have adequate accuracy for predicting falls (AUCs=0.53-0.59), specialist (AUCs=0.48-0.60), family doctor (AUCs=0.48-0.59), or rehabilitation professional visits (AUCs=0.65-0.67), or hospitalizations (AUCs=0.56-0.63). CONCLUSION: Results support the feasibility and reliability of virtual administration of the Timed-Up-and-Go usual and fast pace, Chair Rise-5 repitition, and 1-minute Sit-to-Stand tests. Clinicians and researchers can use the included manuals to conduct these tests virtually. Future research should examine the clinical utility of these tests for remote monitoring and mobility assessment.
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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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".