Clinical validation of a frailty management mHealth tool in a cohort of community-dwelling older adults: the Geras Fit-Frailty App
Bibliographic record
Abstract
OBJECTIVES: This study describes the prototype testing and clinical validation of the Fit-Frailty App, a fully guided, interactive mobile health (mHealth) app to assess frailty and sarcopenia. This multi-dimensional tool is freely available on the App Store and considers medical history, physical performance, cognition, nutrition, daily function and psychosocial domains. To guide management, a total frailty score and clinical summary of underlying "risk flags" are provided. Our objectives were to examine usability, feasibility, criterion and construct validity. DESIGN: Cross-sectional SETTING: Outpatient geriatric medicine clinic PARTICIPANTS: Community-dwelling older adults, age 65 years or older METHODS: The primary outcome of the clinical validation study was criterion validity. A research nurse administered the Fit-Frailty App during a routine clinic appointment. Clinicians simultaneously completed a paper-based frailty index (FI) tool with similar items from a comprehensive geriatric assessment (FI-CGA). Total scores for both assessments were computed using the cumulative deficits frailty index scoring method. Intraclass and Pearson correlation coefficients and 95% CIs were calculated to examine criterion validity. Secondary outcomes were construct validity, feasibility (eg, completion rates, safety occurrences, resources) and usability (eg, ratings on ease of use, time to complete the app). RESULTS: In the clinical validation study (n=75, mean age 79.2, SD=7.0, 53% female), the mean total Fit-Frailty App score was 0.33 (SD=0.13) with 73% of our sample considered frail or severely frail. The app presented comparable results to FI-CGA (moderate to good validity; ICC=0.65, 95%CI=0.50-0.76) with a strong association between the measures (r=0.74, 95%CI=0.62-0.83). In our prototype and clinical cohorts, the app had a 100% completion rate with no safety occurrences and had high usability ratings. CONCLUSIONS: The Fit-Frailty App is a feasible and valid tool that can be used in research and clinical settings to comprehensively assess frailty and sarcopenia by non-geriatricians and could assist with developing targeted interventions.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".