Virtual fall program assessment for frail Canadian community-dwelling older adults: Examining equitable accessibility
Bibliographic record
Abstract
Objective: In response to COVID-19, the fall prevention program (FPP) at Sunnybrook Health Sciences Centre was modified to be delivered virtually. We compared patient populations assessed for the FPP virtually versus in-person to explore equitable accessibility. Methods: A retrospective chart review was performed. All patients assessed virtually from the beginning of the COVID-19 pandemic until the end of abstraction (April 25, 2022) were compared to a historic sample of patients assessed in-person beginning in January 2019. Demographics, measures of frailty, co-morbidity, and cognition were abstracted. Wilcoxon Rank Sum tests and Fisher's Exact tests were used for continuous and categorical variables, respectively. Results: Thirty patients were assessed virtually and compared to 30 in-person historic controls. Median age was 80 years (interquartile range 75-85), 82% were female, 70% were university educated, the median Clinical Frailty Score was 5 out of 9, and 87% used >5 medications. Once normalized, frailty scores showed no difference (p = 0.446). The virtual cohort showed significantly higher outdoor walking aid use (p = 0.015), reduced accuracy with clock drawing (p = 0.020), and nonsignificant trends toward using >10 medications, requiring assistance with >3 instrumental activities of daily living (IADLs), and higher treatment attendance. No significant differences were seen for time-to-treat (p = 0.423). Conclusion: Patients assessed virtually were similarly frail as the in-person controls but had increased use of walking aids, medications, IADL assistance, and cognitive impairment. In a Canadian context, frail and high socioeconomic status older adults continued to access treatment through virtual FPP assessments during the COVID-19 pandemic highlighting both the benefits of virtual care and potential inequity.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".