Tools to Identify Community-Dwelling Older Adults in Different Stages of Frailty
Bibliographic record
Abstract
There is a paucity of evidence regarding the ability of health professionals to recognize and manage frailty in community settings before it contributes to significant functional dependency. The purpose of this study was to examine, through a systematic review of the literature, tools that can identify community-dwelling older adults in different stages of frailty. We searched multiple electronic databases (Med-line, Embase, Psycinfo, Cinahl, Scopus, Ageline, Eric, Hapi). Our search yielded 27 articles that met established criteria. Most commonly used tools included Fried et al.'s Frailty Phenotype (2001), Rockwood et al.'s Frailty Classification (1999), and Speechley and Tinetti's Classification of Frailty and Vigorousness (1991). With our rapidly aging population an increasing number of health services are being provided in the community and it is important that therapists have the necessary tools to enable timely and well-targeted intervention.
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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 | 0.012 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.030 | 0.015 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".