The Pictorial Fit-Frail Scale—Malay version (PFFS-M): reliability and validity testing in Malaysian primary care
Bibliographic record
Abstract
BACKGROUND: This study investigated the reliability and convergent validity of the PFFS-Malay version (PFFS-M) among patients (with varying educational levels), caregivers, and health care professionals (HCPs). PFFS-M cutoffs for frailty severity were developed. METHODS: This is a cross-sectional study from 4 primary care clinics where 240 patients aged >60 years and their caregivers were enrolled. Patients were assigned to a nurse or a health care assistant (HCA) for 2 separate PFFS-M assessments administered by HCPs of the same profession, as well as by a doctor during the first visit (inter-rater reliability). Patients were also administered the Self-Assessed Report of Personal Capacity & Healthy Ageing (SEARCH) tool, a 40-item frailty index, by a research officer. The correlation between patients' PFFS-M scores and SEARCH tool scores determined convergent validity. Patients returned 1 week later for PFFS-M reassessment by the same HCPs (test-retest reliability). Caregivers completed the PFFS-M for the patient at both clinic visits. Classification cut-points for the PFFS-M were derived against frailty categories defined through the SEARCH tool. RESULTS: The inter-rater (intraclass correlation coefficient [ICC] = 0.92 [95% CI, 0.90-0.93)] and test-retest (ICC = 0.94 [95% CI, 0.92-0.95]) reliability between all raters was excellent, including by patients' education levels. The convergent validity was moderate (r = 0.637, p < 0.001), including for varying educational background. PFFS-M categories were identified as: 0-3, no frailty; 4-5, at risk of frailty; 6-8, mild frailty; 9-12, moderate frailty; and >13, severe frailty. CONCLUSION: PFFS-M is a reliable and valid tool with frailty severity scores now established for use of this tool in primary care clinics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".