2815 Cross-cultural adaptation and psychometric properties of the Yoruba version of the clinical frailty scale
Bibliographic record
Abstract
Abstract Background This cross-sectional study aimed to assess the socio-demographic, anthropometric, and patient characteristics of 94 Yoruba speakers aged 60 years and older, and to validate the Yoruba version of the Clinical Frailty Scale (CFS). Methods This study used a cross-sectional design with a purposive sampling technique and a sample size of 94 participants. This study also made use of the World Health Organisation methodologic guidelines on cultural adaptation of clinical scales. Convergent validity was assessed by evaluating the context that the Clinical frailty scale (CFS) relates to the Edmonton frailty scale, using the Spearman rank correlation coefficient. The known group validity was assessed using one-way ANOVA. Results The mean age of participants was 70.81 ± 8.11 years, with a mean BMI of 27.04 ± 5.61. The cohort included 38 males (44.4%) and 56 females (59.6%). Educational attainment varied, with 20.2% having no education and 9.6% holding postgraduate degrees. The validated CFS has excellent content validity (S-CVI/AVE = 0.96; S-CVI-UA = 0.78). Convergent validity demonstrated a moderate correlation between the CFS and the Edmonton Frail Scale (Spearman’s rho = 0.61, p < 0.01). Known-group validity indicated significant associations between frailty, age (p = 0.02), and BMI (p = 0.007). Conclusion The Yoruba version of the CFS is a valid tool for assessing frailty in elderly Yoruba-speaking populations.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".