<scp>Cross‐cultural</scp> adaptation of the <scp>FRAIL</scp> scale for critically ill patients in Spain
Bibliographic record
Abstract
AIM: To translate and culturally adapt the FRAIL scale into Spanish and perform a preliminary test of diagnostic accuracy in patients admitted to intensive care units. DESIGN: Cross-sectional diagnostic study. METHODS: Five intensive care units (ICU) in Spain were participated. Stage 1: Three native Spanish-speaking bilingual translators familiar with the field of critical care translated the scale from English into Spanish. Stage 2: Three native English-speaking bilingual translators familiar with critical care medicine. Stage 3: Authors of the original scale compared the English original and back-translated versions of the scale. Stage 4: Five nurses with more than 5 years of ICU experience and five critical care physicians assessed the comprehension and relevance of each of the items of the Spanish version in 30 patients of 3 different age ranges (<50, 50-65 and >65 years). RESULTS: The FRAIL scale was translated and adapted cross-culturally for patients admitted to intensive care units in Spain. The process consisted of four stages: translation, back translation, comparison and pilot test. There was good correspondence between the original scale and the Spanish version in 100% of the items. The participating patients assessed the relevance (content validity) and comprehensibility (face validity) of each of the items of the first Spanish version. The relevance of some of the items scored low when the scale was used in patients younger than 65 years. CONCLUSIONS: We have cross-culturally adapted the FRAIL scale, originally in English, to Spanish for its use in the critical care medical setting in Spanish-speaking countries. IMPLICATIONS FOR PROFESSIONALS: Physicians and nurses can apply the new scale to all patients admitted to the intensive care units. Nursing care can be adapted according to frailty, trying to reduce the side effects of admission to these units for the most fragile patients. REPORTING METHOD: The manuscript's authors have adhered to the EQUATOR guidelines, using the COSMIN reporting guideline for studies on the measurement properties of patient-reported outcome measures. PATIENT OR PUBLIC CONTRIBUTION: In a pilot clinical study, we applied the first version of the FRAIL-Spain scale to intensive care unit (ICU) patients. Five nurses with more than 5 years of ICU experience and five critical care physicians assessed the relevance (content validity) and comprehensibility (face validity) of the five items of the first Spanish version. Relevance was assessed using a 4-point Likert scale ranging from 1 (no relevance) to 4 (high relevance), and comprehensibility was assessed as poor, acceptable or good. Each health professional applied the scale to three patients (total number of patients = 30) of three different age ranges (<50, 50-65 and >65 years) and recorded the time of application of the scale to each patient. Although the frailty scales were initially created by geriatricians to be applied to the elders, there is little experience with their application in critically ill patients of any age. Therefore, more information is needed to determine the relevance of using this scale in critical care patients. In this pilot study, we considered that nurses and critical care physicians should evaluate frailty using this adapted scale in adult patients admitted to the Intensive Care Units.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".