<scp>Kihon Checklist</scp> to assess frailty in older adults: Some evidence on the internal consistency and validity of the <scp>Spanish</scp> version
Bibliographic record
Abstract
AIM: The aim of this study was to assess the internal consistency, hypothesis testing and criterion-related validity of the Spanish versions of the Kihon Checklist (KCL) - the original 25-item and reduced 15-item versions - for screening frailty in community-dwelling older adults. METHODS: A cross-sectional study was carried out between March and September 2018 in Valencia province (Spain). A sample of 251 participants was recruited. Construct validity was assessed using four different frailty instruments, and alternative measures corresponding to the KCL domains (handgrip strength, gait speed, the Short Physical Performance Battery, skeletal muscle mass index, physical activity level, functional status, cognitive function, depressive mood, health-related quality of life and nutritional status). Fried's Frailty Phenotype was used to evaluate criterion validity. RESULTS: Internal consistency assessed with Kuder-Richardson Formula had a value of 0.69 for the 25-item version, slightly lower than the usual 0.7 for considering good reliability, and 0.71 for the 15-item version. There were significant correlations between KCL versions and Fried's Frailty Phenotype, Edmonton Scale, Tilburg Indicator and FRAIL Scale. Consistent significant correlations were also obtained with all frailty measurements and instrumental activities of daily living, physical strength, eating, socialization, and mood domains of the KCL. The KCL closely correlated with other standardized measurements of physical function, cognitive function, depressive mood, and health-related quality of life. The KCL also showed satisfactory diagnostic accuracy for frailty (area under the curve 0.891 for KCL-25; area under the curve 0.857 for KCL-15). The optimal cut-off points were 5/6 and 3/4, respectively. CONCLUSIONS: The findings suggest that both versions of the KCL, especially KCL-15, showed adequate evidence of validity and internal consistency as a preliminary screening of frailty among community-dwelling older adults in Spain. Geriatr Gerontol Int 2021; 21: 262-267.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".