Psychometric Properties of the Japanese Version of the Edmonton Functional Assessment Tool 2
Bibliographic record
Abstract
CONTEXT: Physical symptoms such as pain and cancer-related fatigue limit physical function and activities of daily living among patients with terminal cancer, which can lead to a decline in quality of life. Therefore, comprehensive functional impairments should be evaluated to determine the progression of the disease and the effectiveness of palliative treatment. OBJECTIVE: To validate the psychometric properties of the Japanese version of the Edmonton Functional Assessment Tool 2 (EFAT2-J). METHODS: We developed a Japanese version of the EFAT-2 in accordance with international guidelines. To verify the reliability and validity of the EFAT2-J, patients were evaluated by a physiotherapist and a nurse separately, and correlations with existing evaluation scales for physical function, physical symptoms, and quality of life were analyzed, respectively. The significance level was set at 5%. RESULTS: Twenty patients participated in the reliability measurement. The average EFAT2-J scores were 7.95 ± 4.12 for physical therapists and 7.20 ± 4.23 for nurses, and the intraclass correlation coefficient was 0.95. The weighted kappa coefficient (κ) for each item was 0.57-1.00. Fifty-five patients participated in the validity measurement. The EFAT2-J showed significant correlations with Eastern Cooperative Oncology Group Performance Status and the Karnofsky Performance Scale, Barthel Index, and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 15-Palliative Care sub-item "physical function." CONCLUSION: These results indicate that the EFAT2-J has robust psychometric properties and is useful for evaluating physical function in patients with terminal cancer, and thus may be an acceptable clinical instrument in research and practice.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".