The Fatigue Pictogram: Psychometric evaluation of a new clinical tool
Bibliographic record
Abstract
Fatigue is one of the most prevalent side effects of cancer, yet clinicians may not focus on it during busy clinic appointments. The purpose of this project was to evaluate the psychometric properties of a new two-item instrument designed to quickly identify patients experiencing difficulties with fatigue. The evaluation was conducted with 190 lung cancer patients attending ambulatory clinics. The Fatigue Pictogram had good reliability for test-retest over a 24-hour period (Weighted Kappa 0.71 for Question 1 and 0.72 for Question 2) and for equivalence of method (in person versus phone) (Weighted Kappa 0.64 for Question 1 and 0.65 for Question 2). Validity was assessed by comparing results of the new tool against the Multidimensional Fatigue Inventory and the SF-36. Overall, patients who indicated high fatigue levels did so on all respective scales. The new Fatigue Pictogram was easy to administer and score in a busy clinical setting. It provides a standardized reliable and valid instrument to identify patients experiencing difficulty with fatigue.
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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 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".