The Fatigue Pictogram: Assessing the psychometrics of a new screening tool
Bibliographic record
Abstract
Fatigue is one of the most distressing side effects of cancer for patients, yet clinicians often do not focus on it during busy clinic appointments. The purpose of this project was to evaluate the psychometric properties of a new instrument designed to quickly identify patients experiencing difficulties with fatigue. The evaluation was conducted with a mixed group of 220 patients receiving chemotherapy. The two-item Fatigue Pictogram had good reliability for test-retest over a 24-hour period (Spearman Coefficient 0.69 for Question 1 and 0.72 for Question 2) and for equivalence of method (in person versus phone) (Spearman Coefficient 0.69 for Question 1 and 0.59 for Question 2). Validity was assessed by comparing results of the new tool against the Multidimensional Fatigue Inventory and the FACT-an. 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 screen patients experiencing difficulty with fatigue and set the stage for a conversation about this bothersome side effect.
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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 | 0.006 | 0.022 |
| 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 | 0.000 | 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".