The Brief Rehabilitation Assessment for Survivors of Head and Neck Cancer (BRASH): Content and Discriminant Validity
Bibliographic record
Abstract
Background: Survivors of head and neck cancer (HNC) face challenges that may negatively impact health-related quality of life. Despite evidence suggesting that rehabilitation addresses many of their needs, survivors of HNC do not consistently receive rehabilitation services. Purpose: To evaluate the content and discriminant validity of the newly developed Brief Rehabilitation Assessment for Survivors of Head and Neck Cancer (BRASH), a patient-centered assessment tool. Methods: To assess content validity, 20 health care professionals completed the Content Validity Index (CVI). To assess discriminant validity, the BRASH goals and scores of 23 participants were compared with the items and scores of a standardized health-related quality-of-life measure. Data were analyzed using Spearman ρ correlation coefficients. Results: The BRASH received a CVI score of 0.81, indicating acceptable content validity. The BRASH's physical, cognitive/psychosocial, activity/role, open-ended question, and goal-setting domains received CVI scores of 0.81, 0.70, 0.84, 1.00, and 0.74, respectively, indicating acceptable content validity by domains. Regarding discriminant validity, of the 35 goals identified in the BRASH, 71% were addressed by the standardized measure. Correlations between the scores on the BRASH and the standardized measures were moderate to weak. Limitations: This study provides initial support for content and discriminant validity of the BRASH. Future research should examine additional aspects of validity and responsiveness. Conclusions: The BRASH demonstrates acceptable content validity, suggesting that it adds value to patient-centered rehabilitation consultation for survivors of HNC. In comparison with a standardized quality-of-life measure, it specifically focuses on rehabilitation needs of the individual patient.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".