Reliability and validity of an observer-rated disfigurement scale for head and neck cancer patients
Bibliographic record
Abstract
BACKGROUND: Facial disfigurement is considered to be one of the most distressing aspects of head and neck cancer and its treatment, but it has been the focus of little systematic study. Existing studies have yielded conflicting results about the psychosocial impact of disfigurement. No studies to date have examined disfigurement using a valid and reliable observer-rated measure. The purpose of the current study was to examine the validity (convergent and discriminant) and the inter-rater reliability of a novel nine-point observer-rated disfigurement scale. METHODS: The sample consisted of 74 ambulatory head and neck cancer patients more than 6 months post treatment. Ratings of disfigurement were assigned independently by surgical and nonsurgical raters. Validity was assessed by comparing the association between disfigurement ratings and sociodemographic and illness treatment variables. Reliability was assessed by examining the concordance between the surgical and nonsurgical ratings. RESULTS: Disfigurement ratings were not associated with several sociodemographic variables, supporting the discriminant validity of the scale. Disfigurement was significantly related to a diagnosis of oral cancer, a history of adjunctive radiation, the type of surgical procedure performed, the degree of physical dysfunction, and the presence of postoperative complications. Observer ratings of disfigurement were significantly related to patient ratings of disfigurement. These findings support the convergent validity of the disfigurement scale. Inter-rater reliability of the scale was high (intraclass correlation coefficient =.91). CONCLUSION: The study provides preliminary evidence for the validity and inter-rater reliability of a novel nine point observer-rated disfigurement scale that may be useful in evaluating the impact of disfigurement on quality of life in head and neck cancer.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".