Patient‐reported outcome measures for dysphagia in head and neck cancer: A systematic review and appraisal of content validity and internal structure
Bibliographic record
Abstract
Dysphagia is a major head and neck cancer (HNC) issue. Dysphagia-related patient-reported outcome measures (PROMs) are critical for patient-centred assessment and intervention tailoring. This systematic review aimed to derive a comprehensive inventory of HNC dysphagia PROMs and appraise their content validity and internal structure. Six electronic databases were searched to February 2023 for studies detailing PROM content validity or internal structure. Eligible PROMs were those developed or validated for HNC, with ≥20% of items related to swallowing. Two independent raters screened citations and full-text articles. Critical appraisal followed COSMIN guidelines. Overall, 114 studies were included, yielding 39 PROMs (17 dysphagia-specific and 22 generic). Of included studies, 33 addressed PROM content validity and 78 internal structure. Of all PROMs, only the SOAL met COSMIN standards for both sufficient content validity and internal structure. Notably, the development of 18 PROMs predated the publication of COSMIN standards. In conclusion, this review identified 39 PROMs addressing dysphagia in HNC, of which only one met COSMIN quality criteria. Given that half of PROMs were developed prior to COSMIN guidelines, future application of current standards is needed to establish their psychometric quality.
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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 | 0.027 | 0.094 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".