EQUATOR Network Mapping Review for Dysphagia Research
Bibliographic record
Abstract
PURPOSE: The EQUATOR Network is an international initiative aimed at improving published health research through use of reporting guidelines. We conducted a review to determine the extent to which EQUATOR Network guidelines contain recommendations relevant for dysphagia research in human subjects. METHOD: We downloaded all 542 EQUATOR Network guidelines on November 8, 2022. Each guideline was reviewed by two independent raters and judged for relevance to dysphagia and related fields (e.g., otolaryngology, gastroenterology). Dysphagia-relevant guidelines pertaining to quantitative human subjects research were further inspected to identify reporting guidance regarding (a) general research elements (e.g., data collection, statistical methods), (b) participant characteristics (e.g., demographics, accrual, randomization), (c) screening and clinical/noninstrumental assessments, (d) videofluoroscopic examinations, (e) flexible endoscopic examinations, (f) other instrumentation in swallowing research, (g) dysphagia treatment, (h) patient-/care provider-reported outcome measures, and (i) any other narrowly specified focus relevant for research on swallowing. Discrepancies were resolved by consensus. RESULTS: Of 542 guidelines, 156 addressed quantitative research in human subjects relevant to dysphagia. Of these, 104 addressed general research elements and 108 addressed participant characteristics. Only 14 guidelines partially addressed the other topics of interest, and none addressed elements relevant to reporting videofluoroscopic or endoscopic assessments of swallowing. CONCLUSIONS: We were unable to find guidelines with specific relevance to reporting key methods in dysphagia research. This lack of guidance illustrates a gap that hinders the critical appraisal of research quality in the field of dysphagia. Our review highlights the need to develop dysphagia-specific tools for critical appraisal and guidance regarding adequate research reporting. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25014017.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".