Dysphagia Identification and Assessment in Adults in Primary Care Settings—A Canadian Study of Dietitians
Bibliographic record
Abstract
Dysphagia affects up to 35% of older adults living in the community and is considered a significant risk factor for malnutrition and aspiration. Early intervention is important, yet dietitian referrals for dysphagia management in primary care are disproportionately low considering the prevalence of dysphagia and its risk factors. As little is known about dietitian's current dysphagia identification and assessment practices in Canada, an online survey was developed. Registered dietitians practicing in primary care were invited to participate. Of the 70 surveys completed, nearly 75% do not have a dysphagia screening process where they practice, and only 8% reported performing noninstrumental, clinical swallowing assessment (CSA). Lack of competency or skills required to complete dysphagia screening and assessment was the most reported barrier. Many respondents were unsure or did not believe CSA fell within their scope of practice, and over 70% reported needing hands-on dysphagia screening and assessment training. Current practices in primary care could be placing individuals with dysphagia, and those at risk, in jeopardy of being overlooked. Initiatives to increase dysphagia awareness, create screening processes, and increase awareness of dietitian's scope of practice are needed to enable primary care dietitians to develop competency in dysphagia screening and assessment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".