Consistencies and terminologies – the use of IDDSI
Bibliographic record
Abstract
INTRODUCTION: Introduction: this study aimed to verify the ability of speech therapists to identify, sort and name the different consistencies used in neurogenic oropharyngeal dysphagia (NOD) management, and to compare the results with the terms proposed by the International Dysphagia Diet Standardization Initiative (IDDSI). Methods: this research was approved by the ethics committee. Sixty speech therapists who work with NOD patients sorted 5 commercial foods from thinnest to thickest to match IDDSI levels 0 to 4, and then used a term to designate each consistency. Results: most subjects (76.66%) sorted the foods properly. Terminologies were divergent at all levels. For level 0, practitioners assigned 3 different terms. For level 1, 24 different terms were reported; for level 2 there were 25 terms, 23 terms for level 3, and 18 terms for level 4. Level 0 (IDDSI - thin) was designated by most participants as liquid; level 1 (IDDSI - slightly thick) was referred to as semi-thickened liquid; level 2 (IDDSI - mildly thick) as thickened liquid; level 3 (IDDSI - moderately thick) as honey; and level 4 (IDDSI - extremely thick) as pasty by most subjects. A reduced number of participants used terms in accordance with IDDSI. Level 0 was appropriately named by 5 subjects (8.33%); levels 1, 2 and 4 by 2 practitioners each (3.33%); and level 3 by 1 professional (1.66%). None of the subjects named all 5 IDDSI levels correctly. Conclusion: most practitioners progressed consistencies properly. There was a diversity of terminologies used for the same consistency at all levels, with no standardization.
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 | 0.029 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".