Nutrition education tools used in <scp>p</scp>henylketonuria: clinician, parent and patient perspectives from three international surveys
Bibliographic record
Abstract
BACKGROUND: Three international surveys were developed aiming to identify the current nutrition educational tools used in the management of phenylketonuria (PKU) and the perceived effectiveness of these tools by clinicians, parents and patients. METHODS: The first two surveys were distributed through the Metabolic Dietitians ListServe (pno-metabl@listserv.cc.emory.edu), and the third survey was distributed by international clinics and the National PKU Alliance website (www.npkua.org). A total of 888 responses (S1, n = 88; S2, n = 81; S3, n = 719) were collected from all three surveys. The surveys represent participants from 17 countries, in Europe; North America (USA and Canada); Mexico; Argentina; Turkey; Australia; and Africa (Tunisia). RESULTS: A consistent decline in 'parents as role models' as an educational tool was observed starting at age 10 years. Patients responded they feel their families are the most effective form of education, whereas handouts were selected as the least effective educational tool by patients. Parents responded they feel the most effective educational tool is one-on-one counselling. Patients and parents show a desirable trend in wanting to attend group clinic, even in centres where this type of educational tool is not offered. CONCLUSIONS: There was a discrepancy between clinicians and patient views regarding the perceived effectiveness of the nutrition education tools. Future research is needed surrounding the impact nutrition education may have on improved dietary compliance in patients with PKU.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".