Dietetic practice in the management of gestational diabetes mellitus: A survey of Australian dietitians
Bibliographic record
Abstract
Abstract Aim: To examine current Australian dietetic practice in the management of gestational diabetes, to identify models of dietetic care and to determine the need for national evidence‐based dietetic practice guidelines for gestational diabetes. Methods: A 55‐item cross‐sectional survey of Australian dietitians practicing in the area of gestational diabetes was undertaken. Participants were recruited via Dietitians Association of Australia interest group membership, public and private hospital maternity and diabetes services across Australia. The survey examined dietetic service provision, interventions, management recommendations, postnatal care, current guideline use and the perceived need for Australian evidence‐based dietetic management guidelines. Results: A total of 220 eligible dietitians participated in the survey. The majority (77%) reported that all women with gestational diabetes attending their service were referred to a dietitian. Group (33%) and individual consults (93%) were provided and 67% provided one to two dietetic consults per client. Fifty‐four per cent (54%) believed that their service currently offered adequate antenatal dietetic interventions and 8% adequate postnatal follow up for women with gestational diabetes. There were differences in the implementation of medical nutrition therapy by Australian dietitians in regards to nutrient recommendations. However, consistency was seen in key components of nutrition education. Dietitians perceived that there was a need for evidence‐based gestational diabetes dietetic practice guidelines (86%) and nutrition recommendations (87%). Conclusion: The survey results strongly indicate there is a need for evidence‐based gestational diabetes practice guidelines and nutritional recommendations and provide baseline data for future practice of Australian dietitians working in gestational diabetes.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".