<i>A Definition, Description, and Framework</i> For Advanced Practice in Dietetics
Bibliographic record
Abstract
PURPOSE: We explored advanced practice (AP) across the diversity of dietetics to develop a definition, description, and framework for guiding future education, research agendas, and policy development. METHODS: The process began with a literature review and discussion with dietitians exploring AP in other countries. Various concepts were identified, and these informed the phase 1 survey questions. Phase 1 was a 36-item survey created in SurveyMonkey, engaging a purposeful sample of key stakeholders (n=136). A modified Delphi approach, involving seven dietitians from different geographical locations and practice areas, finalized the phase 2 survey. An e-mail link to this 50-item survey was sent to a random sample of dietitians (n=885). The proposed AP framework entailed an iterative approach, integrating survey results with AP literature. RESULTS: Response rates were 40% for phase 1 and 35% for phase 2. In phase 1, 83% of respondents agreed that a depth and breadth definition captured all dietetic job roles, and 95% agreed that it differentiated AP from entry-level practice. Descriptive statistics are presented to provide demographic information and level of agreement with themes relevant to AP. CONCLUSIONS: A framework is presented, and discrepancies with phase 2 results indicate areas for professional development, such as leadership, mentorship, and outcome measurement.
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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 | 0.007 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".