Clinical ladders are positively associated with job satisfaction and career advancement for registered dietitians in clinical nutrition management
Bibliographic record
Abstract
Background: Following a change in reporting structure, Registered Dietitian Nutritionists (RDNs) in a Virginia hospital system provided patients with better care, cost savings, and almost doubled clinical nutrition staff from 2008 to 2013. Objective The study was conducted to determine if the administrative alignment of RDNs in their place of employment 1) allows them to perform to their greatest scope of practice and 2) influences job perceptions.Methods: A survey was developed and distributed nationally to CNMs and their coworkers. Statistical analyses: Using SPSS 24, univariate descriptive statistics and bivariate analyses were conducted. Contingency tables were generated and Pearson Chi-square tests and as appropriate Fishers’ exact tests were used to draw statistical inferences.Results: Respondents (n=508) represented four regions of the US with various job titles. Some reported to vice presidents of support services (34%) and others reported to vice presidents overseeing both clinical and support services (26%). Respondents, regardless of alignment, were either ‘satisfied’ (47%) or ‘very satisfied’ (36%) with their current positions. Most (74%) were in a nutrition department separate from food service. There was no difference in education (p=0.87) or pay (p=0.62) dependent on reporting structure. However, when RDNs reported to a clinical nutrition department, separate from food service, it was more likely that there was a clinical ladder for RDNs and there were more levels on the clinical ladder.Conclusion: This survey suggests alignment of a clinical nutrition department is associated with a higher likelihood that RDNs will have a clinical ladder to promote career advancement.
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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 | 0.013 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".