"Walking the talk" in the integration of chronic disease prevention management: dietitians' perspectives regarding diabetes management in adult peritoneal dialysis programs in Ontario
Bibliographic record
Abstract
Ontario???s Chronic Disease and Prevention Framework (CDPM) is a framework\naimed at improving health outcomes and reducing costs. Currently, there is a paucity of\ndata examining diabetes management (DM) in peritoneal dialysis (PD) programs. This\nstudy, carried out in 2010-11, describes dietitians??? perspectives regarding DM in PD\nprograms in Ontario. Purposeful sampling of dietitians employed in PD programs (n=18)\nresulted in a response rate of 86.6%. A web-based survey collected data on demographic\ncharacteristics of PD clients, program models, and program-specific data regarding\nfacilitators and barriers to provision of dialysis-specific diabetes education. Statistical\nanalysis was completed and responses to open-ended questions examined using thematic\nopen-coding. Findings suggest three major themes: ???walking the CDPM talk???, dietitians\nas ???unrecognized CDPM champions??? and ???the missing pieces to the CDPM puzzle???.\nResults suggest that while many dietitians have embraced CDPM, their capacity to fully\nintegrate it into their practices is limited by organizational- and system-level barriers.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".