Promoting Health in Type 2 Diabetes: Nurse-Physician Collaboration in Primary Care
Bibliographic record
Abstract
The purpose of this study is to examine effects of a nurse-physician collaborative approach to care of patients with type 2 diabetes and to determine possible effect sizes for use in computing sample sizes for a larger study. Forty patients from a family practice clinic with type 2 diabetes were randomly assigned to control or experimental groups. The control group received standard care, whereas the experimental group received standard care plus home visits from a nurse, as well as consultation with an exercise specialist and/or nutritionist. Follow-up continued for 3 months. Clinical end points included standard measures of diabetes activity as well as quality-of-life indicators. Focus group interviews were used to explore patients' responses to the program. Although findings were not statistically significant, a trend toward small to moderate positive effect sizes was found in glycosylated hemoglobin and blood pressure. Quality of life measures also showed a trend toward small to moderate, but nonsignificant, improvements in physical functioning, bodily pain, vitality, social and global functioning, energy, impact of diabetes, and health distress. Focus group interviews indicated a very positive response from patients, who expressed feelings of empowerment. In this study, patients treated with nurse-physician collaboration demonstrated small, but nonsignificant, improvements in blood chemistry after only 3 months. Physical and social functioning, energy, and bodily pain also showed a small improvement. Changes in awareness of effects of diabetes on health and an expressed sense of self-efficacy suggest that effects could be sustainable over the longer term.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".