Nurse Partners in Chronic Illness Care
Bibliographic record
Abstract
PURPOSE: To examine how patients with multiple chronic conditions perceive the role of nurses who function in a care management role in a primary healthcare setting. PARTICIPANTS: Thirteen patients between the ages of 56 and 88 years were recruited from an outpatient family practice clinic. All participants had type 2 diabetes, plus at least 1 chronic comorbid condition. METHOD: Data were collected using a semistructured interview protocol and analyzed using an iterative process. Interviews were coded independently by the core team and emerging themes were identified through weekly discussion. Discrepancies in coding and interpretation were resolved by reviewing transcripts and field notes as a group until consensus was reached. The core team met twice with advisory members to review conceptual constructs. CONCLUSIONS: Three themes emerged: (1) an overwhelming positive regard for the nurse partner, both as a person and a professional; (2) appreciation for the availability of the nurse partner; and (3) a perceived partnership with healthcare providers. Results provide evidence that the role is appreciated and that nurses provide care that is commensurate with patients' expectations and desires for healthcare. Future research must demonstrate the efficiency and sustainability of care coordination services for patients with chronic illness.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".