Nurses joining family doctors in primary care practices: perceptions of patients with multimorbidity
Bibliographic record
Abstract
BACKGROUND: Among the strategies used to reform primary care, the participation of nurses in primary care practices appears to offer a promising avenue to better meet the needs of vulnerable patients. The present study explores the perceptions and expectations of patients with multimorbidity regarding nurses' presence in primary care practices. METHODS: 18 primary (health) care patients with multimorbidity participated in semi-directed interviews, in order to explore their perceptions and expectations in regard to the involvement of nurses in primary care practices. Interviews were audio-recorded and transcribed. After reviewing the transcripts, the principal investigator and research assistants performed thematic analysis independently and reached consensus on the retained themes. RESULTS: Patients with multimorbidity were open to the participation of nurses in primary care practices. They expected greater accessibility, for both themselves and for new patients. However, the issue of shared roles between nurses and doctors was a source of concern. Many patients held the traditional view of the nurse's role as an assistant to the doctor in his or her various duties. In general, participants said they were confident about nurses' competency but expressed concern about nurses performing certain acts that their doctor used to, notwithstanding a close collaboration between the two professionals. CONCLUSION: Patients with multimorbidity are open to the involvement of nurses in primary care practices. However, they expect this participation to be established using clear definitions of professional roles and fields of practice.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".