Integrated self-management support provided by primary care nurses to people with chronic diseases and common mental disorder
Bibliographic record
Abstract
Context: Chronic diseases (CD) and common mental disorders (CMD), increasingly prevalent in primary care, account for a large amount of mortality and morbidity worldwide. Self-management support (SMS) represents an important activity for primary care nurses and people with CD and CMD requires an integrated approach. In-depth description of the experiences of primary care nurses performing integrated SMS for persons with CD and CMD could improve this essential activity. Objective: The main objective of this study was to explore the experiences of primary care nurses performing integrated SMS for persons with CD and CMD. Secondary objectives were to describe 1) how clinical integration of SMS is done; 2) activities; 3) factors influencing integrated SMS; and 4) strategies to improve integrated SMS. Study Design and Analysis: Interpretive descriptive qualitative approach. Setting or Dataset: Family medicine groups (FMG) in the province of Quebec, Canada. Population Studied: A sample of 23 primary care nurses was recruited using purposive and snowball sampling. To be included, nurses needed to: 1) have worked at least one year in an FMG; 2) follow persons with concurrent CD and CMD; and 3) speak French. Many strategies were used to contact the participants. Intervention/Instrument: Data collection was done using virtually semi-structured interviews of 60-90 minutes. The interview guide consisted of open-ended questions and follow-up questions based on the objectives, results of a scoping review, and Valentijn’s Rainbow model of integrated care. Outcome Measures: Miles et al. iterative inductive-deductive thematic analysis method was used for data analysis. Valentijn’s model and Pearce’s PRISMS taxonomy were used for deductive analysis. Analysis was done in team and a reflexive journal was kept. Results: This study highlights how primary care nurses clinically integrate SMS for CD and CMD through promotion of good health habits and prevention of risks factors using education, support activities and an approach that encompasses person-focused care and cocreation of SMS process. Factors influencing clinical integration of SMS at the clinical (e.g., skills, knowledge) and external level (e.g., collaboration, roles, culture) were identified, as well as strategies to improve it (e.g., training, clinical support). Conclusions: Integrated SMS is a promising, yet complex, approach that is critical to ensure that persons with CD and CMD gets the right care.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".