Integrating the Illness Beliefs Model in Clinical Practice
Bibliographic record
Abstract
To promote the integration of Family Systems Nursing (FSN) in clinical practice, we need to better understand how nurses overcome the challenges of FSN knowledge utilization. A qualitative exploratory study was conducted with 32 practicing female nurses from hospital and community settings who had received FSN intervention training and skill development based on the Illness Beliefs Model and the Calgary Family Assessment and Intervention Models. The participants were interviewed about how they utilized FSN knowledge in their nursing practice. From the data analysis, a FSN Knowledge Utilization Model emerged that involves three major components: (a) nurses' beliefs in FSN and in their FSN skills, (b) nurses' knowledge utilization strategies to address the challenges of FSN practice, and (c) FSN positive outcomes. The FSN Knowledge Utilization Model describes a circular, incremental, and iterative process used by nurses to integrate FSN in daily nursing practice. Findings point to a need for re-evaluation of educational and management strategies in clinical settings for advancing the practice of FSN.
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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 | 0.012 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".