The Process of Translating Family Nursing Knowledge Into Clinical Practice
Bibliographic record
Abstract
PURPOSE: To report on approaches that were used to assist with implementation of family systems nursing (FSN) at a university hospital level in Northern Europe. DESIGN AND METHODS: A quasi-experimental research design was used for the first phase of the study. For the second phase, a cross-sectional research design was used. Data were collected in the first phase of the study from 457 nurses in all except one of the divisions of the hospital regarding their attitudes towards involving families into their care before and after having participated in the education and training intervention (ETI) program in FSN. Furthermore, in the second phase, data were collected from 812 nurses, after FSN had been implemented in all divisions at Landspitali University Hospital, regarding the nurses' knowledge of FSN and their evaluation of the quality of the ETI program (i.e., theoretical lectures on FSN as well as the benefit of the skill lab training regarding applying FSN into their clinical practices). Graham and colleagues' Knowledge to Action framework was used as the conceptual framework for the research. RESULTS: Nurses who had taken a course in FSN reported a significantly more positive attitude towards involving families in their care after the ETI program compared to those who had not taken such a course. Furthermore, a majority of the nurses who participated in the ETI program reported that the program was a favorable experience and indicated readiness for applying FSN in clinical practice. CONCLUSIONS: Further research is needed regarding the benefits of offering FSN at an institutional level, but focusing international attention on effective strategies to implement FSN into nursing practice may result in better health care for individuals and families around the globe. CLINICAL RELEVANCE: Providing clinically meaningful education and training in family nursing through programs such as the ETI program for practicing nurses at a university hospital is essential in supporting nurses applying new knowledge, when providing evidence-based health care services, to individuals and their family members. Such training can facilitate integration of new and needed information in clinical 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 | 0.097 | 0.150 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".