Translating Knowledge From a Family Systems Approach to Clinical Practice: Insights From Knowledge Translation Research Experiences
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
While there has been continued growth in family nursing knowledge, the complex process of implementing and sustaining family nursing in health care settings continues to be a challenge for family nursing researchers and clinicians alike. Developing knowledge and skills about how to translate family nursing theory to practice settings is a global priority to make family nursing more visible. There is a critical need for more research methods and research evidence about how to best move family nursing knowledge into action. Enhancing health care practice is a multifactorial process that calls for a systemic perspective to ensure its efficacy and sustainability. This article presents insights derived from lessons learned through recent research experiences of using a knowledge translation model to promote practice changes in health care settings. These insights aim to optimize (a) knowledge translation of a Family Systems Approach (FSA) in practice settings; (b) knowledge translation research processes; and
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it