Understanding genetics in nursing care – A qualitative interview study
Bibliographic record
Abstract
Objective: The aim of the present study was to investigate the use of genetics/genomics (G/G) knowledge and competencies in a Danish nursing context.Methods: Using a qualitative approach, thirteen Danish nurses representing different parts of the Danish health care system were interviewed about their experiences with G/G in daily practice. One focus group interview was conducted face to face, and nine individual semi-structured interviews were conducted partly face to face, partly online due to Covid-19 restrictions. Data were analyzed through systematic text condensation using the NVIVO13 tool (QSR International).Results: We identified five themes: 1) The nature of genetics; 2) Knowledge about genetics; 3) The roles of the nurse; 4) Nurses’ engagement with patients and relatives; 5) Patient pathways. Ethics was a recurrent theme in all five themes.Conclusions: The Danish nurses interviewed generally hold a narrow understanding of genetics i.e. defining it as heredity. They are involved in G/G aspects of care, although the extent and nature of this involvement varies considerably between different care settings. Hence, it seems unlikely that all nurses will require the same G/G knowledge and competencies. Nevertheless, the nurses share the belief that they should possess some basic knowledge about G/G to perform adequate nursing care. Their current knowledge about G/G is typically informed by practice and to a very small degree by their formal education. They agree that G/G literacy will be a general requirement in future nursing. Some of the nurses consider personalized medicine to be the golden road to better patient treatment and care. Some request more knowledge about G/G topics and a vocabulary to communicate adequately with doctors, patients and relatives on these issues. The importance of ethics is emphasized throughout the interviews.
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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 | 0.022 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".