Consumer-oriented (patient and family) outcomes from nursing in genomics: a scoping review of the literature (2012–2022)
Bibliographic record
Abstract
Introduction: Genomics is a lifespan competency that is important for improving health outcomes for individuals, families, and communities. Nurses play a key role in genomic healthcare and realizing the potential of the genomic era. Methods: We aimed to chart the current state of genomics in nursing by conducting a systematic scoping review of the literature in four databases (2012-2022). We categorized included articles using the Cochrane Collaboration outcome domains/sub-domains and identify key topical areas. Results: Of 8532 retrieved articles, we identified 67 articles on 'consumer-oriented outcomes' (patient and family) for analysis. Identified articles primarily centered on themes of genetic testing and screening. Most studies reported non-interventional studies 39/67 (58%) and more than half were from the U.S.A. 34/67 (51%). Six of nine subdomains were reported on. The "patient involvement in care" subdomain was the most commonly reported subdomain (17/67, 25%) while "treatment outcomes" had the fewest reports (5/67, 8%). Overall, consumers (i.e., patients and families) had high satisfaction with nurse-led interventions. Discussion: Synthesizing findings revealed key knowledge gaps and unmet patient informational needs around genetic testing and decision support. There are opportunities for interprofessional collaboration between nursing and genetic counseling to meet the mounting demand for genomic healthcare and develop more person-centered approaches to genetic counseling and decisional support. Findings support the need for interventional studies and enhanced focus on implementation for nurses to improve consumer-oriented outcomes.
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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 | 0.028 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.031 | 0.029 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".