Three-year assessment of one pre-licensure cohort of baccalaureate nursing students’ attitude, comfort and knowledge of genomics
Bibliographic record
Abstract
Objective: Descriptive three-year comparison of one pre-licensure cohort of baccalaureate nursing students’ genomic knowledge, attitude and comfort level.Methods: Two analyses were of interest, utilizing the same survey instrument, Genetics/Genomics Literacy Assessment (GGLA): 1) Comparison of pre vs. post intervention on the sophomore (2nd year) class and 2) Retention of the information through junior (3rd year) and senior year (4th year). Two analyses were of interest: 1) Comparison of pre-class vs. post-class assessment on sophomore [2nd year] students and 2) Retention of the information through junior [3rd year] and senior year [4th year].Results: For the total score variable [retention of genomic knowledge over time] data was sophomore vs junior vs senior means of 7.1 vs. 6.9 vs. 8.7, p < .001 showing maintenance from sophomore (post-class assessment) to junior year with an increase in the senior year score for the cohort of students. Comparison of pre-class vs post-class on the sophomore class resulted in statistically significant differences demonstrating higher knowledge after class. Enhancement of confidence, perceptions and attitude regarding genomics was evident with comparison of pre-class vs. post-class and overtime after taking foundational course. Overall, data showed that students felt that nurse educators need more confidence in teaching and explaining as well as in patient advocacy.Conclusions: Promoting knowledge and practice integration of universal genomic health requires healthcare professionals, educators and students be knowledgeable and cognizant of their participation to advance client health 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".