Factors influencing the practice of new graduate nurses: A focused ethnography of acute care settings
Bibliographic record
Abstract
AIM: To explore the influence of an acute care setting on competency deployment of new graduate nurses (NGNs) from a competency-based undergraduate programme. BACKGROUND: In the last 15 years, nursing education has shifted to competency-based education (CBE). Few studies have focused on how NGNs from these reformed programmes use the competencies they have developed. To be paradigmatically coherent with the nature of a competence, studies should also examine how context influences nursing practice and competency deployment. DESIGN: A focused ethnography of three acute care units from one academic hospital in Canada. METHODS: Purposive and snowball sampling strategies were used to recruit 19 participants: NGNs (n = 4), nurse preceptors (n = 2), clinical nurse specialists (n = 9) and nurse managers (n = 4). Data were collected through individual interviews, focus groups, observation and documentation. Data were analysed according to Roper and Shapira (Ethnography in nursing research. Thousand Oaks, CA: Sage Publications, 2000) ethnographic nursing analysis framework. RESULTS: Organisational and individual factors were identified as influencing NGNs' competency deployment. Organisational factors are orientation, stability, workload and the scientific culture of the unit. Personal factors have been linked to groups of professionals: for NGNs, personality and clinical placements during their initial education; for nurses working with NGNs, to be role models, to promote integration and to denounce bullying; and for other health professionals, to recognise nursing expertise. CONCLUSION: One way to smooth the transition from academic to clinical settings for NGNs is by offering transition or orientation programmes that will provide them with stability and a reduced workload, allowing them to progressively deploy their competencies. RELEVANCE TO CLINICAL PRACTICE: Organisational and individual factors influence how new graduate nurses deploy their competencies. Clinical educators and nurse managers can help new nurses by acting on these factors. This study conforms to the COREQ Research Reporting Guidelines for qualitative studies.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".