A Focused Ethnography of Baccalaureate Nursing Students Who Are Using Motivational Interviewing
Bibliographic record
Abstract
PURPOSE: The purpose of this article is to describe how nursing students learned and used motivational interviewing (MI) in a community-based clinical context at a primary care vascular risk reduction clinic focused on health promotion. DESIGN AND METHODS: A focused ethnography was used to access a sample of 20 undergraduate nursing students, 16 patients, and 2 instructors. Data were generated from participant observations, field notes, student journals, and interviews (one-on-one and focus group). FINDINGS: Central to the students' experience was their transformation because of learning and using MI. Three sub themes describe the social processes that shaped the student experience: learning a relational skill, engaging patients, and collaborating as partners. CONCLUSIONS: It is feasible for nursing students to learn MI and use this approach to enhance collaborative care in a primary care setting. The experience can be transformative for students. CLINICAL RELEVANCE: Supporting patients to adopt healthy lifestyles is a significant role for nurses in practice. The findings provide key insights and strategies for nurse educators teaching students a collaborative communication approach, such as MI, to engage patients in health behavior change.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".