Development of client-centredness: Perceptions of interprofessional health care students.
Bibliographic record
Abstract
Background: Health care professionals who provide high-quality care engage in interprofessional collaborative practice. Engaging collaboratively requires that educators ensure health care students have well-developed client-centred knowledge, skills, values, and attitudes. Limited research exists to help educators understand how to support health care students' client-centred development. Purpose: This study aimed to use storytelling and reflection to advance understanding of client-centredness development from the perspective of prelicensure health care students. Method: In this interpretive description study, 6 students from various health disciplines engaged in 3 focus group sessions over 5 months to discuss client-centred experiences. Digital stories were introduced to stimulate discussion. Focus group data were inductively analysed using thematic analysis. Results: Four themes related to client-centred development emerged: 1) building on existing professional knowledge; 2) internalizing client-centredness as an evolving process; 3) sharing stories; and 4) reflecting: a critical process. Discussion: Consistent with the limited evidence, employing storytelling and reflection in an interprofessional education setting enabled students to explore the concept of client-centredness in a way that enriched the discussion and their perceptions. Conclusion: Health care students benefit from storytelling and open discussion opportunities to learn with, from, and about each other in an interprofessional education context as they internalize client-centredness and move beyond their professional education programs' knowledge and skill-based foundations.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".