"We Don't Like Unanswered Questions”: Information Practices of Students Transitioning to Clinical Education
Bibliographic record
Abstract
Objective – Health professions students are awash in large quantities of information, often conflicting, as they learn their professions. In order to navigate this information, librarians often engage with these students, usually in their didactic phase of education; however, the way students use information clinically may not be the same as the way they learn to do so in the classroom. This study investigated the information practices and experiences of health professions students early in the clinical phase of their education, in order to answer the following research questions: What are the information practices of health professions students at the transition to clinical education? How do these students understand how their practices have developed over their education? Methods – A purposive sample of learners from six health-focused professional programs participated in individual in-depth interviews, created timelines, and completed follow-up diary entries. The data were analyzed using inductive thematic analysis. Results – Students’ information practices are characterized by three themes. They are motivated to build competency to provide patient care; they operate in dual roles as student and clinician; and they navigate ambiguity, uncertainty, and doubt. They were able to describe the way they experienced information, problems they solved, and the development over time. Taken as a whole, this describes student experience with information as a method of making meaning from previous experience and learning with a focus on applying what they know and learn to improve patients’ lives and health. Conclusion – Insight into these students’ practices, including affective and social domains of practice, can inform librarian-led instruction and outreach within health professions and other professional programs. Linking education about information to students’ motivations to provide excellent patient care and their desire to operate scientifically in a world of doubt may provide more relevant instruction, leading to transference of learning to new environments.
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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 | 0.009 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| 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".