Patients as educators: the challenges and benefits of sharing experiences with students
Bibliographic record
Abstract
CONTEXT: Despite movement towards active patient involvement in the education of health professionals, explorations of the experiences of patient-educators beyond descriptive research are limited. OBJECTIVES: The purpose of this study was to identify the positive and negative factors that contributed to the experiences of patient-educators in a health mentors programme for health professional students at a Canadian university. METHODS: Semi-structured focus group discussions and individual interviews were used to elicit the experiences of 30 patient-educators with chronic conditions or disabilities, of the 151 involved in the programme. Thematic analysis was used to identify key themes in the participants' experiences. RESULTS: Study participants spoke of the potential challenges and benefits of sharing their experiences. The main challenge involved in sharing their experiences was potential vulnerability should students not appreciate what was shared. The main benefits were personal learning and making valued contributions. Two factors influenced the participants' sense of whether the potential benefits outweighed the challenges of personal sharing in the programme: monitoring disclosure, and perceived student learning. Participants used the strategy of monitoring their disclosure to limit how much personal information they shared with students. The benefits of participating in the programme outweighed the potential challenges when students were seen to embrace the intended messages of the patient-educators. CONCLUSIONS: The results of this study provide a conceptual framework that can be used to better prepare patient-educators and students for more reciprocal learning interaction.
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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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.014 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.005 | 0.006 |
| 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".