Patient Narratives as a Teaching Tool: A Pilot Study of First-Year Medical Students and Patient Educators Affected by Intellectual/Developmental Disabilities
Bibliographic record
Abstract
PROBLEM: People with intellectual and developmental disabilities (IDD) face complex biopsychosocial challenges and are medically underserved. This is in part due to insufficient resources and supports but can also be attributed to a lack of adequate physician training in addressing the unique needs of this population. INTERVENTION: This study aimed to introduce 1st-year medical students to the IDD population using a blended educational experience that included video narratives of and direct interactions with people affected by IDD. The goal of this intervention was to promote person-centered attitudes and communication among early medical trainees. CONTEXT: The study recruited 27 first-year medical students and randomly assigned each to 1 of 2 groups. The control group received an introductory video lecture about IDD healthcare, followed by a quiz. The narrative group received the same lecture, followed by reflective discussion of videos featuring people living with IDD sharing their perspectives and stories. All students then participated in 4 simulated clinical encounters with patient educators (PEs) who have lived experiences of IDD. Focus groups were conducted with students following the simulated encounters to explore their experiences and perceptions of this blended learning activity. Moreover, secondary quantitative data were collected to assess students' performance in the clinical encounters, along with self-reports of comfort, confidence, and competence of interacting with people with IDD (pre- and postparticipation). OUTCOME: All students thought that the blended educational experience was valuable and enjoyable, commenting on the importance of adaptable language and engagement of people with IDD, as well as the merits of reflecting on patient narratives. Students also discussed feelings of discomfort stemming from a lack of knowledge and previous exposure to IDD and how this discomfort might motivate them to learn more and develop their skills further. In addition, descriptive analyses revealed that students in the narrative group showed greater self-rated measures of comfort, confidence, and competence compared to control; they also had higher mean performance scores across all PE interview stations. LESSONS LEARNED: PEs add a powerful real-life dimension to communication skills teaching and have been shown to be a valuable educational modality. Moreover, exposure to and reflection on video-based patient narratives are useful ways of teaching medical students about patients' lived experiences and promoting person-centered communication, both within and beyond IDD.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".