The Experience of Family Medicine Interns Conducting McGill ILLNESS Narrative Interview with Non-Compliant Chronic Patients
Bibliographic record
Abstract
ABSTRACT Despite several governmental policies with the purpose of changing medical training in Brazil, it is still predominantly hospital-centered, and the learning process is focused on diseases. We conducted a study in a traditional medical school, in which the students carried out an interview focused on the illness experience assessing chronic patients with compliance difficulties in the treatment of hypertension and/or diabetes in primary care. Fourteen medical students during the Family Medicine Internship at the Federal University of Rio de Janeiro were trained to carry out the McGill Illness Narrative Interview (MINI) and identify the modes of understanding and attribution of meaning to the illness and treatment experience. Before and after the completion of the set of 35 interviews, the students were listened to individually regarding their understanding of the compliance phenomenon and the experience with the MINI. The 35 interviews conducted by the students were analyzed with respect to the objectives of each section, in addition to interviewer’s general objective of offering a position of expertise to the patient in their report of the case. We sought to investigate the consistency of the student’s experience with this script to obtain the narrative of illness using conceptual topics – prototypes and explanatory models – and the emerging topics identified according to the technique described by Bardin for content analysis. In the analysis of the interviews conducted by the researcher with the interns at the beginning and the end of their internship, the content analysis consisted of two main themes: clinical understanding and experience with the non-compliance phenomenon, and the appreciation of performing the MINI in the context of medical training. The students considered the MINI a useful tool for understanding and exploring the individuals’ illness and their treatment experiences in their socioeconomic and cultural context. By recognizing the importance of the MINI, the interns usually reported few learning opportunities while providing care for patients. Although the students had previously recognized the importance of listening and the development of bonds, they did not know how these issues could be built, and the experience increased their confidence in the healthcare provided to patients in their medical daily life. The students noticed that non-compliance involved multiple factors, which did not usually emerge during regular medical appointments. In fact, there was more understanding about the compliance phenomenon.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".