A mixed methods pilot study of a serious illness communication training curriculum among medical residents
Bibliographic record
Abstract
Background: It is crucial that clinicians develop skillful communication to support patients to improve their illness understanding. A strong understanding of illness is associated with improved quality of life and care that is consistent with patient priorities. Unfortunately, many clinicians lack these skills, and residents, in particular, feel unprepared. The ABCs (All Providers, Better Communication Skills) is a virtual curriculum that teaches core communication skills to facilitate conversations with people who are living with serious illnesses. Objectives: We explored whether the ABCs curriculum increases self-efficacy and addresses self-reported weaknesses in communication training for internal medicine (IM) and family medicine (FM) residents. Design: We conducted a prospective sequential mixed methods cohort study. Methods: Residents completed pre-/post-curriculum self-assessment surveys and a post-curriculum semi-structured interview. Primary outcomes were changes in self-efficacy, whether the curriculum addressed self-identified training needs and feedback on its structure and delivery. Secondary outcomes included feedback on how the modules could be tailored to IM and FM-specific content. Results: Twelve residents completed the study. Most were in IM, female, and aged 26–30 years. Self-efficacy improved significantly as per the SE-12 summative score (mean difference 11.5 points (SD 10.35), p = 0.003). The study-created items showed a significant improvement in breaking bad news (0.83 (SD 0.84), p = 0.005), overall knowledge (0.67 (SD 0.65), p = 0.005), and confidence (0.67 (SD 0.50), p = 0.001). Key strengths of the curriculum were its structured approach, focus on allowing for silence, transferrable skills, and practical application. The virtual format was both a strength and a weakness, as residents appreciated its accessibility but valued real-time practice. Conclusion: The ABCs improved self-efficacy among IM and FM residents. We will use results from this study to inform future iterations of the platform that are tailored to resident-specific learning needs and improving patient-centered outcomes.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".