Effects of Practicing With and Obtaining Crowdsourced Feedback From the Video-Based Communication Assessment App on Resident Physicians’ Adverse Event Communication Skills: Pre-post Trial
Notice bibliographique
Résumé
BACKGROUND: US residents require practice and feedback to meet Accreditation Council for Graduate Medical Education mandates and patient expectations for effective communication after harmful errors. Current instructional approaches rely heavily on lectures, rarely provide individualized feedback to residents about communication skills, and may not assure that residents acquire the skills desired by patients. The Video-based Communication Assessment (VCA) app is a novel tool for simulating communication scenarios for practice and obtaining crowdsourced assessments and feedback on physicians' communication skills. We previously established that crowdsourced laypeople can reliably assess residents' error disclosure skills with the VCA app. However, its efficacy for error disclosure training has not been tested. OBJECTIVE: We aimed to evaluate the efficacy of using VCA practice and feedback as a stand-alone intervention for the development of residents' error disclosure skills. METHODS: We conducted a pre-post study in 2020 with pathology, obstetrics and gynecology, and internal medicine residents at an academic medical center in the United States. At baseline, residents each completed 2 specialty-specific VCA cases depicting medical errors. Audio responses were rated by at least 8 crowdsourced laypeople using 6 items on a 5-point scale. At 4 weeks, residents received numerical and written feedback derived from layperson ratings and then completed 2 additional cases. Residents were randomly assigned cases at baseline and after feedback assessments to avoid ordinal effects. Ratings were aggregated to create overall assessment scores for each resident at baseline and after feedback. Residents completed a survey of demographic characteristics. We used a 2×3 split-plot ANOVA to test the effects of time (pre-post) and specialty on communication ratings. RESULTS: In total, 48 residents completed 2 cases at time 1, received a feedback report at 4 weeks, and completed 2 more cases. The mean ratings of residents' communication were higher at time 2 versus time 1 (3.75 vs 3.53; P<.001). Residents with prior error disclosure experience performed better at time 1 compared to those without such experience (ratings: mean 3.63 vs mean 3.46; P=.02). No differences in communication ratings based on specialty or years in training were detected. Residents' communication was rated higher for angry cases versus sad cases (mean 3.69 vs mean 3.58; P=.01). Less than half of all residents (27/62, 44%) reported prior experience with disclosing medical harm to patients; experience differed significantly among specialties (P<.001) and was lowest for pathology (1/17, 6%). CONCLUSIONS: Residents at all training levels can potentially improve error disclosure skills with VCA practice and feedback. Error disclosure curricula should prepare residents for responding to various patient affects. Simulated error disclosure may particularly benefit trainees in diagnostic specialties, such as pathology, with infrequent real-life error disclosure practice opportunities. Future research should examine the effectiveness, feasibility, and acceptability of VCA within a longitudinal error disclosure curriculum.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».