Simulated Conversations With Virtual Humans to Improve Patient-Provider Communication and Reduce Unnecessary Prescriptions for Antibiotics: A Repeated Measure Pilot Study
Notice bibliographique
Résumé
Background: Despite clear evidence that antibiotics do not cure viral infections, the problem of unnecessary prescribing of antibiotics in ambulatory care persists, and in some cases, prescribing patterns have increased. The overuse of antibiotics for treating viral infections has created numerous economic and clinical consequences including increased medical costs due to unnecessary hospitalizations, antibiotic resistance, disruption of gut bacteria, and obesity. Recent research has underscored the importance of collaborative patient-provider communication as a means to reduce the high rates of unnecessary prescriptions for antibiotics. However, most patients and providers do not feel prepared to engage in such challenging conversations. Objectives: The aim of this pilot study was to assess the ability of a brief 15-min simulated role-play conversation with virtual humans to serve as a preliminary step to help health care providers and patients practice, and learn how to engage in effective conversations about antibiotics overuse. Methods: A total of 69 participants (35 providers and 34 patients) completed the simulation once in one sitting. A pre-post repeated measures design was used to assess changes in patients’ and providers’ self-reported communication behaviors, activation, and preparedness, intention, and confidence to effectively communicate in the patient-provider encounter. Changes in patients’ knowledge and beliefs regarding antibiotic use were also evaluated. Results: Patients experienced a short-term positive improvement in beliefs about appropriate antibiotic use for infection (F1,30=14.10, P=.001). Knowledge scores regarding the correct uses of antibiotics improved immediately postsimulation, but decreased at the 1-month follow-up (F1,30=31.16, P.10) Patients with lower levels of activation exhibited positive, short-term benefits in increased intent and confidence to discuss their needs and ask questions in the clinic visit, positive attitudes regarding participation in SDM with their provider, and accurate beliefs about the use of antibiotics (P<.10). The results also suggest small immediate gains in providers’ attitudes about SDM (mean change 0.20; F1,33= 8.03, P=.01). Conclusions: This pilot study provided preliminary evidence on the efficacy of the use of simulated conversations with virtual humans as a tool to improve patient-provider communication (ie, through increasing patient confidence to actively participate in the visit and physician attitudes about SDM) for engaging in conversations about antibiotic use. Future research should explore if repeated opportunities to use the 15-min simulation as well as providing users with several different conversations to practice with would result in sustained improvements in antibiotics beliefs and knowledge and communication behaviors over time. The results of this pilot study offered several opportunities to improve on the simulation in order to bolster communication skills and knowledge retention.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 | 0,000 |
| 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 ».