Medical Education
Conditions
Keywords
artificial intelligence
Brief summary
This is a prospective, collaborative, mixed-methods study which includes anesthesiology trainees receiving one active intervention - a conversational artificial intelligence (CAI) simulation. The goal is to explore the capability of AI to provide high-fidelity simulations that can ultimately improve how healthcare professionals handle difficult conversations such as disclosing medical errors or mistakes.
Interventions
OTHERConversational Artificial Intelligence Simulations
Use of Conversational Artificial Intelligence Simulations generate medical scenario.
Sponsors
Stanford University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SUPPORTIVE_CARE
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 18 Years
Healthy volunteers
No
Inclusion criteria
* Hospital providers, including nurses, physician assistants, physicians, physician trainees, and other healthcare workers at Lucile Packard Children's Hospital (LPCH) and affiliated facilities who communicate with patients daily will be included
Exclusion criteria
* Participants with reported severe motion sickness * Nausea * Seizure disorder * Currently using chronotropic heart medications, such as β blockers
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Evaluate acceptance of Conversational Artificial Intelligence Simulations using Guided Discussion Interview Question Guide | Before simulation | Guided Discussion Interview Question Guide contains 6 questions focusing 3 areas including Attitudes and Opinions, Perceptions and Summation question. All the questions are open-ended questions. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Evaluation of Conversational Artificial Intelligence Simulations usability via the System Usability Scale (SUS) | Immediately after simulation | Measured with the System Usability Scale (SUS). The scale has 10 items. Scores ranges from 1-5 (1 = strongly disagree and 5 = strongly agree) |
| Evaluation of Conversational Artificial Intelligence Simulations usability via the User Experience Questionnaire (UEQ-S). | Immediately after simulation | UEQ-S, includes eight items (four from the pragmatic scales Efficiency, Perspicuity, Dependability, and four from the hedonic scales Stimulation and Novelty). Scores range from -3 (min) to 3 (max) |
| Evaluation of the reliability of AI quantitative assessment of non-technical performance compared to expert human assessors | immediately after simulation | The Anaesthetist Non-Technical Skills (ANTS) tool previously published by Fletcher et al. translated in French. The ANTS scoring system uses four categories assessing task management, teamworking, situation awareness and decision-making (1 to 4 points by categories). The minimum score is 4 and the maximum 16 |
Outcome results
None listed