Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

In BJPsych open

BACKGROUND : Recently, artificial intelligence-powered devices have been put forward as potentially powerful tools for the improvement of mental healthcare. An important question is how these devices impact the physician-patient interaction.

AIMS : Aifred is an artificial intelligence-powered clinical decision support system (CDSS) for the treatment of major depression. Here, we explore the use of a simulation centre environment in evaluating the usability of Aifred, particularly its impact on the physician-patient interaction.

METHOD : Twenty psychiatry and family medicine attending staff and residents were recruited to complete a 2.5-h study at a clinical interaction simulation centre with standardised patients. Each physician had the option of using the CDSS to inform their treatment choice in three 10-min clinical scenarios with standardised patients portraying mild, moderate and severe episodes of major depression. Feasibility and acceptability data were collected through self-report questionnaires, scenario observations, interviews and standardised patient feedback.

RESULTS : All 20 participants completed the study. Initial results indicate that the tool was acceptable to clinicians and feasible for use during clinical encounters. Clinicians indicated a willingness to use the tool in real clinical practice, a significant degree of trust in the system's predictions to assist with treatment selection, and reported that the tool helped increase patient understanding of and trust in treatment. The simulation environment allowed for the evaluation of the tool's impact on the physician-patient interaction.

CONCLUSIONS : The simulation centre allowed for direct observations of clinician use and impact of the tool on the clinician-patient interaction before clinical studies. It may therefore offer a useful and important environment in the early testing of new technological tools. The present results will inform further tool development and clinician training materials.

Benrimoh David, Tanguay-Sela Myriam, Perlman Kelly, Israel Sonia, Mehltretter Joseph, Armstrong Caitrin, Fratila Robert, Parikh Sagar V, Karp Jordan F, Heller Katherine, Vahia Ipsit V, Blumberger Daniel M, Karama Sherif, Vigod Simone N, Myhr Gail, Martins Ruben, Rollins Colleen, Popescu Christina, Lundrigan Eryn, Snook Emily, Wakid Marina, Williams Jérôme, Soufi Ghassen, Perez Tamara, Tunteng Jingla-Fri, Rosenfeld Katherine, Miresco Marc, Turecki Gustavo, Gomez Cardona Liliana, Linnaranta Outi, Margolese Howard C


Primary care, artificial intelligence, depressive disorders, out-patient treatment, simulation centre