Evidence map›Paper›PMID 33403948›Full record

ArticleBJPsych open2021

Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician-patient interaction.

David Benrimoh, Myriam Tanguay-Sela, Kelly Perlman, Sonia Israel, Joseph Mehltretter, Caitrin Armstrong, Robert Fratila, Sagar V Parikh, Jordan F Karp, Katherine Heller and 21 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BJPsych open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

31 authors.

David BenrimohDepartment of Psychiatry, McGill University, Canada; Aifred Heath Inc., Montreal, Canada; and Faculty of Medicine, McGill University, Canada.ORCID https://orcid.org/0000-0002-1452-4791
Myriam Tanguay-SelaMontreal Neurological Institute, McGill University, Canada; and Aifred Health Inc., Montreal, Canada.ORCID https://orcid.org/0000-0002-8056-1697
Kelly PerlmanDouglas Mental Health University Institute, Montreal, Canada; and Aifred Health Inc., Montreal, Canada.ORCID https://orcid.org/0000-0002-2716-0712
Sonia IsraelAifred Health Inc., Montreal, Canada.
Joseph MehltretterDepartment of Computer Science, University of Southern California, Los Angeles, USA; and Aifred Health Inc., Montreal, Canada.
Caitrin ArmstrongSchool of Computer Science, McGill University, Canada; and Aifred Health Inc., Montreal, Canada.
Robert FratilaAifred Health Inc., Montreal, Canada.
Sagar V ParikhDepartment of Psychiatry, University of Michigan, USA.
Jordan F KarpDepartment of Psychiatry, University of Pittsburgh, USA.
Katherine HellerDepartment of Statistical Science, Duke University, USA.
Ipsit V VahiaDepartment of Psychiatry, McLean Hospital/Harvard University, USA.
Daniel M BlumbergerSchool of Psychiatry, University of Toronto, Canada.ORCID https://orcid.org/0000-0002-8422-5818
Sherif KaramaDepartment of Psychiatry, McGill University, Canada.
Simone N VigodDepartment of Psychiatry, University of Toronto, Canada.ORCID https://orcid.org/0000-0002-2736-9639
Gail MyhrDepartment of Psychiatry, McGill University, Canada.
Ruben MartinsDouglas Mental Health University Institute, Montreal, Canada; and Department of Psychiatry, McGill University, Canada.
Colleen RollinsDepartment of Psychiatry, University of Cambridge, UK; and Aifred Health Inc., Montreal, Canada.ORCID https://orcid.org/0000-0002-0291-0038
Christina PopescuDouglas Mental Health University Institute, Montreal, Canada; and Aifred Health Inc., Montreal, Canada.ORCID https://orcid.org/0000-0003-1738-4680
Eryn LundriganDepartment of Anatomy and Cell Biology, McGill University, Canada.ORCID https://orcid.org/0000-0001-5896-9752
Emily SnookFaculty of Medicine, University of Toronto, Canada.
Marina WakidDouglas Mental Health University Institute, Montreal, Canada.
Jérôme WilliamsFaculty of Medicine, McGill University, Canada.ORCID https://orcid.org/0000-0002-8871-2509
Ghassen SoufiFaculty of Medicine, McGill University, Canada.
Tamara PerezDepartment of Experimental Medicine, McGill University, Canada.ORCID https://orcid.org/0000-0002-9892-3043
Jingla-Fri TuntengSchool of Physical and Occupational Therapy, McGill University, Canada.
Katherine RosenfeldDepartment of Psychology, McGill University, Canada.
Marc MirescoDepartment of Psychiatry, McGill University, Canada.
Gustavo TureckiDouglas Mental Health University Institute, Montreal, Canada; and Department of Psychiatry, McGill University, Canada.
Liliana Gomez CardonaDouglas Mental Health University Institute, Montreal, Canada; and Department of Psychiatry, McGill University, Canada.
Outi LinnarantaDouglas Mental Health University Institute, Montreal, Canada; and Department of Psychiatry, McGill University, Canada.
Howard C MargoleseDepartment of Psychiatry, McGill University, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecently, 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.

aimsAifred 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.

methodTwenty 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.

resultsAll 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.

conclusionsThe 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.

Indexed as

artificial intelligencedepressive disordersout-patient treatmentPrimary caresimulation centre

Identifiers

PMID33403948
PMCPMC8058891

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.