Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Mental Health

Date Submitted: Feb 28, 2018
Open Peer Review Period: Feb 28, 2018 - Aug 2, 2018
Date Accepted: Sep 14, 2018
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study

Bourla A, Ferreri F, Ogorzelec L, Peretti CS, Guinchard C, Mouchabac S

Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study

JMIR Ment Health 2018;5(4):e10240

DOI: 10.2196/10240

PMID: 30552086

PMCID: 6315247

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study

  • Alexis Bourla; 
  • Florian Ferreri; 
  • Laetitia Ogorzelec; 
  • Charles-Siegfried Peretti; 
  • Christian Guinchard; 
  • Stephane Mouchabac

Background:

Recent discoveries in the fields of machine learning (ML), Ecological Momentary Assessment (EMA), computerized adaptive testing (CAT), digital phenotype, imaging, and biomarkers have brought about a new paradigm shift in medicine.

Objective:

The aim of this study was to explore psychiatrists’ perspectives on this paradigm through the prism of new clinical decision support systems (CDSSs). Our primary objective was to assess the acceptability of these new technologies. Our secondary objective was to characterize the factors affecting their acceptability.

Methods:

A sample of psychiatrists was recruited through a mailing list. Respondents completed a Web-based survey. A quantitative study with an original form of assessment involving the screenplay method was implemented involving 3 scenarios, each featuring 1 of the 3 support systems, namely, EMA and CAT, biosensors comprising a connected wristband-based digital phenotype, and an ML-based blood test or magnetic resonance imaging (MRI). We investigated 4 acceptability domains based on International Organization for Standardization and Nielsen models (usefulness, usability, reliability, and risk).

Results:

We recorded 515 observations. Regarding our primary objective, overall acceptability was moderate. MRI coupled with ML was considered to be the most useful system, and the connected wristband was considered the least. All the systems were described as risky (410/515, 79.6%). Regarding our secondary objective, acceptability was strongly influenced by socioepidemiological variables (professional culture), such as gender, age, and theoretical approach.

Conclusions:

This is the first study to assess psychiatrists’ views on new CDSSs. Data revealed moderate acceptability, but our analysis shows that this is more the result of the lack of knowledge about these new technologies rather than a strong rejection. Furthermore, we found strong correspondences between acceptability profiles and professional culture profiles. Many medical, forensics, and ethical issues were raised, including therapeutic relationship, data security, data storage, and privacy risk. It is essential for psychiatrists to receive training and become involved in the development of new technologies.


 Citation

Please cite as:

Bourla A, Ferreri F, Ogorzelec L, Peretti CS, Guinchard C, Mouchabac S

Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study

JMIR Ment Health 2018;5(4):e10240

DOI: 10.2196/10240

PMID: 30552086

PMCID: 6315247

Per the author's request the PDF is not available.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.