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

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 psychiatr...

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Autores principales: Bourla, Alexis, Ferreri, Florian, Ogorzelec, Laetitia, Peretti, Charles-Siegfried, Guinchard, Christian, Mouchabac, Stephane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6315247/
https://www.ncbi.nlm.nih.gov/pubmed/30552086
http://dx.doi.org/10.2196/10240
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author Bourla, Alexis
Ferreri, Florian
Ogorzelec, Laetitia
Peretti, Charles-Siegfried
Guinchard, Christian
Mouchabac, Stephane
author_facet Bourla, Alexis
Ferreri, Florian
Ogorzelec, Laetitia
Peretti, Charles-Siegfried
Guinchard, Christian
Mouchabac, Stephane
author_sort Bourla, Alexis
collection PubMed
description 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.
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spelling pubmed-63152472019-01-28 Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study Bourla, Alexis Ferreri, Florian Ogorzelec, Laetitia Peretti, Charles-Siegfried Guinchard, Christian Mouchabac, Stephane JMIR Ment Health Original Paper 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. JMIR Publications 2018-12-14 /pmc/articles/PMC6315247/ /pubmed/30552086 http://dx.doi.org/10.2196/10240 Text en ©Alexis Bourla, Florian Ferreri, Laetitia Ogorzelec, Charles-Siegfried Peretti, Christian Guinchard, Stephane Mouchabac. Originally published in JMIR Mental Health (http://mental.jmir.org), 14.12.2018. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Bourla, Alexis
Ferreri, Florian
Ogorzelec, Laetitia
Peretti, Charles-Siegfried
Guinchard, Christian
Mouchabac, Stephane
Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study
title Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study
title_full Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study
title_fullStr Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study
title_full_unstemmed Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study
title_short Psychiatrists' Attitudes Toward Disruptive New Technologies: Mixed-Methods Study
title_sort psychiatrists' attitudes toward disruptive new technologies: mixed-methods study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6315247/
https://www.ncbi.nlm.nih.gov/pubmed/30552086
http://dx.doi.org/10.2196/10240
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