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Front. Psychiatry | doi: 10.3389/fpsyt.2018.00051

e-addictology: an overview of new technologies for assessing and intervening in addictive behaviors

  • 1Adult Psychiatry and Medical Psychology, Université Pierre et Marie Curie, France
  • 2Addiction Research and Treatment Center, Hôpital Paul Brousse, France

Background: New technologies can profoundly change the way we understand psychiatric pathologies and addictive disorders. New concepts are emerging with the development of more accurate means of collecting live data, computerized questionnaires, and the use of passive data. Digital phenotyping, a paradigmatic example, refers to the use of computerized measurement tools to capture the characteristics of different psychiatric disorders. Similarly, machine learning a form of artificial intelligence can improve the classification of patients based on patterns that clinicians have not always considered in the past. Remote or automated interventions (web-based or smartphone-based apps), as well as virtual reality and neurofeedback, are already available or under development.

Objective: These recent changes have the potential to disrupt practices, as well as practitioners’ beliefs, ethics and representations, and may even call into question their professional culture. However, the impact of new technologies on health professionals’ practice in addictive disorder care has yet to be determined. In the present paper, we therefore present an overview of new technology in the field of addiction medicine.

Method: Using the keywords [e-health], [m-health], [computer], [mobile], [smartphone], [wearable], [digital], [machine learning], [ecological momentary assessment], [biofeedback] and [virtual reality], we searched the PubMed database for the most representative articles in the field of assessment and interventions in substance use disorders.

Results: We screened 595 abstracts and analyzed 92 articles, dividing them into seven categories: e-health program and web-based interventions, machine learning, computerized adaptive testing, wearable devices and digital phenotyping, ecological momentary assessment, biofeedback, and virtual reality.

Conclusions: This overview shows that new technologies can improve assessment and interventions in the field of addictive disorders. The precise role of connected devices, artificial intelligence and remote monitoring remains to be defined. If they are to be used effectively, these tools must be explained and adapted to the different profiles of physicians and patients. The involvement of patients, caregivers and other health professionals is essential to their design and assessment.

Keywords: Addictive Disorders, Digital phenotyping, Ecological momentary assessment (EMA), virtual reality, wearable devices, machine learning

Received: 08 Jan 2018; Accepted: 06 Feb 2018.

Edited by:

Liana Fattore, Consiglio Nazionale Delle Ricerche (CNR), Italy

Reviewed by:

Antoni Gual, Hospital Clínic de Barcelona, Spain
Giuseppe Carrà, Università degli studi di Milano Bicocca, Italy  

Copyright: © 2018 Ferreri, Bourla, Mouchabac and Karila. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: MD. Alexis Bourla, Université Pierre et Marie Curie, Adult Psychiatry and Medical Psychology, Paris, 75012, France,