ReviewFrontiers in psychiatry2018
e-Addictology: An Overview of New Technologies for Assessing and Intervening in Addictive Behaviors.
Review in Frontiers in psychiatry, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 3 of them syntheses that pooled 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.
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.
Who cites it
61 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Ethical challenges in EEG neurofeedback: a systematic review of gaps, risks, and responsibilities.BMC medical ethics · 2026Pooled it
- The Application of AI to Ecological Momentary Assessment Data in Suicide Research: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Virtual Reality (VR) in Assessment and Treatment of Addictive Disorders: A Systematic Review.Frontiers in neuroscience · 2019Pooled it
- Reducing gambling harm through digital self-help intervention: a pilot study in mild to moderate gambling disorder.Harm reduction journal · 2026Trial
- The Effect of Aversive Therapy Using Virtual Reality on Craving, Depression, and Self-Efficacy: A Pilot Study in Patients Under Methadone Maintenance Treatment.Brain and behavior · 2025Trial
- Feasibility of online group schema therapy: A preliminary study with therapists in training for future application in borderline personality disorder.Internet interventions · 2026Article
- Immersive Virtual Reality-Supported Cognitive-Behavioral Therapy for Patients With Mild to Borderline Intellectual Disabilities and Substance Use Disorders: Two Exploratory Studies.JMIR XR and spatial computing · 2026Article
- Conceptualisation of Digital Wellbeing Associated with Generative Artificial Intelligence from the Perspective of University Students.European journal of investigation in health, psychology and education · 2025Article
- Digital Psychosocial Interventions Tailored for People in Opioid Use Disorder Treatment: Scoping Review.Journal of medical Internet research · 2025Article
- Exploring the Ethical Challenges of Conversational AI in Mental Health Care: Scoping Review.JMIR mental health · 2025Article
- Relationship between attentional bias and psychological craving in methamphetamine use disorder.Frontiers in public health · 2025Article
- Fusion Model Using Resting Neurophysiological Data to Help Mass Screening of Methamphetamine Use Disorder.IEEE journal of translational engineering in health and medicine · 2025Article
- Ecological Momentary Assessment of Mental Health Problems Among University Students: Data Quality Evaluation Study.Journal of medical Internet research · 2024Article
- Monitoring Substance Use with Fitbit Biosignals: A Case Study on Training Deep Learning Models Using Ecological Momentary Assessments and Passive Sensing.AI (Basel, Switzerland) · 2024Article
- Acceptability of "DIDE", a mobile application designed at facilitating care adherence of patients with substance use disorder.Addiction science & clinical practice · 2024Article
- Machine minds: Artificial intelligence in psychiatry.Industrial psychiatry journal · 2024Article
- Acceptability and Perceived Utility of Virtual Reality Among People Who Are Incarcerated Who Use Drugs.Journal of correctional health care : the official journal of the National Commission on Correctional Health Care · 2024Article
- Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment Study.JMIR research protocols · 2024Article
- Digital interventions targeting excessive substance use and substance use disorders: a comprehensive and systematic scoping review and bibliometric analysis.Frontiers in psychiatry · 2024Article
- Using machine learning algorithms and techniques for defining the impact of affective temperament types, content search and activities on the internet on the development of problematic internet use in adolescents' population.Frontiers in public health · 2024Article
1 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNew 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.
objectiveThese 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.
methodUsing 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.
resultsWe 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.
conclusionThis 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.
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Identifiers
What OpenQuestion holds
Registered trials
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.