BRIEF RESEARCH REPORT article

Front. Digit. Health

Sec. Digital Mental Health

Volume 7 - 2025 | doi: 10.3389/fdgth.2025.1584716

This article is part of the Research TopicDigital Medicine in Psychiatry and Neurology - Chances and Challenges for Mobile Scalable Monitoring and InterventionView all 4 articles

Detecting Benzodiazepine Use Through Induced Eye Convergence Inability With A Smartphone App: A Proof-of-concept study

Provisionally accepted
Kiki KuijpersKiki Kuijpers1Markku D HämäläinenMarkku D Hämäläinen2Andreas ZetterströmAndreas Zetterström2Maria WinkvistMaria Winkvist2Marieke NiestersMarieke Niesters1,3Monique Van VelzenMonique Van Velzen1Fred NybergFred Nyberg4Albert DahanAlbert Dahan3,5,6Karl AnderssonKarl Andersson7,8*
  • 1Leiden University Medical Center (LUMC), Leiden, Netherlands
  • 2Kontigo Care AB, Uppsala, Uppsala, Sweden
  • 3Centre for Human Drug Research, Leiden, Netherlands
  • 4Uppsala University, Uppsala, Uppsala, Sweden
  • 5MedI Consultancy Group, Amsterdam, Netherlands
  • 6Outcomes Research Consortium,, Huston TX, United States
  • 7Skillsta Teknik, Design och Kvalitet AB, Vänge, Sweden
  • 8University of Skövde, Skövde, Sweden

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Background: Benzodiazepines (BZD) are readily available potent drugs which act as central depressants. These drugs are widely used, misused, and abused. For patients with BZD use disorder, the traditional sobriety monitoring method is periodic urine tests.Methods: The utility of eye-scanning data related to non-convergence (the ability to cross eyes) collected using smartphones with the Previct Drugs app before and after ingestion of the BZD lorazepam for detecting BZD-driven effects were evaluated using data from 12 individuals from a historic clinical study (NCT05731999). Data of 12 individuals from a recently published clinical study (NCT05731999) was used to detect BZD-driven effects. Using a novel metric that represents the change in distance between irises when converging eyes, either in absolute terms (NCdiff) or as individualized (NCdiffInd), classifiers were built using logistic regression.Results: The ability to converge eyes is a strongly individual and an acquired skill which is impaired after ingesting lorazepam. The maximum NCdiff for one BZD sober individual may be smaller than the impaired NCdiff for another individual. Using NCDiff as measured in sober condition after about 1 week of regular eye-scanning as the individual baseline to form NCdiffInd produced a highly functional classifier with AUC = 0.88, superior to a classifier based on NCdiff with AUC =0.79. Conclusions: The loss of eye convergence induced by lorazepam is continuous, individual, and can be partial. Smartphone based eye-scanning technology combined with a classifier adapted to the ability of eye convergence of individuals shows promising performance in detecting ingestion of lorazepam.

Keywords: substance use disorder, Pupillometry, Eye convergence, Benzodiazepines, smartphone

Received: 27 Feb 2025; Accepted: 05 May 2025.

Copyright: © 2025 Kuijpers, Hämäläinen, Zetterström, Winkvist, Niesters, Van Velzen, Nyberg, Dahan and Andersson. 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) or licensor 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: Karl Andersson, Skillsta Teknik, Design och Kvalitet AB, Vänge, Sweden

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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