This study explored whether changes in a person's voice could help identify opioid use in patients with opioid use disorder (OUD). Current methods for determining whether a patient is intoxicated or in withdrawal often rely on self-reporting and clinical judgment, which can be subjective and inconsistent. Drug tests are logistically challenging to administer and can be costly with repeated use. The project investigated whether physiological changes associated with opioid use could be detected through speech analysis technology. Researchers evaluated whether machine learning methods could identify voice patterns associated with opioid intoxication or withdrawal. The primary goal of the study was to assess the accuracy of voice-based biomarkers in identifying opioid use. The study also explored relationships between opioid use and specific speech characteristics.
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
Sensitivity and Specificity
Timeframe: 12 months after the enrollment