Innovative App Aims to Predict Opioid Addiction Relapse Risk

Understanding Opioids and Their Impact

Opioids are a class of drugs that either originate from opium or mimic its effects. These substances have various medical applications, such as pain management, anesthesia, and treating diarrhea. Common opioids include morphine, codeine, heroin, oxycodone (known as Percocet), and fentanyl. Due to their ability to significantly elevate dopamine levels, opioids can induce intense feelings of euphoria, making them susceptible to misuse. In 2018, over ten million Americans aged 12 and older misused opioids, highlighting the severity of the ongoing opioid crisis.

The Risks of Opioid Misuse

Misuse of opioids poses serious dangers, as even small quantities can lead to overdose. Furthermore, opioids are highly addictive, with studies indicating that 8 to 12 percent of individuals who misuse them develop an opioid use disorder. Recovery from opioid addiction is challenging, and existing research on predicting relapse among recovering individuals is limited.

Development of a Predictive App

To address the need for better prediction of opioid relapse, a new app is in development. This application features a simulated betting game designed to assess risk-taking behavior. Players choose between accepting a smaller reward or gambling for a larger one, with a high beta-score indicating a propensity for risk-taking.

Study and Findings

The app was tested with 70 men and women enrolled in an opioid addiction treatment program at NYC Health + Hospitals/Bellevue. Participants engaged with the game regularly over seven months during their clinic visits. A control group of 50 patients who had never been addicted to opioids also participated in the game for the same duration. The results were published in the Journal of the American Medical Association Psychiatry.

The study revealed that patients exhibiting significant increases in beta scores were up to 85 percent more likely to reuse opioids. In contrast, individuals with stable beta scores showed a lower likelihood of relapse.

Conclusion and Future Research

These findings indicate that the app could serve as a valuable tool for predicting opioid addiction relapse. While further research is necessary to validate the app’s effectiveness, it lays the groundwork for the advancement of technology aimed at supporting individuals in recovery.

References

Konova, A. B., Lopez-Guzman, S., & Urmanche, A. (2019). Computational Markers of Risky Decision-making for Identification of Temporal Windows of Vulnerability to Opioid Use in a Real-world Clinical Setting. JAMA Psychiatry. doi: 10.1001/jamapsychiatry.2019.4013

Computer game may help to predict reuse of opioids. (2019, December 8). Retrieved December 10, 2019, from https://www.eurekalert.org/pub_releases/2019-12/nlh-cgm120319.php

National Institute on Drug Abuse. (2019, January 22). Opioid Overdose Crisis. Retrieved December 10, 2019, from https://www.drugabuse.gov/drugs-abuse/opioids/opioid-overdose-crisis

Opioid Crisis Fast Facts. (2019, December 4). Retrieved December 10, 2019, from https://www.cnn.com/2017/09/18/health/opioid-crisis-fast-facts/index.html

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