AIMC Topic: Substance-Related Disorders

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Flexibility and resilience in equity-centered research: lessons learned conducting a randomized controlled trial of a family-based substance use prevention program for American Indian families.

Frontiers in public health
Meaningful and effective community engagement lies at the core of equity-centered research, which is a powerful tool for addressing health disparities in American Indian (AI) communities. It is essential for centering Indigenous wisdom as a source of...

Artificial Intelligence-driven and technological innovations in the diagnosis and management of substance use disorders.

International review of psychiatry (Abingdon, England)
Substance Use Disorders (SUD) lead to a collection of health challenges such as overdoses and clinical diseases. Populations that are vulnerable and lack straightforward treatment access are vulnerable to significant economic and social effects linke...

The metabolic clock of ketamine abuse in rats by a machine learning model.

Scientific reports
Ketamine has recently become an anesthetic drug used in human and veterinary clinical medicine for illicit abuse worldwide, but the detection of illicit abuse and inference of time intervals following ketamine abuse are challenging issues in forensic...

Improving treatment completion for young adults with substance use disorder: Machine learning-based prediction algorithms.

Journal of psychiatric research
Substance use disorder (SUD) treatment completion was intertwined with various factors. However, few studies have explored the intersections of psychosocial and system-related factors with SUD treatment completion, particularly for individuals receiv...

Evaluating generative AI responses to real-world drug-related questions.

Psychiatry research
Generative Artificial Intelligence (AI) systems such as OpenAI's ChatGPT, capable of an unprecedented ability to generate human-like text and converse in real time, hold potential for large-scale deployment in clinical settings such as substance use ...

Exploring predictors of substance use disorder treatment engagement with machine learning: The impact of social determinants of health in the therapeutic landscape.

Journal of substance use and addiction treatment
BACKGROUND: Improved knowledge of factors that influence treatment engagement could help treatment providers and systems better engage patients. The present study used machine learning to explore associations between individual- and neighborhood-leve...

IUPHAR Review: New strategies for medications to treat substance use disorders.

Pharmacological research
Substance use disorders (SUDs) and drug overdose are a public health emergency and safe and effective treatments are urgently needed. Developing new medications to treat them is expensive, time-consuming, and the probability of a compound progressing...

Comparison of hepatitis B and SARS-CoV2 vaccination rates in people who attended Drugs and Addiction Centres.

Frontiers in public health
BACKGROUND AND AIMS: Persons with substance use disorder are at increased risk for hepatitis B virus (HBV) infection. Although most of them are attached to social health centers, the vaccination rate in this group is low. In this context, we designed...

A relational agent for treating substance use in adults: Protocol for a randomized controlled trial with a psychoeducational comparator.

Contemporary clinical trials
BACKGROUND: Substance use disorders (SUDs) are prevalent and compromise health and wellbeing. Scalable solutions, such as digital therapeutics, may offer a population-based strategy for addressing SUDs. Two formative studies supported the feasibility...