What topics does this cannabis study cover?

This study covers research on: Anxiety.

Where was this research published?

Published in Journal of addictive diseases on February 4, 2026.

AI and Personalized Therapy: A New Hope for Cannabis Addiction

Tailored psychotherapy and AI-enhanced contingency management for co-occurring disorders in cannabis use disorder: a systematic review.

Journal of addictive diseases • February 4, 2026 • Review • Moderately Relevant

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AI Summary

Cannabis use disorder (CUD) is often complicated by co-occurring mental health conditions like depression, PTSD, anxiety, and ADHD. This systematic review reveals promising approaches to treating these complex cases by integrating personalized psychotherapy with cutting-edge technology. Cognitive-behavioral therapies showed particular effectiveness in reducing psychiatric symptoms and cannabis use, especially for patients with depression and post-traumatic stress disorder.

The research highlights an innovative approach using artificial intelligence (AI) to enhance treatment outcomes. Machine learning algorithms can now predict relapse risks and optimize behavioral interventions through contingency management techniques. By analyzing smartphone and sensor data, these AI-driven methods can improve treatment attendance and verify patient abstinence with unprecedented precision. Personalized reward systems powered by AI show potential to make addiction treatment more adaptive and responsive to individual patient needs.

Most notably, the study suggests that combining tailored psychotherapy with AI-enhanced behavioral reinforcement could significantly improve recovery outcomes for individuals struggling with cannabis use disorder. The integrated approach addresses both substance use and underlying mental health challenges, offering a more holistic treatment strategy that goes beyond traditional addiction interventions. This research represents a critical step toward more personalized, technology-assisted addiction treatment.

📄 Original Abstract

Cannabis use disorder (CUD) commonly co-occurs with depression, post-traumatic stress disorder (PTSD), anxiety, and attention-deficit/hyperactivity disorder (ADHD), resulting in poorer outcomes and underscoring the need for tailored interventions. Contingency management (CM) is one of the most effective behavioral treatments for substance use disorders, and emerging applications of artificial intelligence (AI) may enhance CM by predicting relapse risk and personalizing incentives. This review evaluates evidence on integrated interventions for CUD with co-occurring disorders and the developing role of AI-enhanced CM. A systematic search of PubMed, PsycINFO, Embase, and Web of Science (through October 2025) identified clinical studies and systematic reviews on tailored interventions for CUD with depression, PTSD, anxiety, or ADHD, as well as research on AI-driven CM. Data were extracted on study design, interventions, and outcomes. Thirty-eight studies met inclusion criteria. Integrated cognitive-behavioral therapies improved psychiatric symptoms and reduced cannabis use, particularly in depression and PTSD. Pharmacotherapies showed inconsistent benefits, while ADHD-focused behavioral and stimulant-based approaches demonstrated promising reductions in cannabis use. AI applications such as machine-learning prediction of relapse using smartphone/sensor data, remote CM delivery, and reinforcement-learning-based incentive optimization-improved attendance, abstinence verification, and reward efficiency. Integrated psychosocial approaches and AI-augmented CM offer complementary pathways for improving outcomes in individuals with CUD and co-occurring disorders. Combining personalized psychotherapy with adaptive, technology-assisted reinforcement may strengthen treatment efficacy. This review examines treatments for people with cannabis use disorder who also have depression, post-traumatic stress disorder (PTSD), anxiety, or ADHD. It also evaluates how artificial intelligence can strengthen contingency management by predicting relapse and improving rewards. Combining tailored psychotherapy with AI-enhanced behavioral reinforcement may improve abstinence, symptom reduction, and overall recovery outcomes.

Paper Type

📚 Review

Publication

Journal: Journal of addictive diseases
Published: February 4, 2026
PMID: 41640005
DOI: 10.1080/10550887.2026.2616726

Authors (3)

Sidharth Mishra Department of Psychiatry, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, India.
Sayali Mishra Department of Psychiatry, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, India.
Sibanarayan Rath Research and Development Department, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, India.