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As concerns with work or other aspects of life mount, individuals may look to old habits and outlets for relief, which could lead to substance addiction relapse. Also, going into environments where substances are accessible, not getting adequate sleep, having difficult mental health conditions, and socializing with family or friends who use substances can all invite substance addiction relapse. A lack of support for maintaining sobriety is also a relapse factor.
While individuals may face multiple challenges to maintaining sobriety, supports to help prevent addiction relapse are available. Structured group sessions, positive community involvement, eating right, and getting exercise can all make a difference. Artificial intelligence (AI) can also be used to help prevent substance addiction relapse.
AI has applications in healthcare, both as initiated by an individual for tracking health, signaling warning signs, and more, and by healthcare providers for a variety of uses.
For years, AI has been impacting healthcare. A 2024 PubMed Central article, in referencing ScienceDirect information about AI use in healthcare from 2011-2022, reports that “AI-based tools are increasingly being utilized in the field of healthcare to improve patient outcomes by promoting precision medicine, streamlining service delivery processes, and enhancing the efficiency and quality of medical research.”
Another example of AI in healthcare is predictive analytics, with applications including risk forecasting, patient care planning, and optimizing scheduling to provide more efficient care.
As reported in the PubMed article, “The potential applications of AI in the context of addiction may be studied under four domains: identification, management, relapse prevention, and prognostication.”
One consideration in the use of AI by healthcare providers is protecting sensitive data. If AI is used for healthcare support, it is important that providers and those receiving care are aware of the AI use, including how AI data is being used and interpreted.
According to a 2024 Journal of Medical Internet Research article presented by the National Library of Medicine, “the collection and processing of sensitive patient data, along with tasks such as model training, model building, and implementing generative AI systems, present potential security and privacy risks.”
A Cureus article, also from 2024 and presented by the National Library of Medicine, includes, “Ethical considerations permeate every aspect of the development, implementation, and utilization of AI and ML [machine learning] in health care. From safeguarding patient privacy and ensuring data security to mitigating algorithmic biases and promoting transparency, ethical principles serve as the cornerstone of responsible AI adoption in healthcare.”
The early warning signs of substance addiction relapse may be hard to identify, but there are machine learning models that analyze patterns over time, providing data that can be used to identify signs of potential relapse. Corrections can then be implemented to help prevent relapse from occurring.
AI can interpret an individual’s sleep and activity from wearables, mood shifts presented in journaling or messaging, and treatment program changes. AI can also pick up on physiological signals like heart rate variability that can factor into an approach to relapse prevention.
AI’s ability to identify specific data, quickly compute, and handle vast amounts of information can all be helpful in healthcare contexts.
One powerful way AI can be used is to alert a doctor or team of early warning signs of relapse, which can help lead to the creation and application of a care plan. Also, AI can be used to personalize long‑term relapse prevention plans, with AI identifying individual patterns that can inform structures for sobriety.
AI can also be used to provide continuous monitoring.
The powerful benefits of AI in supporting relapse prevention do not equate to AI being infallible or limitless in healthcare.
AI cannot understand emotional nuance the way humans do. AI can provide data, but not the human-to-human connections that can influence healthcare, such as a caregiver’s emotional understanding. Artificial intelligence is not able to replace human-directed therapy, community interactions, or lived experience that can influence healthcare plans.
There are also limits relative to AI’s accuracy. False positives and false negatives derived from AI processing can create confusion or anxiety in healthcare settings.
Diagnosis, treatment adjustments such as medicine and dosage changes, human-to-human therapy, and response to nuanced non-verbal communication are all functions belonging to professional caregivers and have not been replaced by AI technologies and capabilities. Still, combining technology with human empathy and understanding can have positive impacts on substance addiction treatment, including recovery prevention efforts.
Jackson House offers substance addiction treatment, offering evidence-based and individualized care. Our team utilizes multiple modalities in providing care and gives attention to skills and tools for maintaining long-term sobriety.
Before individuals complete their treatment programs, we give attention to them having safe residency after they leave the center, a plan for handling stress, and a support system. We also keep in contact with individuals during the first 60 days following at-center treatment.
Each of these is a way that we can help protect against relapse, and another is by offering alumni group services. Our alumni community meets regularly and offers connection as a means to support recovery.
We offer professional treatment for substance addiction in San Diego. Contact us for compassionate substance use treatment from trained professionals. We offer care for a variety of substance addictions, with treatment including tools to support long-term recovery.