Safety vs. Autonomy: When is Guardianship Legally and Ethically Acceptable?

The tension between the values of autonomy and safety have been a major debate topic in the field of medical ethics. This tension applies to debates about guardianship, which is when a court appoints a person to make and supervise personal, day-to-day decisions, including medical decisions, for another person [1]. Guardianship is granted when the supervisee is deemed unable to independently manage their own lives [2]. 

Addiction can greatly impact a person’s ability to make sound, well-informed decisions about their health, finances, and everyday responsibilities [3]. Although substance use by itself does not necessarily mean someone lacks legal capacity, long-term or severe addiction can weaken judgment, memory, impulse control, and risk awareness [3]. When these effects begin to hinder a person’s ability to care for themselves or handle essential obligations, courts may consider whether legal measures, such as guardianship, are appropriate [3]. 

Guardianship is a controversial power because on one hand it helps protect people from themselves, but on the other hand it reduces their autonomy and has a risk for abuse. Courts try to navigate the line between this tension by trying to choose the least restrictive measures that can effectively protect someone, which means they typically will not order absolute guardianship lightly [3]. 

One of the most controversial aspects of guardianship is that it allows one to make medical decisions for another person [1]. Since addiction tends to have a high co-occurrence with psychiatric illnesses, this means that in a scenario of guardianship the guardian can force another person into receiving antipsychotic medications and electroconvulsive therapy [4-5]. Some argue that these restrictive measures can further the stigma around mental illness and addiction, and additionally weaken their ability to develop the competencies needed to re-integrate back into broader society after a mental health crisis [5]. 

But if we got rid of guardianship, what should society do if an addict is a clear danger to themselves? One alternative is involuntary commitment, where an addict is forced into a treatment facility, either short term or long term [6]. This could help protect the addict during a crisis, without needing a guardian to make their decisions long term. However, a problem with this is that once the rehab is completed the patient has a high risk of relapse, with 40–60% of individuals treated for a substance use disorder relapsing at some point [7]. This means that involuntary commitment alone is not effective for everyone long term, meaning further interventions like guardianship might be necessary for some. 

Overall, guardianship in the case of addiction is a contested issue that does not have a clear solution. Our government needs to find a healthy balance between protecting individual liberties while also protecting individual and societal safety. As a last resort, guardianship in some capacity seems to be necessary, but with strong safeguards against abuse and with the goal to make it temporary. 

Designed by: Vedant Patel

Reviewed by: Vedant Patel

References

[1] Moye, J. (2005). Guardianship and Conservatorship. In Evaluating Competencies (Vol. 16, pp. 309–389). Kluwer Academic Publishers. https://doi.org/10.1007/0-306-47922-2_8

[2] Nwakasi, C., & Restorick Roberts, A. (2018). CHALLENGES OF ADULT GUARDIANSHIP. Innovation in Aging, 2(suppl_1), 525–525. https://doi.org/10.1093/geroni/igy023.1940

[3] Casey, R. (2026, March 11). Guardianship and Addiction: What the Courts Consider. Robinson & Casey, PLLC. https://robinsoncasey.com/guardianship-and-addiction-what-the-courts-consider/

[4] Avramut, M. (2024). Mental illness and addiction . EBSCO Information Services, Inc. https://www.ebsco.com/research-starters/health-and-medicine/mental-illness-and-addiction

[5] Salzman, Leslie. (2011). Guardianship for persons with mental illness a legal and appropriate alternative. Saint Louis University Journal of Health Law & Policy, 4(2), 279-330.

[6] NC DHHS: Involuntary Commitments. (n.d.). Www.ncdhhs.gov. https://www.ncdhhs.gov/ivc

[7] Estrellado, N. (2024, July 24). National Statistics on Relapse Rates for Various Addictions - Addiction Group. Addiction Group. https://www.addictiongroup.org/resources/relapse-rates-statistics/

Can AI Predict Relapse Before It Happens?

Addiction is a complex, chronic disorder that can affect individuals for long periods of time. Relapse rates are high with studies showing that 40-60% of individuals relapse within the first year following treatment [2]. Not only does addiction take a toll on the individual and their close friends and family, addiction is an economic burden in regards to healthcare system costs and workforce productivity. The opioid crisis alone has cost the U.S. around $1 trillion between 2001 and 2017 and costs employers an estimated $18 billion annually [1]. One of the greatest challenges in addiction treatment is relapse, which can occur even after periods of progress and stability. The identification of warning signs to allow for early intervention is crucial for effective treatment. Current treatment is limited in that it causes delayed intervention, relies on subjective self-reporting, and is embedded with recall bias [1,2]. When considering how to better treat addiction, finding ways to improve the accuracy of relapse prediction is extremely important. Relapse prediction is the process of recognizing warning signs that a person in recovery may be at risk of relapse and intervening before it happens. 

AI has become a common tool in healthcare, such as with cancer diagnosis, but its potential in early detection of relapse is quite promising. One study shows how a hybrid AI and machine-learning model achieved 99.75% accuracy in identifying risk factors associated with diagnosing Internet addiction [1]. AI can use common patterns in behavior, physiology, and patient history to estimate relapse risk [3]. Through collection of real-time data using phones and wearables (such as smart watches), information on mood, sleep quality, mobility, environment, stress, and other physiological metrics can be continuously monitored [2,4]. Additionally, AI models can detect less obvious warning signs like changes in daily routines, decreased social interaction, and irregular sleep [3]. Making use of these metrics, AI can be used to create individualized risk profiles, detect windows of relapse risk, and send alerts for intervention [5].

With AI’s potential for big data analysis and pattern recognition, real-time predictions can be relayed to clinicians and recovery support systems, allowing them to act proactively [3,4]. This opens up the possibility for anticipatory care models and tailored interventions, such as peer support systems and clinician outreach. Preventing relapse before it occurs allows for reinforcement of healthy coping strategies and behavioral cues that might help establish these supportive routines long-term, decreasing future relapse risk. 

AI models can also deliver personalized interactions that offer psychoeducation, coping strategies, and continuous support especially in times of emergency [1]. The advanced natural language processing capabilities of AI models may be able to address accessibility barriers and biases in traditional mental health care, though concerns persist regarding the accuracy of AI in simulating human-like interactions and the therapeutic relationship [1].

Although AI can be a very effective tool to detect potential relapses, AI alone will not comprehensively tackle addiction. Additionally, with the introduction of AI-based monitoring, there are various ethical and privacy concerns to address. To move forward with using this technology in relapse intervention, we must consider the data privacy risks and concerns about surveillance and potential data misuse [3]. Also, AI models must include data from a wide variety of sociocultural environments to prevent underrepresentation of certain populations [3]. 

AI has the potential to transform addiction care by shifting treatment from reactive to proactive. By utilizing real-time data and pattern recognition, periods of elevated relapse risk can be predicted and timely support can be administered. While there is still a long way to the practical implementation of AI in addiction relapse treatment, this technology is promising to improve long-term recovery outcomes from addiction.

Designed by: Jimin Lee

Reviewed by: Wendy House

References: 

[1] Khakpaki, A., & Sepehri, H. (2025, July 24). Ai in addiction: Harnessing technology for diagnosis, prevention, and recovery: A narrative review. Addiction and Substance Abuse. https://www.probiologists.com/article/ai-in-addiction-harnessing-technology-for-diagnosi s-prevention-and-recovery-a-narrative-review 

[2] Mirian Akujuobi, O., Chuks Azu, J., Uzoigwe, Z., & Nelyn Akunna, O. (2025). Digital Therapeutics and AI-Assisted Monitoring for Relapse Prevention in Substance Use Disorders. Healthcare Studies, 3(1), 21–29. https://doi.org/ 10.58612/hs314 

[3] Suva, M., & Bhatia, G. (2024, August 31). Artificial Intelligence in addiction: Challenges and opportunities. Indian journal of psychological medicine. 

https://pmc.ncbi.nlm.nih.gov/articles/PMC11572328/ 

[4] Barndollar, H. (2025, November 4). Ai could predict when someone is going to relapse on opioids. Governing. 

https://www.governing.com/artificial-intelligence/ai-could-predict-when-someone-is-goin g-to-relapse-on-opioids 

[5] Malhotra, D. K. (2022, March 20). The role of Artificial Intelligence (AI) in assisting applied natya therapy for relapse prevention in de-addiction. SpringerLink. 

https://link.springer.com/chapter/10.1007/978-3-030-98404-5_28

Breaking the Silence: Ending the Cycle of Intergenerational Addiction

We have all heard stories from our parents about becoming addicted to drugs or about that one uncle who abuses substances. When we talk about addiction, we often focus on an individual's choices, bad behavior, or immediate environment. However, for many, the roots of substance issues trace back before they were even born. It comes from decades of family history, past abuses, and generational trauma.

First, according to the Substance Abuse and Mental Health Services Administration (SAMHSA), they “consider dependence on alcohol or drugs to be a long-term illness, like asthma, hypertension (high blood pressure), or diabetes” [1]. They also say that not only do genetics play a part in the chance of developing a substance abuse disorder, but also someone's environment, psychological traits, and stress level [1]. A substance abuse disorder is a serious classification of disease that should be met with compassion, understanding and a comprehensive strategy rather than judgement or isolation.

Next, to understand the causes of substance abuse we must analyze the link between a difficult childhood and a negative adulthood. According to the CDC’s landmark Adverse Childhood Experiences (ACE) study, they found that adverse childhood experiences can have “long-term negative impacts on health, opportunity and well-being” including toxic stress and “unstable work histories as adults and struggle with finances, job stability, and depression throughout life” [2]. Many of these negative consequences can lead to a turn to a dependence on substances.

Other research shows a direct relationship between generations, that the “empirical evidence is clear that parent substance use predicts substance use among offspring” [3]. Also that “intergenerational continuity in substance use appeared to be largely due to the transmission of a general tendency to use substances, rather than substance-specific mechanisms” [3]. In summary, if your parents abused drugs, you are more likely to as well, along with your kids. This cycle usually repeats generation after generation.

Another unaddressed aspect of this substance abuse issue is the concept of stigma. In many families, a family member’s substance abuse is hidden. This secrecy inadvertently teaches the next generation similar behaviors if they go on to develop a substance abuse disorder. It was found that “perceived stigma in substance abuse was linked to poorer mental health” and was “associated with lower self-esteem, higher depression and anxiety, and poorer sleep [4]. On the other hand “perceived social support was linked to greater mental health” [4]. Overall, this stigmatization can unintentionally deprive individuals of the social support necessary to recover and reinforce harmful behavior.

Combatting this concept of intergenerational substance abuse is complicated but many people are working on different solutions. First the CDC is “committed to building systems and communities that nurture development” and to “prevent ACEs before they happen, and buffer the risk of harm when they do happen” [2]. Secondly, getting abusers to use social support can also mitigate the negative impact of internalized stigma and health [4]. Finally ,“successful preventive interventions in substance abusers “may not only reduce conduct problems and substance use” but “may also affect positive development in the next generation” [3]. Ultimately, these intergenerational issues can be addressed through the right support.

In conclusion, generational trauma and abuse may be built on someone past, but can be combatted in the present to prevent its spread into the future generations. By understanding the science of addiction and destigmatizing substance abuse, we can dismantle the barriers to recovery and help the next generation.

Reviewed By: Vedant Patel

References

[1] Substance Abuse and Mental Health Services Administration. (2014). What is Substance Abuse Treatment? A Booklet for Families. U.S. Department of Health and Human Services. https://library.samhsa.gov/sites/default/files/sma14-4126.pdf.

[2] Centers for Disease Control and Prevention. (2024). About Adverse Childhood Experiences. U.S. Department of Health and Human Services. https://www.cdc.gov/aces/about/index.html.

[3] Bailey, J.A., Hill, K.G., Oesterle, S. et al. (2006).  Linking Substance Use and Problem Behavior Across Three Generations. Journal of Abnormal Child Psychology.  https://doi.org/10.1007/s10802-006-9033-z. 

[4] Birtel, M.A., Wood, L., Kempa, N.J. (2017). Stigma and Social Support in Substance Abuse: Implications for Mental Health and Well-being. Psychiatry Research. https://doi.org/10.1016/j.psychres.2017.01.097.