AI in Mental Health: Exploring Advantages and Challenges
Table of Contents
Introduction to AI
Artificial intelligence (AI) is revolutionizing our world and, naturally, impacting our mental health.
Advancements in AI are not just reshaping our approach to mental well-being; they are creating unprecedented opportunities to improve mental health care and support.
As we embrace these new technologies, we must proceed with caution. AI has already proved to cause serious harm, underscoring the need to harness its potential responsibly. Let’s explore how these advancements can improve our lives, the challenges we face and how we can use AI for a brighter future.
AI’s role in mental health
AI refers to advanced technology that enables machines to learn, think and make decisions like humans. It uses its capabilities to analyze vast data sets — from electronic medical records to social media content — helping identify early indicators of mental health issues and offering support to manage them.
By integrating AI with tools like mobile apps and chatbots, this technology is transforming how mental health conditions are diagnosed, treated and understood.
Already providing personalized advice and supporting clinical experts, AI’s expanding role in mental health is bound to bring even more insights and innovative solutions.
Five AI applications in mental health
Let’s explore how AI is shaping mental health through five key applications, each with its own advantages and challenges.
1. Early detection and prevention of mental health concerns
AI’s ability to analyze diverse data sources enables it to identify behavioral changes that may indicate mental health conditions and aid in prevention.
Advantages
AI can detect early signs of depression, anxiety and schizophrenia that aren’t always evident to humans. How? By leveraging advanced algorithms like natural language processing and machine learning to analyze speech, text and behavior patterns.
AI can also monitor and interpret abrupt changes in activity levels through devices like smartwatches. If someone who regularly uses a smartwatch to track activity suddenly shifts from being highly active to mostly sedentary, AI may interpret this as a potential sign of depression [1]. With some smartwatches, users can opt in to share this data with their health care providers, leading to early detection and timely interventions.
Challenges
AI can sometimes misinterpret data, which can cause undue stress and lead to inappropriate treatments. This can be frustrating and even harmful, so verifying AI-generated advice with a trusted professional is crucial.
Additionally, AI requires a lot of personal data to work effectively. While you generally need to consent to your data being used, not all health apps are HIPAA-compliant, meaning some may sell your data. One study found that 28% of health apps didn’t have a privacy policy and nearly 40% scored poorly on privacy standards [2]. If you choose to share your personal health data, stay informed about how your data is used and don’t hesitate to opt out of data collection if you feel uncomfortable.
2. Virtual mental health assistants
Though not a replacement for human therapists, virtual assistants and mental health AI chatbots offer 24/7 support, providing immediate assistance, educational resources, referrals and crisis intervention.
Advantages
In the U.S., one in five adults and one in six young people (ages 6-17) experience mental disorders annually, yet nearly 60% don’t receive treatment due to inaccessibility [3]. AI-driven chatbots and virtual assistants are helping to bridge this gap by making mental health resources more available and affordable.
Research on the Limbic AI chatbot, which screens individuals seeking mental health support, demonstrated a significant boost in mental health referrals. Notably, referrals for nonbinary individuals rose by 179% and for underrepresented ethnic groups by 29%, with the chatbot’s anonymity and patients’ self-recognition of their treatment needs likely contributing factors [4].
Furthermore, nine in 10 users find talking to the AI-based chatbot Wysa helpful [5]. By offering nonjudgmental and accessible communication, platforms like this address language barriers and encourage individuals who struggle to express emotions to seek help — freeing up human resources for more critical needs.
Challenges
Interactive AI tools sometimes spread misinformation and lack the human empathy required for effective mental health care, leading to negative outcomes. There have been many instances of chatbots providing inappropriate and harmful advice to individuals seeking support for eating disorders, sexual assault and other sensitive issues. These chatbots have suggested counterproductive behaviors, from weight loss and calorie counting to inappropriately reframing a deeply traumatic situation. These responses can exacerbate conditions and cause harm to people in need of genuine support.
Negative experiences with AI can also diminish trust and discourage individuals from seeking further help. If users encounter misinformation or feel misunderstood, they may hesitate to engage with mental health services again. Ensuring AI tools are carefully monitored and complemented by human oversight is crucial to protect users’ well-being.
3. Personalized treatment plans
AI can help tailor treatments to individual needs, offering new possibilities for personalized care.
Advantages
By analyzing electronic medical records, wearable devices and patient-reported outcomes, AI can assess the likelihood of developing mental health disorders based on individual profiles and create personalized treatment plans. For instance, Woebot utilizes AI-powered chatbot technology to deliver cognitive behavioral therapy (CBT) interventions through daily user interactions, tailoring responses and therapeutic approaches to meet individual needs.
Challenges
A major issue is the reliability of the underlying data. If the data used to personalize treatment is inaccurate, it can result in ineffective or detrimental recommendations. An incorrect AI mental health diagnosis or misinterpreted predictions could worsen a patient’s condition and lead to significant psychological distress. Therefore, while AI can generate valuable insights, therapists need to oversee and refine any approach to treatment. Their deep understanding of human emotions, genuine empathy and nuanced judgment make them better suited for adapting plans that effectively meet patients’ needs.
Learn more about how we approach individualized care here at Pathlight Mood & Anxiety Center.
4. Enhancing traditional therapist methods
AI mental health tools support human therapists by analyzing large sets of patient data, tracking treatment progress, facilitating remote therapy sessions and more, allowing therapists to focus more on the necessary human aspects of patient care [6].
Advantages
Many therapists are using digital tools in their approach to care. While the full potential of AI assistance in mental health is yet to be realized, numerous technologies are being developed, tested and implemented. For example, Mindstrong Health used AI to analyze smartphone interactions, such as typing patterns and screen usage, to help clinicians assess patients’ cognitive function and emotional well-being. Mindstrong’s AI models accurately predicted a crisis for a patient managing bipolar disorder and psychosis, enabling timely intervention by alerting her health care team (with her permission) and successfully preventing the crisis [7]. Although Mindstrong Health shut down in 2023, it remains a notable example of what AI is capable of in mental health care.
Challenges
After raising over $160 million in funding, Mindstrong Health faced significant challenges, highlighting the difficulty in integrating AI with traditional therapy methods on a widespread level. Difficulties in scaling the technology, changes in leadership and investor pressure to bring the technology to market prematurely all contributed to the company’s downfall. Not only did this leave Mindstrong’s patients to find alternative care, but it also exposed another layer of complexity involved in merging AI with human-led treatment.
5. Raising awareness and combating stigma
AI has the power to foster understanding and reduce stigma by filtering and sharing accurate mental health information.
Advantages
AI can make sure only accurate and relevant facts are shared, helping prevent the spread of misinformation and dismantling harmful stereotypes. Beyond this, AI can actively monitor social media, analyzing tweets, posts and comments to capture the public’s opinions on mental health issues [8]. By picking up emotional cues from these online interactions, AI helps us understand the mood of discussions and pinpoint exactly where we need to direct our awareness efforts.
Challenges
Algorithms can unintentionally favor or discriminate against certain groups based on race, gender or socioeconomic status. This problem is known as algorithmic bias and can exacerbate existing health disparities. AI’s potential to improve the accessibility and affordability of mental health care is especially significant for underrepresented communities. However, if these systems aren’t designed with diversity at their core, they might reinforce existing biases. This could unevenly distribute mental health resources and strengthen societal stigmas, ultimately hindering the progress AI aims to achieve.
The future of AI in mental health
Can AI help with mental health? Yes, and it holds significant potential. However, it complements — not replaces — the critical human touch needed in mental health care.
As these changes unfold, staying informed is crucial. Remember that if you or someone you know is struggling with a mental health concern, it’s important to seek professional help.
At Eating Recovery Center and Pathlight Mood & Anxiety Center, we provide evidence-based treatment at all levels of care for eating disorders and mood and anxiety disorders, including trauma-related disorders. To learn more about treatment, call us at 866-622-5914 or reach out for a free assessment. A compassionate mental health professional will match you with the exact support you need.
Sources
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- Benjumea, J., Ropero, J., Rivera-Romero, O., Dorronzoro-Zubiete, E., & Carrasco, A. (2020). Assessment of the fairness of privacy policies of mobile health apps: Scale development and evaluation in cancer apps. JMIR mHealth and uHealth, 8(7), e17134. https://mhealth.jmir.org/2020/7/e17134.
- National Alliance on Mental Illness. (n.d.). Mental health by the numbers. Retrieved June 25, 2024, from https://www.nami.org/about-mental-illness/mental-health-by-the-numbers.
- Habicht, J., Viswanathan, S., Carrington, B., Hauser, T.U., Harper, R., & Rollwage, M. (2024). Closing the accessibility gap to mental health treatment with a personalized self-referral chatbot. Nature Medicine, 30(2), 595-602. doi: 10.1038/s41591-023-02766-x.
- Wysa. (2023). Employee mental health report. Retrieved June 25, 2024, from https://www.wysa.com/2023-emhr.
- Graham, S., Depp, C., Lee, E.E., Nebeker, C., Tu, X., Kim, H.-C., & Jeste, D.V. (2019). Artificial intelligence for mental health and mental illnesses: An overview. Current Psychiatry Reports, 21(16). https://escholarship.org/content/qt9gx593b0/qt9gx593b0_noSplash_d814b6b41c76cb874050695d2bf30ced.pdf?t=qd3z26.
- Gruber, T. (2024). Mindstrong (website). Retrieved June 25, 2024, from https://tomgruber.org/mindstrong-story.
- Mowery, D., Smith, H., Cheney, T., Stoddard, G., Coppersmith, G., Bryan, C., & Conway, M. (2017). Understanding depressive symptoms and psychosocial stressors on Twitter: A corpus-based study. Journal of Medical Internet Research, 19(2), e48. https://doi.org/10.2196/jmir.6895.
