Can artificial intelligence help prevent mental illness?

Mental illness is a significant public health issue affecting millions of people worldwide. According to the National Institute of Mental Health, approximately one in five US adults have a mental illness. Mental illness can impact a person’s daily life, affecting their ability to work, study, and maintain personal relationships. Given the widespread prevalence of mental health issues, finding new and innovative ways to prevent and treat mental illness is essential. One promising area of research in this field is using artificial intelligence (AI) to prevent, treat, or manage mental health disorders. Thus, this article discusses some of the ways the technology has been valuable and the various challenges of its adoption.

Artificial intelligence and mental illness: Ways to improve treatment interventions

AI can learn and use complex data to analyze issues and provide possible solutions. It can be instrumental in mental health diagnosis by increasing the accuracy of test results, speeding up and improving the speed of drug development, and fine-tuning the general methods of service delivery. Here are the specific ways AI can help improve mental illness treatment plans:

Identifying people at high risk of developing mental health conditions

AI helps with the development of predictive machine learning algorithms. These algorithms can analyze huge data sets to identify people at the highest risk of developing mental health complications. In addition, the algorithms can help to map out some of the major causes of mental health issues and help with their resolution. One of the benefits of using this technique is its accuracy. The machine learning algorithms undergo intensive training, ensuring they are fully compliant with medical procedures and can provide the required level of assistance. Predictive analytics is one of the ways health institutions can use artificial intelligence to prevent mental illness. It ensures that data informs all policies, leading to better patient management. Thus, it is worth implementing, not just in managing mental health but other issues significant to public safety.

Chatbots therapy

Using AI for mental health interventions involves various steps. One widely used and accepted procedure is using AI-powered chatbots to provide 24/7 support to patients with mental health conditions. Researchers can program the Chatbots to provide empathy, offer advice, and detect signs of distress or suicidal ideation. The step can be instrumental when dealing with people who fear opening up and might be more comfortable dealing with technology for fear of judgment. The AI-powered chatbots can also help collect data and patient demographics, enabling policymakers to find accurate information on people’s mental health and ensure the implementation of the right prevention interventions.

Virtual reality therapy

Virtual reality therapy uses computer-generated simulations to recreate real-life situations that trigger anxiety or other mental health issues. It is one of the most effective applications of artificial intelligence to treat mental illness. Mental health professionals can use this technique to help patients understand their situations and decide to seek treatment. Virtual reality therapy can help patients overcome their fears and anxiety by gradually exposing them to simulated conditions in a controlled environment.

Monitoring patient progress

Health institutions use AI for mental health when there is a need to monitor many patients. It allows the professionals to feed in data that identifies and analyzes patients’ utterances to gauge the effectiveness of the adopted treatment measures. The results from such initiatives help with the redevelopment of better mental health interventions.

While artificial intelligence has provided some reasonable ways to deal with the issue of mental health, there needs to be more work to find ways students can navigate the subject to maintain optimum performance. The challenge comes in when one has to fulfill academic obligations while at the same time undergoing treatment. 

Challenges of using artificial intelligence to treat mental illness

The use of artificial intelligence in healthcare has great potential when it comes to sustainability and accuracy. However, some challenges come along the way, affecting the milestones researchers have made in its improvements. Here are some challenges associated with using AI for mental health interventions.

• Lack of standardized data: Mental health conditions can be difficult to diagnose and treat due to the complexity of the various illnesses. In addition, healthcare professionals often need more consensus regarding the best treatment options, making implementing interventions more complicated. Such disparities have led to limited data that can be useful in training AI models that institutions can use, leading to poor interventions. Developing accurate predictive models or personalized treatment plans can be easier with standardized data.
• Potential for bias: AI systems are only as good as the data they are trained on, and if the data is biased, the algorithm’s results can also be partial. For example, if an AI algorithm is trained on data that disproportionately represents one race or gender, the algorithm may be less accurate for people from other races or genders. Many health professionals who use AI for mental health research have reported these issues, putting the technology in the spotlight as a contributor to society’s ills.
• Data privacy concerns: Data is susceptible and must be protected from unauthorized access. For this reason, researchers must design AI algorithms to protect the privacy and confidentiality of mental health data. In addition, patients must be assured that they are secure and will not fall victim to data breaches just because they accepted using artificial intelligence to get mental health assistance.
• Limited access to mental health services: AI can help address the shortage of mental health professionals by providing 24/7 support to patients with mental health conditions. However, not all patients can access the technology needed to use AI-powered mental health services. Also, the cost of AI-powered mental health services may be prohibitive for some patients, forcing them to shy away from using artificial intelligence to treat mental illness.
• Ethical concerns: Some people may be uncomfortable sharing their personal information, including their mental health data, with machines. Additionally, AI-powered chatbots may need to provide a different level of empathy and emotional support than human therapists, leading to concerns about the quality of care. These concerns have contributed to the low success rates of using artificial intelligence in mental health. Thus, there is a need to find better ways to address the patient’s concerns before promoting the complete adoption of AI in healthcare.
• Integration with existing mental health services: Integrating AI-powered mental health services with existing systems can be challenging. Mental health professionals may be hesitant to adopt new technology due to the numerous concerns of patients. In addition, integrating the latest technology into the existing services can be complicated, calling for the souring of more experienced professionals. The process might be costly and critically affect the hospitals’ budget. Therefore, there is a need to address the costs before promoting the use of AI for mental health.

Breaking the status quo

Many healthcare institutions have been reluctant to implement artificial intelligence in mental health interventions. The numerous challenges that come with a change in systems are concerns to go by. However, with the significant milestones AI has completed, there is no doubt that it holds an important position in the global medical system. This article has presented some of the issues, and we hope it turns out useful to mental health advocates and policymakers.

How AI Lets Clinicians Accurately Diagnose Mental Health

About the Author

Lauren Bradshaw started writing career in 2003. Since then she has tried her hand in SEO, website design and copywriting. Currently she is working for an essay writing service CustomWritings. Her major interests lie in content marketing, developing communication skills, and blogging. She’s also passionate about AI, machine learning and digital marketing.