AI Transforming Mental Health Care
-By Sania Patel
According to Britannica, artificial intelligence, or AI, is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. AI has the ability to learn, reason, problem-solve and recognize and respond to languages and various perceptions.
Learning is developed through two categories, trial and error, and generalization. AI often uses trial and error to form multiple possible solutions. The program will then run through all the possible solutions to record correct answers and edit flawed ones. For example, a simple computer program may move at random to solve a mate-in-one chess problem. AI may also use generalization, which involves the application of experience to analogous new solutions. For example, a program that learns the past tense of regular English verbs by rote will not produce the past tense of a word such as jump unless it was previously presented with jumping. In contrast, a program that is able to generalize can learn the “add ed” rule and so form the past tense of jump based on experience with similar verbs.
AI also has the ability to reason, and problem solve. Although AI can perform deductive reasoning, as it involves logic and mathematics, it has difficulty performing activities dealing with inductive reasoning. AI struggles with the ability to draw inferences relevant to the solution of a particular task or situation, while it succeeds in the field of drawing inferences from specific circumstances. AI also involves itself in problem-solving by searching through a range of possible options to reach some predefined goal. AI has a strong ability to solve both special-purpose and general-purpose situations. While special-purpose focuses on specific features of a problem, general-purpose applies to various issues.
Finally, AI has the ability to perceive its environment given specific programming and sensors to complete its analysis. Through these systems, AI is able to develop a language, which, in AI’s situation, is perceived through a system of signs that have meaning by convention. Due to this factor, AI often does not depend on language to be confined to the spoken word - certain images and graphics can be easily translated.
Given the nature of AI’s accuracy and accessibility, there is no doubt that these technologies will be used increasingly in the future, especially in the field of mental health care. Currently, AI offers patients their diagnosis, treatment plans, and therapy. Many studies have shown that people prefer mental health treatment plans to come in the form of AI, as it is easy to accommodate one’s schedule and more affordable than traditional in-person treatment.
As stated previously, AI has already made its way into mental health care. There are three particular technologies that allow AI to specialize in this field they are machine learning (ML) and deep learning (DL), natural language processing (NLP), and computer vision. ML and DL help AI provide greater accuracy in diagnosing mental health conditions and predicting patient outcomes. NLP is used for speech recognition and text analysis, which assists AI in the simulation of human conversing via chatbot programs. It is also used for creating and understanding clinical documentation. Finally, computer vision allows AI to analyze imaging data and understand non-verbal cues, such as facial expression, gestures, eye gaze, and voice tenseness.
There are many ways that AI is revolutionizing mental health care in order to make it more affordable, accessible, and expansive. Overall, there are five ways that AI is looking to develop to transform the current mental health care system.
1. Combining mental health care with physical health care
By combining these two aspects of health care, machine learning algorithms can alert doctors and surgeons of a patient that is at risk of developing a serious mental health issue based on their existing medical records. A study was conducted by the Association for Psychological Science which found that out of the 5,167 adult participants with a claim code of self-injury, 3,250 patients made a suicide attempt, and 1,917 patients engaged in self-injury that was nonsuicidal, accidental, or nonverifiable. Another study showed that when it comes to the opioid crisis, data suggests that 10 percent of patients who use opioids for 90 days after cardiac surgery will end up dependent on those medications.
2. Reducing bias and human error in AI services
There are several studies that have proven AI to be successful at detecting signs of conditions like depression and post-traumatic stress disorder by interpreting speech patterns and facial expressions. A study done by Virtual Human (VH) uses their technology, SimSensei, to infer the states of the user through behavioral signals such as facial expressions, body gestures, and vocal parameters. This technology could be used by mental and physical health providers, to provide backup during patient intake meetings. Current meetings are very brief, and professionals are often rushed and may neglect to recognize certain behaviors exhibited by the patient.
3. Increasing accessibility
By producing mental health care services by AI, they can become accessible from anywhere at any time. These online chatbots and apps are low-cost, affordable treatment options that are always available. There have also been several studies that show people are more comfortable sharing their emotions and history with an anonymous chatbot than a human being. Many people find that sharing personal information with other people can be threatening, as they may be judged or falsely diagnosed due to bias. Although these tools are still new and experimental, app-based mental health care services can offer ways to improve their mood, and track cognitive-behavioral aspects.
4. Destigmatize mental health issues
In the future, AI could make mental health diagnosis and treatment more quantifiable and less subjective, ultimately helping to destigmatize mental health conditions and improve outcomes. Since AI functions as a machine learning algorithm, the treatments can focus less on a patient’s subjective experience and distress, while focusing more on evidence-based data and medical practices. Overall, mental health care services that are AI-based will allow people to feel open to sharing their issues, rather than thinking of treatment as a secret shame.
5. Flagging early warning signs of mental health issues
Finally, AI can be used in mental health care to alert medical professionals of suicidal thoughts or actions, as well as increased depression, anxiety, and other issues. Eventually, AI could be capable of detecting certain tendencies depending on daily actions, such as how fast you’re typing and what you are typing. In a study conducted by IBM, algorithms using language analysis were 100 percent accurate at identifying teenagers who were likely to develop psychosis. Language analysis could also be used to monitor patients who are currently in treatment but experience a greater suicidal risk. By answering a few questions and analyzing the behavior of the patient, AI could detect early signs of trouble.
Overall, AI is making massive advancements into mental health care services and could quickly modernize and revolutionize health care. AI has the ability to make health care easy to access, affordable, and accurate, as it is based online and follows algorithms, not inherent bias. As AI advances, medical professionals are noticing its increasing benefits and potential. Given the current AI abilities and technology, we can only begin to imagine the possibilities.