Artificial intelligence is shaping our future nearly in all industries. Businesses from different industries use artificial intelligence development services to optimize business processes and improve their products and services. Recent developments suggest that the latest AI advances can usher in a new era of mental healthcare, too, and probably just in time.
The mental health crisis is serious worldwide. According to the latest data from the WHO, almost 1 billion people were experiencing a mental disorder in 2019, with their number estimated to jump by a third in 2020 due to the COVID-19 pandemic.
However, access to effective care continues to be challenging. A growing shortage of psychiatrists and expensive therapy are the main causes.
The adoption of AI in healthcare might open the door to a change. Read below to learn how.
How can AI help improve mental healthcare, exactly?
AI is already gaining traction across mental healthcare, with its following subsets driving the wave of innovation:
- Machine Learning (ML)
- Natural language processing (NLP)
- Computer vision
They are applied for accomplishing different tasks, including:
1. Helping users track their mood and manage mental health
AI chatbots are increasingly being used in the field of mental health treatment as a way to provide support and a sense of companionship to individuals who may be struggling with mental health issues. They mostly rely on NLP to understand, interpret, and generate human language, and ML to learn from the user and tailor their responses accordingly, offering more personalized guidance.
Such AI chatbots are usually trained in cognitive behavioral therapy (CBT), an evidence-based approach that helps users identify and change negative thought patterns and behaviors. They provide coping strategies, self-diagnosis tools, and even personalized recommendations. Woebot, Tess, Wysa, and iHelpr are among the conversational agents that are already widely used for mental health self-management.
Despite criticism that AI is not yet able to recognize all complexities of human language, studies suggest positive experiences with the quality of diagnosis and the efficacy of therapy provided by chatbots.
2. Analyzing vast volumes of data to improve diagnosis, adjust treatment plans, and detect mental conditions early
Incorporating AI into data science tools to analyze patients’ medical history, tests, questionnaires, behavioral aspects, emotions, and text/speech can enable health professionals to detect mental illnesses and personalize treatment plans.
For instance, researchers at the US-based Dartmouth College have presented an AI model capable of detecting emotional disorders based on Reddit posts. Another research has shown that deep learning techniques used in combination with motion sensors can identify symptoms of anxiety with 92% accuracy.
3. Improving patient engagement
AI offers big hopes for improving the experience of patients in healthcare organizations.
For instance, AI chatbots can be used not only for psychotherapy but also to ease the burden on healthcare staff by automating their tasks. Applications range from scheduling doctor appointments to giving instant answers to queries, monitoring medication adherence, and checking on patients by asking questions about their mental health status or analyzing biometric readings from sensors.
4. Automating daily operations
Using ML, NLP, and robotic process automation, AI-powered systems can automatically fill in EHR forms, search for clinical information, and process papers, saving hours of doctors’ work. They can also extract data from the healthcare ecosystem for producing various kinds of reports that a medical professional might require for a patient’s case.
Examples of such systems feature the AI-based system OPTT that is able to provide mental health provider teams with new, innovative approaches to care.
What benefits does AI deliver for mental health care?
- Making therapy more affordable. With an AI chatbot, individuals get access to cost-efficient tools for support and guidance. They don’t require a user to travel to a therapist’s office, take time off work, or settle other things to make it for a scheduled one-to-one session. Pricing plans offered by AI chatbots are also much more affordable than in-person therapy.
- Improving access to care. AI can help address workforce shortages — demand for therapy has increased in the aftermath of the COVID-19 crisis, with six in 10 psychologists in the US saying that they are fully booked. The number of individuals seeking therapist help has also increased. AI-based solutions are a good option to get help for as long as a person may need it and wherever it is needed.
- Providing effective care. AI technologies have been found effective at measuring behavioral aspects in users to help diagnose various medical conditions. Today, AI models can predict if a person with a family history of schizophrenia is likely to develop this disorder, too, or identify those at risk of developing PTSD symptoms a few weeks after a trauma, using smartphone-based surveys. AI can also predict how children with depression might react to treatment with antidepressants. In addition, there is early evidence that AI chatbots designed for mental health self-management can improve subjective psychological wellbeing.
- Keeping things private. Many people feel more at ease when sharing intimate details about their lives anonymously. In fact, more than 20 percent of patients lie to doctors, with 75% of them citing embarrassment as the major reason. AI doesn’t judge your bad habits or sexual activity, making it easier to spill a heart.
- Supporting therapists. Because of its ability to monitor and process a big amount of data, including patients’ mood and activity, healthcare AI development services are a great help to medical professionals in detecting symptoms early to reexamine their treatment strategies. Timely interventions to offer emotional support can be especially critical in support of suicidal patients.
Wrapping it up
The power of AI comes with challenges, like data and societal bias, little transparency over AI models’ decision-making process, and the inability to provide consciously empathic attention.
However, the implementation of AI in mental healthcare is an ongoing undertaking, and there will always be a new technique and a new model. One thing is certain: the story of AI in mental health has begun and there’s every sign that there’s more to come.