AI in Mental Health: Key Advances Changing Therapy in 2024

Clinicians are sounding an alarm bell about a global mental health crisis. In the U.S, suicide is the second leading cause of death among young people and teenagers. According to Harvard University, half of the world's population will suffer from a mental health disorder in their lifetime. 

The number of mental health patients is quickly rising and putting a strain on healthcare systems. The shortage of healthcare professionals leaves clinicians overloaded and patients suffering. In this challenging context, AI in mental health offers a glimmer of hope for psychologists, psychiatrists, and their patients. 

In this article, we discuss applications of artificial intelligence in mental health. From clinical diagnostics to AI mental health therapy, we’ll shed light on the most current developments and practical use of AI in mental health. 

Let’s get started. 

AI for clinical diagnostics and prediction

Multiple studies have explored the possibility of using AI to diagnose mental health disorders. A recent comprehensive review on the topic investigated the use of AI for mental health trained on several types of data: 

• Electronic health record data. AI models trained on EHR data successfully predicted the likelihood of depression, estimated probability of suicide death, and detected suicide ideation based on sociodemographic variables and EHR data.

• Mood rating scales. AI models trained on patients’ mood rating scales were able to predict whether patients with depression will achieve remission after a treatment. AI was also able to compare the efficacy of antidepressants and detect patients that will respond better to placebo or medication. 

• Biological data. AI trained on brain imaging data was able to diagnose subtypes of depression and schizophrenia, detect brain aging, and predict late-life diagnosis. 

• Social media data. AI models trained on social media data predicted suicide ideation, accurately detected mood from data, and identified users with depressive symptoms. 

Studies prove the immense potential of AI mental health diagnosis to improve diagnostic accuracy and facilitate timely interventions. For now, however, AI is not yet widely used as a diagnostic aid for clinicians. 

AI for EHR record keeping and therapeutic assistance

AI has been practically applied to streamline EHR record keeping and reduce administrative load on clinicians. Here are some AI-based features recently introduced in EHR systems. 

• Recording notes from patient-clinician conversations. One EHR provider has recently introduced a feature that allows to confidentially record conversations between patients and clinicians. An electronic note is generated and updated with a draft of the discussion, which the physician can then review, edit, and finalize. This can significantly save time spent by doctors after clinical hours and improve documentation quality. 

• Voice assistants and summarizing. Integration of voice assistants into EHR systems allows clinicians to get specific information about the patient’s history without looking through dozens of documents. The clinician can just ask questions like “Has she ever complained about panic attacks” and receive accurate answers within seconds. A clinician can also get AI summaries and detailed medical history, including changes since the last visit, new medications, clinical documentation, past treatments, risk factors, etc. 

• Patient scheduling. Mental health artificial intelligence can optimize patient scheduling. AI software can prioritize high-need visits and reserve slots based on predicted daily volume of patients. This makes sure that patients who need care the most will receive it. AI scheduling solution can also update templates to minimize open slots, and manage no-shows and cancellations. 

Applying AI for streamlining routine tasks and reducing administrative load is one of the most practical ways to achieve improved efficiency and productivity. 

AI mental health chatbots

Mental health chatbots have by far been the most popular type of AI for mental health. These chatbots aim to provide accessible support through mobile applications. They engage users in personalized interactions and provide a non-judgmental environment that encourages self-disclosure and emotional expression. Chatbots can be especially beneficial for those hesitant to seek traditional mental health services due to stigma. 

A recent review of mental health AI studies shows that chatbots can successfully track moods, provide elements of CBT therapy, reduce depressive symptoms, and promote positive psychology.  

Types of mental health chatbots

AI mental health chatbots can be trained on different kinds of data and provide information tailored to the specificities of the application. 

Purpose

Mental health chatbots are designed to provide support to users in specific ways:

• Digital Coach. These chatbots help users set and achieve small personal goals. Without offering professional-level advice, they provide guidance and motivation to help users implement positive changes in their daily routines.

• Digital Screener. These chatbots can analyze conversations and alert users to potential mental health concerns. When necessary, the chatbot encourages users to seek further information or counseling. 

• Virtual Therapist. These chatbots engage users in therapeutic conversations. While not identical to professional therapy, they offer basic counseling and support that mimics interactions with a human therapist.

Type of Conversation Flow

AI mental health chatbots can be designed to follow three types of conversation flow. 

• Guided Conversation. This approach restricts user interaction to predefined responses and provides a structured dialogue with limited user input.

• Semi-Guided Conversation. Users primarily interact through predefined responses but can occasionally give open inputs. However, the chatbot may not effectively understand or use this information.

• Open-Ended Conversation. Combines predefined responses with open user inputs. The chatbot can recognize and extract meaningful information from open inputs, which allows more natural and flexible exchanges. 

Open-ended conversations are the most advanced type of the conversation flow. However, sometimes it may not be necessary – for example, if your bot is designed for screening. 

Types of content for mental health chatbots

Mental health chatbots offer different types of content designed to address various aspects of mental well-being. Here are the types of content these chatbots can offer, along with examples:

Educational Content

Chatbots can provide users with information about the symptoms of mental illness, information on potential triggers and treatment options, including therapy and medication.

A chatbot can explain concepts like cognitive distortions and provide examples of how negative thinking patterns affect mood. It may help the user identify automatic negative thoughts and replace them with more balanced ones. 

Therapeutic Conversations

Meditation and mindfulness exercises are commonly included in chatbot functionality. A chatbot can ask users to focus on their breath or conduct a body scan to increase awareness of physical sensations. This helps the patient relax and focus on the present moment. 

It can also ask users to journal the moments they felt stressed and explore what might have triggered these feelings. This is helpful for understanding and managing emotions. 

Monitoring and Tracking 

Many chatbots allow users to log in their daily moods and note any significant events that impacted their mental health. For example, a chatbot might remind users to log how many days they felt anxious over the past week. This helps them identify trends and address the underlying causes of anxiety.  

Interactive Features

Chatbots typically provide a range of interactive features. For example, it could help set a goal like "exercise for 30 minutes, three times a week" and provide regular reminders and encouragement. If the user struggles to adhere to the schedule, the bot can suggest corrections. 

The bot may also guide the user to establish a bedtime routine and provide guided progressive muscle relaxation sessions or short breathing exercises to quickly alleviate stress. 

Crisis Support

Some chatbots provide users with information on crisis-related helplines and emergency services. Advanced solutions can even analyze conversational cues and detect potential emergencies. This allows the user to reach out to professionals on time. 

Furthermore, If the chatbot is connected to a network of mental health professionals, it may notify designated personnel in critical situations. 

AI mental health chatbots examples

Here are the examples of successful commercial AI mental health chatbots that provide efficient care to users. 

Wysa

Wysa is an artificial intelligence mental health app and support platform designed to provide accessible and comprehensive mental health resources. Wysa is integrated with the NHS and provides a range of features that make it a comprehensive companion for mental health monitoring and treatment. 

• Resource Library. On-demand access to evidence-based videos, audios, and materials for issues like stress and anxiety.

• Mental Health Tools. Mood monitoring, thought reframing, relaxation techniques, and goal setting via interactive chat.

• Crisis Support. Connecting users to helplines and offering grounding exercises and safety plans. .

• NHS Integration. Integrates with NHS TT Electronic Patient Record Systems to streamline clinician workflows.

• Wysa Copilot. Improves patient-therapist communication with direct messaging, document sharing, and shared goal setting. 

These features help Wysa effectively support mental health management and care delivery.

Youper

Youper offers interactive CBT therapy exercises designed to calm anxiety, boost mood, and strengthen relationships. It provides instant, practical advice on the go, ideal for those with busy schedules.

Youper employs scientifically-backed CBT techniques to help users manage stress and emotions. A Stanford University study found that it significantly improves depression and anxiety symptoms. Some features of Youper include: 

• Assessment and Personalization. Youper screens for common mental health conditions and customizes its features according to the issues found. This ensures that each user receives tailored support.

• CBT-Based Interactions. Users can engage in quick chats with Youper to receive instant mental health support. The bot uses Cognitive Behavioral Therapy (CBT) interventions to address their concerns.

• Symptoms Monitoring. The app provides clinically validated assessments to help monitor symptoms across six different mental health conditions. 

Limbic AI

Limbic Care is an AI-powered mental health chatbot designed to complement therapy and help users in-between sessions. Distinctive features of Limbic AI include: 

• Customization by clinicians. Cognitive Behavioral Therapy prompts delivered by Limbic AI can be modified and customized by clinicians to deliver specialized care to each patient. 

• Limbic Library. Provides a resource of modifiable activities that therapists can tailor for individualized patient care.

• Personalized treatment plans. In this way, Limbic AI fits into existing therapy plans. It provides continuous support and allows clinicians to adjust and customize treatment pathways.

Final thought: Can AI help with mental health?

AI in mental health is becoming an incredibly effective tool for overcoming the worsening mental health crisis in the world. Researchers are developing and testing AI models that can help diagnose mental health conditions based on large datasets. 

When it comes to practical applications of AI in behavioral health, administrative tasks can be automated most efficiently. Artificial intelligence mental health solutions are already streamlining EHR record keeping and reducing administrative load on practitioners. 

Simultaneously, AI mental health chatbots are becoming an increasingly popular solution for patient support in-between therapy sessions. Used both as a standalone solution for individual users, and systematically by healthcare providers, AI chatbots for mental health have proven their efficiency in reducing patient dropouts, reducing the number of necessary sessions, and increasing reliable recovery. 

The future of AI and mental health is promising. At Apiko, we have extensive experience in mental health app development, including and not limited to AI chatbots. Check out our case study to see by yourself!