The Promise of AI in Mental Health: Possibilities for Early Detection, Screening, and Increased Accessibility

Mental health is an integral part of our overall wellbeing. As more people around the globe are beginning to realise this, the demand for mental health services continues to grow. At the same time, there’s a notable rise in the prevalence of mental health disorders around the world – which could be linked to several recent major world events.

The COVID-19 Pandemic, return to the office post-lockdown, increases in cost of living, the Russia-Ukraine War, and the possibility of a looming recessions – to name but a few. The list is long and has left many communities, businesses, and entire countries with great uncertainty. For many, these changes have dismantled life as we know it. This can cause ongoing – and even lasting – mental and emotional distress. And it can be difficult to manage and navigate these mental health challenges on our own. 

Now, more than ever, it’s important for mental health service providers to explore innovative approaches that can help them meet these increasing demands. Artificial intelligence (AI) is emerging as a promising solution that could revolutionise mental health services around the world. Applications span early detection, screening for individual needs, and enhanced accessibility and scalability. While many people are embracing the power of AI in mental health care, there are some who are showing caution in response to warnings over possible risks and challenges that AI holds for the field.  

We explore some of these concerns and unpack how these risks and challenges can be mitigated or entirely avoided. We also look at how AI can be safely used in mental health care and be beneficial to both patients and practitioners alike. And we share a brief case study of Plumm’s very own virtual wellbeing assistant EMMA, where we unpack some of the most notable benefits of EMMA’s always-on, personalised support.  

The Promise for Early Detection of Mental Health Issues 

Early detection ensures that mental health issues are addressed in time and prevented from getting worse. AI-powered algorithms can analyse large amounts of data, including people’s behavioural patterns, language use, social interactions, and physical data. This information can help the algorithms identify subtle indicators of mental health concerns and help put preventative strategies in place. An article published by the World Health Organisation (WHO) earlier this year, highlighted AI’s potential to help recognise early signs of depression, anxiety, and other mental health disorders, even before individuals are able to recognise or express their struggles to themselves or a professional (WHO, 2023). This is what makes AI such a valuable tool for preventative care. 

By analysing data from digital platforms, social media, and health records, AI can also identify behavioural patterns that might indicate declining mental health in certain individuals. This type of early detection was not possible before the introduction of AI. It’s a capability that opens many new avenues for mental health professionals. This data can help providers intervene faster - significantly reducing the burden on healthcare systems by decreasing the number of hospitalisations linked to mental health.

Screening for Individual Needs 

Another exciting element of AI-powered tools is that they can analyse individual data to create personalised treatment plans. These would be specially tailored to each person’s specific needs – a benefit which may have taken a long time to develop in a pre-AI world. By considering a person's unique circumstances, experiences, and preferences, AI can offer more targeted and effective interventions. This means people might benefit from fewer ‘trial-and-error' treatments and find the right fit a lot sooner.  

As WHO (2023) noted in their recent article, personalised mental health care enhances treatment outcomes and empowers people to actively participate in their healing journey. Through machine learning algorithms, AI systems can continuously learn from user interactions, refine its understanding of individual needs, and adjust support accordingly. This interactive process helps ensure mental health services remain adaptive and relevant, providing tailored guidance and resources based on each person's progress and requirements over time. 

Improved Accessibility and Scalability 

One of the biggest advantages of AI in mental health is its potential to bridge the accessibility gap and support a broader population. WHO (2023) has also emphasised how AI-powered mental health chatbots and virtual assistants can provide 24/7 support. This allows people to seek help at any time, even in remote or underserved areas where access to traditional mental health services might be limited. Another great benefit is that AI can also help reduce the care barriers associated with stigma. Some people might feel more comfortable discussing sensitive issues with an AI system rather than face-to-face with another person. This fosters a safe space where individuals can talk about their emotions and concerns openly, encouraging more people to seek help without fear of judgment. 

One of the most notable ways in which AI increases scalability of mental health services and interventions is through its cost effectiveness. AI significantly reduces the need for human resources and manual labour, which in turn lowers operational costs. This cost-effectiveness allows mental health programs and platforms utilising AI to extend their reach to a much bigger part of the global population. There’s huge benefit in making mental health services more affordable and accessible for people from diverse socioeconomic backgrounds.  

When mental health needs surge in times of crises or emergencies, AI can provide immediate responses and resources to many people simultaneously. This eases the burden on mental health professionals and crisis helplines. More to follow on this in our real-life case study of EMMA below!  

EMMA: A Real-Life Case Study 

At Plumm, we have already witnessed the impactful difference that our virtual wellbeing assistant, EMMA, has made for many employees, partners, and teams. One notable benefit is the instant access to support that comes with EMMA. Scheduling a session with a real-life therapist can be time-sensitive, often resulting in waiting times of 24 hours or more. While this is a normal challenge associated with booking a virtual or in-person appointment, the possible delay can be distressing for someone grappling with intense emotions, frustrations, or episodes of feeling ‘out of control.’ In this instance, EMMA – and similar AI tools – can offer instant support, which may provide solace during the waiting period and help with containment of these difficult emotions. By attentively listening, understanding, and responding, EMMA can help to alleviate a person’s emotional burden and assure them that they are not alone, that they are being heard, and that their feelings and concerns are valid. 

Another great benefit is that EMMA may offer a more approachable initial step in the healing journey. Unlike conventional therapy, users don’t have to schedule appointments or emotionally prepare for live sessions. AI-powered wellbeing companions like EMMA offer flexibility, allowing individuals to engage in conversations whenever they want. Whenever works for them and whatever their need in that moment. EMMA is also programmed to recommend relevant course material and educational resources to users depending on the topic areas they would like to work on. This way, they can learn more about the condition or challenges they are grappling with. These additional insights into the topic provide a clearer understanding of the strategies they can adopt to improve their health and wellbeing.  

Another thing we’ve noted since launching EMMA is the element of approachability and convenience. Interactions with EMMA are discreet. The text-based support can be accessed through a mobile device or PC, resembling regular, everyday smartphone, tablet or PC use. This can help to eliminate the stigma or pressure that some people associate with seeking private spaces for virtual therapy sessions. For people who don’t feel ready to tell their colleagues or families about their need for mental health support, services like EMMA offer the most discrete and accessible care on the market. With over 10,000 chats EMMA is already making a massive impact for users. 

By leveraging AI technologies – such as natural language processing and machine learning – EMMA can provide empathetic and personalised responses in real-time, fostering a sense of safety, confidentiality, and anonymity for users. By understanding and leveraging these advantages of AI systems for mental health, we can create a more inclusive and effective mental health support ecosystem, complementing the expertise of human practitioners with the capabilities of AI technology.  

Proceeding with Caution 

Understandably, as with any change, not everyone is embracing the use of AI in mental health care. There has been some caution and criticism – and it's important to acknowledge and address these concerns. We understand that it can be scary and challenging to navigate a space that is so new and rapidly evolving. But we believe that progress and innovation should be approached with curiosity and open-mindedness. At the end of the day, the more you know about something, the less intimidating and scary it comes to be. That’s where awareness plays such a crucial role. It’s as important to be aware of the risks and challenges associated with innovative technologies as it is to be aware of the benefits. So let’s have a look at some of the key concerns and how they can be mitigated.

Data security and privacy 

One of the major concerns when it comes to the use of AI in mental health support involves the issue of privacy and data security. AI systems require access to sensitive and personal information about individuals to better understand their needs and current situation. While there is a risk of unauthorised access or data breaches – which can lead to sensitive mental health information being exposed – this risk can be mitigated by ensuring that robust data security measures are in place.  

Bias against historically marginalised or underrepresented populations 

Another important challenge to be aware of is the issue of ‘bias’ in AI systems. AI algorithms are only as good as the data they’re trained on. So, if the training data used to build these systems contains biases towards certain people, the systems may unknowingly exercise unfair or discriminatory treatment – particularly for marginalised or underrepresented groups. In these instances, AI could amplify existing inequities in society by seeing certain correlations between characteristics as ‘true’ rather than as being skewed by societal biases and historical inequalities. To address this shortcoming, developers of these AI systems should test carefully and thoroughly for potential biases and make sure they are removed from the algorithm.  

 Misinterpretation and misdiagnosis 

Another criticism has been that AI models may not always be accurate in interpreting and understanding complex emotional and mental states. Because of this limitation, some critics argue that relying just on AI for diagnosis or treatment decisions could lead to misunderstandings or incorrect conclusions, potentially harming the person in treatment. Although this is a valid concern, these risks can be minimised by ensuring that trained, human professionals perform thorough analysis and screening of users before any decisions or diagnoses are made. The AI systems should merely be used to flag concerns that need more urgent care and attention, while leaving the final conclusions to the discretion of the doctor or psychologist. 

Lack of authentic human connection 

One of the most common criticisms of AI-powered wellbeing or mental health assistants is the lack of a true human connection. While AI can provide valuable insights and support, and engage using language that conveys empathy, it doesn’t replace human connection, which are essential in mental health care. The important thing is AI can still bridge an important gap between supply and demand.  AI is not intended to replace, but rather complement the overarching goals of the global mental health community.  

It’s important to acknowledge all points of view. And to understand the potential risks associated with AI in the mental health field. There’s no question developers should show awareness and always remain conscious of new developments. To address the risks discussed in this article, it's essential to combine AI tools with human oversight and intervention. Mental health professionals should work alongside AI systems to provide personalised care, ensure ethical practices, and prioritise user wellbeing above all else. Ongoing research, transparency, and collaboration between AI developers, mental health experts, and regulatory bodies are vital to continue addressing these challenges effectively.  

Reflections 

The emerging role of AI in mental health support shows great promise in addressing the global mental health crisis. With its potential for early detection, diagnosis, intervention, scalability, and personalised care, AI-powered solutions can revolutionise how we approach mental wellbeing. Text-based therapy offered by innovative virtual companions like EMMA, offers a convenient and accessible platform for people to seek support and guidance during times of distress and uncertainty. However, as we embrace these advancements, it‘s also important to remain aware of potential risks linked to AI-powered support systems. We must address them continuously as the technology evolves. Developers will address these challenges and ensure that AI-powered mental health support remains grounded in human-centric principles, empowering people to navigate their mental wellbeing with confidence and resilience. By combining the strengths of AI and human practitioners, we can create a future where mental health support is accessible, effective, and compassionate.  

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