The Benefits of AI in Mental Health Services
A blog by Kathleen Giles
Mental health services in Australia have faced significant challenges, particularly in the aftermath of the Covid-19 pandemic. With a higher demand for talk-based therapies, long waiting times for face-to-face consultations have become a major issue. In fact, a report by the Australian Institute of Health and Welfare found that the average Australian seeking help can wait up to six months for an initial appointment. Research spanning thousands of studies shows that prolonged waits for support can exacerbate symptoms, leading to more complex issues upon seeking help. Consequently, this increase in complexity places greater strain on support networks, diminishing resources available for others, increasing overall wait times and resulting in higher expenses. And don’t even get us started on the expenses! The Australian Bureau of Statistics found that the average person with a mental health disorder will spend approximately $3,200 a year on mental health services, while those with more severe mental illness will spend upwards of $5,600 a year. For many people, this is a tremendous obstacle for seeking support.
When we confront the reality of mental health service challenges, it can feel overwhelming. However, this is exactly where Artificial Intelligence (AI) emerges as a potential solution – offering time-efficient, free and easily accessible support to anyone, anywhere. AI is a broad term that encompasses technologies that are capable of performing tasks that typically require human intelligence, such as learning, problem-solving and decision-making. In the mental health industry, AI can aid in breaking down financial, geographical, socio-economic and time barriers that often discourage people from seeking support. By making effective help available to everyone, AI gives people the power to take control of their mental well-being, no matter where they are, how much money they have or how much mental health knowledge they have.
The Algorithm Always Knows
So, AI can reduce financial, geographical and time barriers, but what can it actually do to help mental health practitioners? Well, preliminary research using AI, has found it can be a time-efficient, cost-effective and highly accurate diagnostic tool. A recent study demonstrated the effectiveness of an AI algorithm in diagnosing mental health conditions based on social media activity alone. The AI tool analysed linguistic cues and behavioural patterns from Twitter posts, achieving a diagnostic accuracy of around 70-80% for conditions like depression and PTSD. This accuracy rate is comparable to some human-driven diagnostic tools, that are the current industry standard. Similarly, researchers using AI to analyse patient electronic health records had an 83% accuracy rate of predicting mental health crises before they occurred. This finding could be the key to revolutionising the way we treat mental health illnesses and disorders. Instead of supporting those in need after a mental health crisis, we could potentially prevent them altogether.
Research has shown time and time again that early intervention is crucial for prevention the progression of mental health disorders and improving long-term outcomes. However, humans are slow, and our diagnostic tools require immense effort, a decent degree of intelligence in the patient and money. Even then, human analysis finds it difficult to identify early warning signs of mental illness, hence we are often treating disorders rather than preventing them altogether. AI can monitor and detect subtle changes in behaviour and mood, providing early warnings that might otherwise go unnoticed.
For example, researchers using an AI-based app analysed user interactions and self-reported data to identify early signs of depression and anxiety, offering coping strategies and alerts for professional help. This resulted in a significant reduction in symptom severity among users. Similarly, another study found an AI-driven platform that monitored students’ digital footprints to predict and intervene in mental health issues, leading to decreased anxiety and depressive symptoms among participants. Identifying potential for mental illness early, not only will improve outcomes for individuals, but lower overall costs for support and lower demand for face-to-face therapy.
Additionally, once AI programs have identified potential mental health concerns, its power can be harnessed to create tailored programs and goals within seconds. Something that can often take many therapy sessions to figure out when relying on human skill alone. In fact, GPs in the United States are already using AI to assess symptoms, reveal health concerns and implement tailored treatment plans for patients, in less than a minute.
A Computer as my Counsellor?
Impersonal. Cold. Mechanical. That’s probably what comes to mind when you think of AI for therapy. In fact, you might be wondering who would ever want a computer as their counsellor. Well, we already have AI-driven therapy platforms that have accrued millions of users, such as Woebot and Wysa, that offer instantaneous, personalised 24/7 access to mental health support. Now, it is important to note that we are not suggesting you never speak to a human counsellor again, however, AI-driven therapy programs are a useful tool for interim support and can be accessed anywhere, anytime and by anyone. These AI-therapy programs utilise cognitive-behavioural therapy, to reduce symptoms of mental disorders and illnesses and have been shown to effectively reduce symptoms.
A randomised controlled trial assessed the effectiveness of Woebot, an AI-driven chatbot, for managing symptoms of anxiety and depression. The study found that users who interacted with Woebot experienced a significant reduction in symptoms compared to the control group, demonstrating the potential of AI-based therapeutic interventions. Similarly, users who accessed Wysa, over a 12-period, were found to have reduced symptoms of depression and anxiety, comparable to traditional counselling results. AI-programs like these, could be the answer for individuals who can’t afford traditional support, for those who live in regional areas with little access to support, or for those individuals who are high risk and need access to support 24/7. Not only would this reduce the strain on traditional therapists, but users of programs like these do not need any expertise in mental health to reap the benefits.
AI Develops Me?
AI isn’t just helping patients; it’s also enhancing the skills of mental health professionals. AI-driven platforms can offer realistic training simulations, provide insights into patient behaviour, and suggest personalized treatment plans. This improves the quality of care and helps professionals stay updated with the latest therapeutic techniques and research.
Researchers in a recent study explored AI training simulations for mental health professionals, showing significant improvements in diagnostic accuracy and therapeutic skills. Additionally, another study used AI to analyse therapy sessions, identifying effective strategies and outcomes, which were then used to develop continuous education modules for therapists, leading to better patient results.
What does it all Mean?
AI is not a replacement for your therapist, and it never should be. However, it’s potential to revolutionise and support an industry that is overwhelmed by its need, is undeniable. AI-driven tolls can significantly reduce barriers to support, such as cost, geography, long wait times and offers accessible, efficient and personalised support to a broader audience. By harnessing AI for early diagnosing, monitoring and interim support, we can improve mental health outcomes and alleviate the burden on existing healthcare systems.
As technology continues to advance, the integration of AI in mental health care promises a future where effective and efficient support is within reach for all, empowering individuals to manage their wellbeing proactively. All in all, AI is not something we should be scared of; it is a tool for us to maximise our ability to support those who need it most.
Resources
- https://s3-ap-southeast-1.amazonaws.com/ap-st01.ext.exlibrisgroup.com/61SCU_INST/storage/alma/64/89/BE/CA/CA/CB/55/EA/B4/D1/70/97/96/29/37/81/Systematic%20review%20on%20service%20linkages%20in%20primary%20mental%20health%20ca.pdf?response-content-type=application%2Fpdf&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240528T230807Z&X-Amz-SignedHeaders=host&X-Amz-Expires=119&X-Amz-Credential=AKIAJN6NPMNGJALPPWAQ%2F20240528%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Signature=130a665b0f6aa3829d5fc7571014823de2694a2817239c2a69d8f5caa413c049
- https://www.aph.gov.au/About_Parliament/Parliamentary_Departments/Parliamentary_Library/pubs/rp/rp1819/Quick_Guides/MentalHealth
- https://mental.jmir.org/2017/2/e19
- https://www.researchprotocols.org/2022/3/e36910/
- https://www.tandfonline.com/doi/full/10.1080/02813432.2021.1973255
- https://www.researchgate.net/profile/Mohamed-Abouhawwash/publication/366893106_Deep_Learning_for_Depression_Detection_Using_Twitter_Data/links/6477ef1bd702370600c51dda/Deep-Learning-for-Depression-Detection-Using-Twitter-Data.pdf
- https://ieeexplore.ieee.org/abstract/document/10510456
- https://ieeexplore.ieee.org/abstract/document/9785250
- https://link.springer.com/article/10.1007/s11920-023-01438-4
- https://link.springer.com/article/10.1007/S11920-019-1094-0
- https://www.sciencedirect.com/science/article/abs/pii/S2352250X2030049X
- https://mental.jmir.org/2018/4/e64/
The Benefits of AI in Mental Health Services
Mental health services in Australia have faced significant challenges, particularly in the aftermath of the Covid-19 pandemic. With a higher demand for talk-based therapies, long waiting times for face-to-face consultations have become a major issue. In fact, a report by the Australian Institute of Health and Welfare found that the average Australian seeking help can wait up to six months for an initial appointment. Research spanning thousands of studies shows that prolonged waits for support can exacerbate symptoms, leading to more complex issues upon seeking help. Consequently, this increase in complexity places greater strain on support networks, diminishing resources available for others, increasing overall wait times and resulting in higher expenses. And don’t even get us started on the expenses! The Australian Bureau of Statistics found that the average person with a mental health disorder will spend approximately $3,200 a year on mental health services, while those with more severe mental illness will spend upwards of $5,600 a year. For many people, this is a tremendous obstacle for seeking support.
When we confront the reality of mental health service challenges, it can feel overwhelming. However, this is exactly where Artificial Intelligence (AI) emerges as a potential solution – offering time-efficient, free and easily accessible support to anyone, anywhere. AI is a broad term that encompasses technologies that are capable of performing tasks that typically require human intelligence, such as learning, problem-solving and decision-making. In the mental health industry, AI can aid in breaking down financial, geographical, socio-economic and time barriers that often discourage people from seeking support. By making effective help available to everyone, AI gives people the power to take control of their mental well-being, no matter where they are, how much money they have or how much mental health knowledge they have.
The Algorithm Always Knows
So, AI can reduce financial, geographical and time barriers, but what can it actually do to help mental health practitioners? Well, preliminary research using AI, has found it can be a time-efficient, cost-effective and highly accurate diagnostic tool. A recent study demonstrated the effectiveness of an AI algorithm in diagnosing mental health conditions based on social media activity alone. The AI tool analysed linguistic cues and behavioural patterns from Twitter posts, achieving a diagnostic accuracy of around 70-80% for conditions like depression and PTSD. This accuracy rate is comparable to some human-driven diagnostic tools, that are the current industry standard. Similarly, researchers using AI to analyse patient electronic health records had an 83% accuracy rate of predicting mental health crises before they occurred. This finding could be the key to revolutionising the way we treat mental health illnesses and disorders. Instead of supporting those in need after a mental health crisis, we could potentially prevent them altogether.
Research has shown time and time again that early intervention is crucial for prevention the progression of mental health disorders and improving long-term outcomes. However, humans are slow, and our diagnostic tools require immense effort, a decent degree of intelligence in the patient and money. Even then, human analysis finds it difficult to identify early warning signs of mental illness, hence we are often treating disorders rather than preventing them altogether. AI can monitor and detect subtle changes in behaviour and mood, providing early warnings that might otherwise go unnoticed.
For example, researchers using an AI-based app analysed user interactions and self-reported data to identify early signs of depression and anxiety, offering coping strategies and alerts for professional help. This resulted in a significant reduction in symptom severity among users. Similarly, another study found an AI-driven platform that monitored students’ digital footprints to predict and intervene in mental health issues, leading to decreased anxiety and depressive symptoms among participants. Identifying potential for mental illness early, not only will improve outcomes for individuals, but lower overall costs for support and lower demand for face-to-face therapy.
Additionally, once AI programs have identified potential mental health concerns, its power can be harnessed to create tailored programs and goals within seconds. Something that can often take many therapy sessions to figure out when relying on human skill alone. In fact, GPs in the United States are already using AI to assess symptoms, reveal health concerns and implement tailored treatment plans for patients, in less than a minute.
A Computer as my Counsellor?
Impersonal. Cold. Mechanical. That’s probably what comes to mind when you think of AI for therapy. In fact, you might be wondering who would ever want a computer as their counsellor. Well, we already have AI-driven therapy platforms that have accrued millions of users, such as Woebot and Wysa, that offer instantaneous, personalised 24/7 access to mental health support. Now, it is important to note that we are not suggesting you never speak to a human counsellor again, however, AI-driven therapy programs are a useful tool for interim support and can be accessed anywhere, anytime and by anyone. These AI-therapy programs utilise cognitive-behavioural therapy, to reduce symptoms of mental disorders and illnesses and have been shown to effectively reduce symptoms.
A randomised controlled trial assessed the effectiveness of Woebot, an AI-driven chatbot, for managing symptoms of anxiety and depression. The study found that users who interacted with Woebot experienced a significant reduction in symptoms compared to the control group, demonstrating the potential of AI-based therapeutic interventions. Similarly, users who accessed Wysa, over a 12-period, were found to have reduced symptoms of depression and anxiety, comparable to traditional counselling results. AI-programs like these, could be the answer for individuals who can’t afford traditional support, for those who live in regional areas with little access to support, or for those individuals who are high risk and need access to support 24/7. Not only would this reduce the strain on traditional therapists, but users of programs like these do not need any expertise in mental health to reap the benefits.
AI Develops Me?
AI isn’t just helping patients; it’s also enhancing the skills of mental health professionals. AI-driven platforms can offer realistic training simulations, provide insights into patient behaviour, and suggest personalized treatment plans. This improves the quality of care and helps professionals stay updated with the latest therapeutic techniques and research.
Researchers in a recent study explored AI training simulations for mental health professionals, showing significant improvements in diagnostic accuracy and therapeutic skills. Additionally, another study used AI to analyse therapy sessions, identifying effective strategies and outcomes, which were then used to develop continuous education modules for therapists, leading to better patient results.
What does it all Mean?
AI is not a replacement for your therapist, and it never should be. However, it’s potential to revolutionise and support an industry that is overwhelmed by its need, is undeniable. AI-driven tolls can significantly reduce barriers to support, such as cost, geography, long wait times and offers accessible, efficient and personalised support to a broader audience. By harnessing AI for early diagnosing, monitoring and interim support, we can improve mental health outcomes and alleviate the burden on existing healthcare systems.
As technology continues to advance, the integration of AI in mental health care promises a future where effective and efficient support is within reach for all, empowering individuals to manage their wellbeing proactively. All in all, AI is not something we should be scared of; it is a tool for us to maximise our ability to support those who need it most.
Resources
- https://s3-ap-southeast-1.amazonaws.com/ap-st01.ext.exlibrisgroup.com/61SCU_INST/storage/alma/64/89/BE/CA/CA/CB/55/EA/B4/D1/70/97/96/29/37/81/Systematic%20review%20on%20service%20linkages%20in%20primary%20mental%20health%20ca.pdf?response-content-type=application%2Fpdf&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20240528T230807Z&X-Amz-SignedHeaders=host&X-Amz-Expires=119&X-Amz-Credential=AKIAJN6NPMNGJALPPWAQ%2F20240528%2Fap-southeast-1%2Fs3%2Faws4_request&X-Amz-Signature=130a665b0f6aa3829d5fc7571014823de2694a2817239c2a69d8f5caa413c049
- https://www.aph.gov.au/About_Parliament/Parliamentary_Departments/Parliamentary_Library/pubs/rp/rp1819/Quick_Guides/MentalHealth
- https://mental.jmir.org/2017/2/e19
- https://www.researchprotocols.org/2022/3/e36910/
- https://www.tandfonline.com/doi/full/10.1080/02813432.2021.1973255
- https://www.researchgate.net/profile/Mohamed-Abouhawwash/publication/366893106_Deep_Learning_for_Depression_Detection_Using_Twitter_Data/links/6477ef1bd702370600c51dda/Deep-Learning-for-Depression-Detection-Using-Twitter-Data.pdf
- https://ieeexplore.ieee.org/abstract/document/10510456
- https://ieeexplore.ieee.org/abstract/document/9785250
- https://link.springer.com/article/10.1007/s11920-023-01438-4
- https://link.springer.com/article/10.1007/S11920-019-1094-0
- https://www.sciencedirect.com/science/article/abs/pii/S2352250X2030049X
- https://mental.jmir.org/2018/4/e64/