{"id":44526,"date":"2022-06-09T08:50:55","date_gmt":"2022-06-09T12:50:55","guid":{"rendered":"https:\/\/www.kaspersky.com\/blog\/?post_type=emagazine&p=44526"},"modified":"2022-07-27T06:44:03","modified_gmt":"2022-07-27T10:44:03","slug":"mental-health-therapy","status":"publish","type":"emagazine","link":"https:\/\/www.kaspersky.com\/blog\/secure-futures-magazine\/mental-health-therapy\/44526\/","title":{"rendered":"Could AI make mental health therapy more effective?"},"content":{"rendered":"

Artificial intelligence (AI) can analyze vast amounts of data more quickly than humans and draw accurate conclusions, making for myriad business applications. But now, some technologists and mental healthcare clinics are using artificial intelligence (AI) to inform mental health therapy<\/a>. They think it could help pinpoint the most effective strategies to help sufferers get better. This may mean better staff retention and productivity and greater value for money from employee assistance programs for business.<\/p>\n

UK-based mental health clinic Ieso<\/a> and US-based mental health technology firm Lyssn<\/a> are among those experimenting with AI-augmented therapy.<\/p>\n

Why mental health is harder to treat<\/h2>\n

I spoke with Valentin Tablan, Chief AI Officer at Ieso. He says while physical healthcare has MRIs, CAT scanners and hundreds of blood tests to diagnose conditions, \u201cIn mental healthcare, we\u2019ve been slower to adopt technology. But that\u2019s changing. We can start using artificial intelligence and natural language processing techniques to understand therapy-specific language and gain insights from that.\u201d<\/p>\n

Ieso uses AI to analyze transcripts of patient-therapist conversations to identify which elements of therapy give the best outcomes, identify cases that may need a more experienced therapist and help evaluate the quality of care. They\u2019re also working on a cognitive behavioral therapy (CBT) companion app that supports patients in between therapy sessions.<\/p>\n\t\t\t

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Games in mental health<\/p>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t

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How two friends combined their experience to create a unique way for more people to get mental health help.<\/p>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t

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Lyssn also uses AI to evaluate the quality of psychotherapy and give therapists actionable feedback.<\/p>\n

Practitioners hope to increase recovery rates and quality of care to bring it on par with physical healthcare\u2019s higher recovery rates. Ieso has seen recovery rates increase 2 percent alongside its AI program \u2013 small but encouraging.<\/p>\n

AI no replacement for therapists<\/h2>\n

\u201cPsychotherapy\u2019s quality is usually measured by experts observing a conversation. Our AI is trained to replicate this human judgment, reducing the cost and time to evaluate the conversation,\u201d says Zac Imel, chief science officer and co-founder of Lyssn.<\/p>\n

These solutions aren\u2019t meant to replace traditional therapy but to provide an evidence-based way to improve therapy\u2019s quality and accessibility.<\/p>\n<\/blockquote>\n

More accessible, AI-powered forms of therapy include chatbots<\/a>. These can help support patients between sessions, collect useful data and provide emotional support to people who cannot access therapy because of stigma, time or financial reasons. Chatbots simulate a conversation between humans, using AI to learn from examples of real conversations. The AI in this case is often trained on therapy session transcripts. It replicates how a therapist would respond to a patient with some accuracy.<\/p>\n

UK\u2019s National Health Service (NHS) says up to 8 million people in England want to access mental health treatment but do not qualify for it<\/a>. High costs, long waiting lists and not wanting to unburden themselves to a stranger also keep people away from therapy.<\/p>\n

\u201cOne barrier to providing care to more people is that CBT, the most common evidence-based treatment for depression, is hard to teach. Having tools to speed up the training would help,\u201d Dr. Paola Pedrelli, Assistant Professor of Psychology at Harvard Medical School, told me. Additionally, supervisors usually evaluate and provide feedback to therapists in training, but there isn\u2019t always the time or resources. AI could bridge that gap.<\/p>\n

Pedrelli is part of a team that worked on a project using machine-learning algorithms to diagnose and monitor major depressive disorder<\/a>. \u201cSometimes treatment takes months to work. Tools to speed the process would be beneficial,\u201d she added.<\/p>\n

AI\u2019s advantage over the human brain<\/h2>\n

AI\u2019s biggest advantage over the human brain is being fast and reliable at analyzing data, said Imel of Lyssn. AI can quickly analyze, process and gain insight from large data sets, making it a powerful tool in mental healthcare where markers of recovery are vague.<\/p>\n

\u201cWith repetitive tasks, humans get tired and can drift over time. And if you show a human the same conversation twice, they might evaluate it differently. With AI \u2013 same data in, same answer out,\u201d Imel says.<\/p>\n

How AI-powered mental health can help employees<\/h2>\n

AI-based therapy tools like Ieso\u2019s CBT companion app<\/a>, Ellie<\/a>, Woebot<\/a> designed by Institute for Creative Technologies (ICT) at the University of Southern California, The Trevor Project\u2019s Crisis Contact Simulator<\/a> and others cannot replace human therapists but help improve access and reduce cost.<\/p>\n

In a randomized, controlled trial of 70 participants, Woebot users displayed a significant decrease in depression symptoms<\/a> compared with the control group. Both groups showed a decrease in anxiety.<\/p>\n

Those experiencing mental distress or stress at work could be directed to therapy bots as a bridge between needing therapy and getting access to it. Chatbots can also gather data about how a patient feels and suggest clinical intervention where required. Organizations considering employee access to therapy bots should consult an expert and make sure therapy is available alongside these solutions rather than as a substitute.<\/p>\n

Privacy and security in AI-powered therapy<\/h2>\n

Alongside benefits, AI-powered therapy programs come with obvious cybersecurity and privacy risks. Sensitive and private conversations between patients and therapists could be exposed or manipulated. Iron-clad security is the first step to protecting patient privacy.<\/p>\n

Tablan and Imel shared the importance of data security to their companies and how they keep patient data safe, such as using multiple layers of security and robust security certifications. \u201cMost people working at Ieso can\u2019t access this data. It\u2019s accessible to computers, but few humans,\u201d said Tablan.<\/p>\n

All data is encrypted, and we go beyond basic security standards. We also de-identify data by removing metadata and in-session identifiable information, so we cannot link conversations with speakers.<\/p>\n

Zac Imel, Co-founder and Chief Science Officer, Lyssn<\/p><\/cite><\/blockquote>\n

Even with the strongest security practices, risks to patient privacy still exist, as a lot depends on humans who can access the data. But those involved believe the potential benefits of AI-powered therapy outweigh the risks.<\/p>\n

AI-augmented, not AI-based therapy<\/h2>\n

There\u2019s much to suggest unconscious bias is present in the therapy room as in other parts of life. Black and minority ethnic people are less likely to find counseling fit for purpose<\/a>. Lesbian, gay and bisexual people also report greater dissatisfaction with counseling<\/a> and psychotherapy than their heterosexual counterparts. When AI programs can imbibe biases in data used to train them, there must be concerns that AI-based outcomes could further marginalize some patients.<\/p>\n

Dr. Tonya Davis<\/a>, faculty member at Northwestern University, Illinois, suggests \u201cunconscious biases<\/a> \u2013 things hidden just beneath the surface of our awareness\u201d might impact training AI chatbots. \u201cI think that if there is a deliberate effort to identify, understand and resolve biases beneath the surface of our awareness, we could be one step closer to addressing the cultural challenges in person-to-person interactions, thereby minimizing these challenges in the development of AI.\u201d<\/p>\n

Pedrelli said, \u201cThere have been cases where AI has provided inappropriate directions in the context of therapy. And AI is still unable to detect subtle emotional changes.\u201d<\/p>\n

However, AI tools only augment diagnosis and therapy. They shouldn\u2019t be relied on for unilateral decisions on patient care.<\/p>\n

\u201cThe tools we\u2019ve built look over our quality of care \u2013 they never make any decisions automatically,\u201d said Tablan. \u201cThey just present information to a qualified clinician who has access to the transcripts and make up their own minds.\u201d<\/p>\n

Imel doesn\u2019t describe what Lyssn does as \u201cAI-based therapy.\u201d Instead, he says, \u201cThis is about using technology to augment the human talent of therapists. So, it\u2019s human-based therapy, augmented by AI.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

Mental healthcare has more uncertainty than physical healthcare, but now artificial intelligence may help make it more measurable and effective.<\/p>\n","protected":false},"author":2644,"featured_media":44527,"template":"","coauthors":[4159],"class_list":{"0":"post-44526","1":"emagazine","2":"type-emagazine","3":"status-publish","4":"has-post-thumbnail","6":"emagazine-category-artificial-intelligence","7":"emagazine-category-emerging-tech","8":"emagazine-category-tech-for-good","9":"emagazine-tag-employee-assistance","10":"emagazine-tag-mental-health"},"hreflang":[{"hreflang":"x-default","url":"https:\/\/www.kaspersky.com\/blog\/secure-futures-magazine\/mental-health-therapy\/44526\/"},{"hreflang":"en-us","url":"https:\/\/usa.kaspersky.com\/blog\/secure-futures-magazine\/mental-health-therapy\/26589\/"}],"acf":[],"_links":{"self":[{"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/emagazine\/44526","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/emagazine"}],"about":[{"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/types\/emagazine"}],"author":[{"embeddable":true,"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/users\/2644"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/media\/44527"}],"wp:attachment":[{"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/media?parent=44526"}],"wp:term":[{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.kaspersky.com\/blog\/wp-json\/wp\/v2\/coauthors?post=44526"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}