Dr. Frank Iorfino: Can AI Solve the Youth Mental Health Crisis?

Bianca: Hi, welcome to the In Our Minds podcast. I'm your host Bianca, CEO of Innowell. In this episode, I'm going to be speaking to Dr. Frank Iorfino, who is the associate professor at the Brain and Mind Centre at Sydney University. So, today we're going to cover what's going on in youth mental health, some of the challenges that are facing youth, and just the mental healthcare system in general. And finally, what are some of the digital tools and solutions including AI that we're seeing can actually make a huge difference in this space. So, Frank, let's get into it. Can you tell us a little bit about your history, your background and how you came to being in your role as associate professor at the BMC?

Frank: Yeah, so my background is actually in psychology and neuroscience. And then I became really interested in the youth mental health space during my PhD, and that was the focus of my PhD. During my PhD I really focused on functional outcomes for young people — so people going to headspace and other youth mental health services, really interested in who was at risk for functional impairment, and what were the outcomes of those attending these services, with really the goal of trying to improve the quality of mental healthcare. But then halfway through my PhD I became really interested in digital solutions as part of how they then help us in the youth mental health fight. And so the second half of my PhD was focused on digital solutions, measurement-based care. How do we digitise a lot of that measurement and provide clinicians and young people with much more information about their outcomes over time? How do we visualise that and how do we use that for more effective care? And so that led me, post-PhD, to be working very closely with health services, with clinicians, with young people with lived experience, to continue to add to the kind of arsenal of tools that we have to improve prediction of mental health, understand mental health and mood disorders more specifically in much more detail, and provide more effective care. So that's the journey I've been on for the last 10 years or so.

Bianca: So, safe to say you've pretty much spent your majority, if not your entire career, in mental health. So in terms of specialists in the area, I think we have the right person here on the couch with me today. I was going to say, and you've obviously seen a lot in that time, particularly with all the research papers that you've published. So what was it, when you were doing your studies, that really drew you to youth mental health care specifically?

Frank: Well, I've worked with Professor Ian Hickie at the Brain and Mind Centre, and he's a leader in the youth mental health space, so I suppose he kind of guided the direction. But we saw, as part of the studies that I had been doing, we became really aware of the huge youth mental health problem — most disorders emerge before the age of 25, so major depression and these things tend to emerge in adolescence for the first time. And so there's a huge need, and that impact during adolescence can have a huge impact on people's lives. It's a critical time when they're supposed to be developing careers, and critical years for education and developing social relationships. And so it's a huge opportunity for impact if we can make a difference in that youth period.

Bianca: So what are the problems that you're currently seeing, Frank, in your research specific to the youth mental health crisis?

Frank: So there are really two things going on at the same time. One is, as I've mentioned, we know that youth mental health problems emerge before the age of 25 — most emerge before that period, but I think in society today we're seeing so many changes in terms of technology and social media and other kinds of impact. So there's a lot of ambivalence in young people, and so those kinds of things may be contributing to increases in the prevalence of disorders during that period, and so there's lots of research trying to unpack why we are seeing an increase in youth mental health problems worldwide, because we are seeing that increase in prevalence. So that's one aspect of the problem. The second is around healthcare, and so access to healthcare more specifically. So we're seeing long wait times for care — for example, wait times to see a psychiatrist have tripled in the last decade, for example. And that's worse for people in regional and rural areas. We know that while people are waiting for care, they tend to engage in maladaptive behaviours and increases in distress. So that wait time can have really big impacts on people. So it's those two things happening at the same time — we're seeing major problems in youth and what they have to face in society and in their daily life, and unfortunately healthcare isn't able to keep up because of workforce shortages and not being able to have enough clinicians to provide that access and effective care.

Bianca: And I've seen that, whether you're talking to headspace centres, particularly in regional sorts of areas, where I think the challenge is actually getting — it could be retention, it could be hiring, it can be all sorts of different challenges because obviously there's mobility that happens in regional areas — and also in areas like Canada, for instance, we see similar challenges, I think, between the two countries. What are the ways and what are some of the solutions that you're seeing that can help address these challenges? If I think about an example — you mentioned those long wait times, how you can sort of help triage people faster — and I think of it like a casualty ward: when you walk into RPA and it's usually jammed with people on a Saturday night because there's always lots of things going on, but people can be waiting for hours and hours and hours. And so the same thing exists when it comes to mental health, but it may not be as visceral because, as you said, it can be hidden in different ways. What are some of the technology solutions that you're seeing out there, and ways that we can assist with that triaging?

Frank: We've done a lot to try and address these kinds of youth mental health problems. We often go to the things we know that have worked in the past — more services, more clinicians, because there is a workforce shortage that is a very real problem. So it would seem like part of the solution is more people, which is one side of addressing that problem, but we definitely need smarter solutions because a lot of work has shown that we can double or triple the workforce and we're never going to be able to meet the demand. And so part of the solution is smarter ways of identifying the needs of people — so using smarter assessments, using AI for example, that can be available more widely to help people identify their own needs, and then be directed to or helped to navigate to the right in-person service, or it might be an online service, or it might be a combination of the two. So it's called a "digital front door" — a term now which really just means, okay, let's use digital technologies to make a front door to our health system, or a mental health system, and make that widely accessible for people, so that instead of bouncing around from service to service trying to find what they need, they can be directed straight to the kind of service that should meet their needs.

Bianca: Absolutely, and I've heard that just through talking to some of our clients. I think it's really interesting whether you refer to it as step-care models — and there are different services that exist across Australia, and obviously in other organisations in Canada as well — but I think it's around, as you were saying, what are the things that we can do, because not everyone necessarily has a high — I'm going to say like high needs or high risk in terms of suicidality from a mental health perspective — so they might be more of a lower risk, and what I mean by that is their needs can actually take a little bit of pressure off the system if you can sort of triage them effectively using digital tools and the digital front door, to sort of say, "well look, Bianca, you know, your anxiety might be a little bit lower today, or here are some options that mean that you may not need to see a therapist or a psychologist immediately," but there's someone who's experiencing manic-like behaviour, psychosis, that we're going to need to really jump them to the top of the queue. And I've loved seeing, through the research at the Brain and Mind Centre, how you're helping clinicians to be able to identify these risks early. You think about smart triaging to help with that digital front door — it's like, rather than going and sitting in casualty for the next five hours, let's actually fast-track you so you can see someone, but you're a bit more low-need, so here's some CBT courses or some ideas that are probably going to help you be more self-managed. That's probably one way of thinking about it — there's two different extremes I think that we could look at here as well.

Frank: Yeah, that's right. In our research we're trying to address this problem — we know that there's clinical services, so if people go and see a psychologist or a psychiatrist, there's also psychosocial services — they might need housing support, they might need support re-engaging with school or education or work, for example. And then there's also physical health problems that people might have, or drug and alcohol support they might need. So if you think about it, those are the different options available for care, and there's obviously digital versions of all of those things too. And so part of what one of our studies tried to do was to go, okay, how could we identify needs across those different dimensions? And so we were trying to identify who has high or low clinical needs that might be addressed by a psychologist, who might have high or low psychosocial needs across that dimension, and then who might have high or low physical health, or drug and alcohol needs. And so when we did that study — and that was in over 1,700 people — we realised we could triage or direct people to the right kinds of services that met their needs. So some people might just need clinical support with very little psychosocial support — so that's one clear pathway we could direct people to. Or some people needed much more intensive interventions across clinical and psychosocial support, so they need maybe a psychologist and a social worker involved in their care. So by doing this kind of work, we could try and identify and help the health system figure out where people need to be. And many of the people, as you pointed out, there was a portion of people, maybe about 20%, that could self-care — so they could be directed to digital solutions and treat or manage their own mental health on their own for a little while, and see how that goes.

Bianca: Awesome, that's helpful. Cool. So Frank, we think about it in terms of — it's been built by clinicians for clinicians — and the phrase that is often used is measurement-based care, or evidence-based care. For anyone who hasn't heard that phrase before, because it's still relatively not as well known as I think it is in certain jurisdictions around the world, how would you describe what measurement-based care actually is?

Frank: So at a basic level, measurement-based care is really about routine outcome monitoring, and at an even more simple level it's about regular assessment of people's symptoms, their functioning, and its impact. So you typically would use questionnaires — there might be a depression scale that measures depressive symptoms, and you're regularly administering that assessment, so you're tracking their outcomes over time. So at week one they might be at a very severe level, at week two they might still be severe, and then you see the progress over time — at week six they might have got better and now be at a moderate or mild level. So it's about tracking those symptoms over time, and that measurement is informing care decisions — is a treatment working or not, is this person getting better or not. And if you compare that to the alternative — the lack of those measures in care — there's often a reliance on intuition, or "oh yeah, this person seems better compared to when I saw them at the start." So there's much more reliance on subjective judgments about improvement over time. And so it's really the contrast between that kind of subjective use of information to judge whether treatment is working or not, and moving away from that to more objective measures, validated scales and questionnaires, to try and understand is this treatment effective, is this treatment working or not.

Bianca: And I think it's like — you go to the doctor, you go to the GP, and the first thing they do is they'll take your blood pressure, or they'll check your heart rate, all that sort of stuff, and then we've normalised that measurement in so many different aspects of medicine, whether it's diabetes management, checking insulin levels, blood sugar levels, all those sorts of things. And so we already have forms of measurement-based care normalised, that when it comes to mental health it's like "oh well, this is different," but you think, not really, because even if you're going to the gym and you're tracking that you're doing strength training and you're lifting five kilos, six kilos, it's the same thing, because we do it in so many other aspects of our life, yet there's still — I still think that there's this stigma that exists around how do we measure the progress of mental health, but this is really what measurement-based care or evidence-based care enables us to do.

Frank: Absolutely, and I can understand why as well — like, people don't like reducing mental health down to a score, right? You don't want to just be defined by a score, or nine out of ten. So I can understand why some people don't like that — they feel like it's too much data, it's too impersonal, or it's not a humanistic kind of approach, or person-centred approach to care. So I completely understand that, but at the same time we need to understand whether something is working or not, and you don't really understand that unless you're tracking what it is you're trying to change. So if you're trying to improve someone's functioning, you want them to get back to school, for example, or get back to university, you need to understand and track whether that's happening or not. You want to reduce someone's avoidance in anxiety — so maybe someone's not leaving the house, so you're trying to reduce their anxiety and improve that behaviour of avoidance, for example. So we're doing this all the time, and clinicians are doing this all the time too. So measurement-based care is really about the formalisation of that, and trying to use tools to quantify whether that's occurring or not.

Bianca: Awesome, and I think of the alternative, right — so I caught up with a girlfriend recently, and she's seeing a psychologist who doesn't leverage any digital tools, and she was saying to me, "I'm sitting across the table in a very traditional clinical setting with a psychologist, and he's writing his notes, but I can't see what he's writing." And it's very subjective, and so for her she's like, "I don't know, am I getting better, am I not getting better, I feel like I'm getting better," but she obviously wants that data as well. So it's really interesting because I think from a client/patient's perspective, there's a lot of people who also want that visibility and are looking for that guidance from their clinical professional to say, "hey, help show me how I'm actually improving or declining, or what's working or what's not."

Frank: It's so interesting you say that, because going back ten years, when this all started, one of the early projects I worked on as part of my PhD — this really was a lived-experience-driven kind of initiative, because it was about taking back some of the power and empowering individuals to be more active agents in their care. So exactly as you just pointed out, there's a lot in healthcare where it's like, okay, well the clinician takes all the notes, they have all the information, the power — and so it was really a lived-experience kind of driven thing of saying, "well, I need to have visibility of what's going on for me, how am I tracking." And so that's why, in the platform in particular, one of the early principles was about making a shared platform or shared dashboard that was seen by clinicians and by young people, so that they're both working from the same information to then make decisions together about, am I improving, is this effective, and all those kinds of things. So it was about empowering people, and that was driven by lived experience and what they were telling us in our research.

Bianca: And I think that transparency — when you think about you're working with your healthcare team, if you've got a team of people, and ultimately depending on what symptoms or challenges people are dealing with, they're going to have different specialists and different people that they use for different aspects of their life — but I think the concept of that transparency is really powerful, because not only can you share that with other people that are a part of your health network, for lack of a better term, but I think it's also just it shows that there's nothing to hide, and that's the thing, I think we all want us to move towards being able to destigmatise mental health. And I think by being really open and transparent, that's a really great step in being able to do that, because the stigma is no longer "well, what did my therapist write down, or what did my clinician write down about me that I can't see" — it's like, well actually, no, let's look at the data together and we can see it and work collaboratively together to improve those health outcomes for that individual.

Frank: Yeah, that's right, and it gives them power to find, if they're looking for something else, if they're not quite having their needs met, they can go and search for that. But it's about — you need to understand where you started and where, how you're tracking, to be able to make those decisions effectively, the journey that you're on. I think the research that you've all done in sort of building around the clinical assessments and the detail, that's what I've loved about just understanding this world where we go so deep on so many different areas and different health domains, that what it can often uncover is things that people may not necessarily feel comfortable actually bringing up in their first consultation. So I think it also helps to sort of just unpack some of the things that people are working through, to then surface those insights through that measurement-based care. It's obviously measuring, but once you know what you're working with, then you can actually go, let's look at this data, let's see what it's surfacing, and then prioritise those areas that are important to the individual.

Bianca: Totally. I mean, if you think about what has happened in the past without this kind of approach, is that you might have a one-hour appointment, which you're paying pretty high costs for, so you're trying to remember everything that you need to tell your clinician, but then you're also trying to get treatment at the same time, often — so that's a lot to pack into a one-hour session. So we're trying to supplement that now with routine measures collected before a session, so you can clearly see going into the session, "oh, I've been getting better over the past week," and so then that session becomes about contextualising what's been contributing to that improvement, for example. And so you now just have more information to do the treatments and inform those treatments. And people often push back on there being an over-reliance on data, or these measures — I think I see it differently, I see it as there isn't really just one source of truth. There's validated questionnaires and measures, there might be information coming from wearables, and then there's also the subjective view as well, and you need to try and use all of that information to then make an informed decision — it's not relying on any one source of truth.

Frank: Yeah, I love that. So Frank, you've touched on AI as being one of the ways to assist with whether it be smart triaging, the digital front door — I know this is a passionate area of yours, you really love identifying what's happening in this space, and it is changing so rapidly. When you think about how rapidly digital health and AI solutions are coming to market, what are you seeing as part of the trends in terms of the research that the Brain and Mind Centre is actually doing, and probably what excites you the most about where AI is heading, because it can be both scary but it's also pretty exciting around how it can help when it's used in the right way as well?

Frank: Yeah, that term AI is an interesting one — I worked with a statistician who once said that AI is just a good marketing term for applied statistics, so it sounds more interesting, because it is such a broad term that includes so many different things. So from one perspective, I started in this space many years ago just in terms of machine learning, and using machine learning to look for patterns in data to try and improve prediction. Our work was focused on things like self-harm and suicidal behaviours — young people presenting to services often do engage in those behaviours, and so we were interested in developing a machine learning model that could be used to predict those particular outcomes, and we showed that it worked to some degree. And we've done similar things for functional impairment — so prediction of functional impairment — and we're doing current work to look at predicting things like bipolar disorder. So that's in the more machine-learning space, using large data sets, large clinical data sets where we track people longitudinally and use machine learning and statistical methods to try and identify who might be at risk. So that's one kind of version of the AI we're talking about, and it has huge utility. But in recent years we've seen the emergence, obviously, of generative AI and large language models, as giving us a new kind of tool to use in a range of different ways. So we've seen things like ambient scribes now that are used to take notes and improve documentation — there's huge gains, I think, in healthcare efficiencies, helping clinicians take off the burden of admin and a lot of that stuff, so that they can really truly focus on clinical care, which is a really exciting area that can't be ignored. And then the other aspect is using AI tools, like we're seeing with ChatGPT and other things, to meet consumers where they're at, in terms of providing them with more information about their own care — they can ask questions about their own mental health and get very personalised answers based on high-quality information. I think one of the things we're focusing on is, rather than relying on just the open internet, where many of the responses might be coming from other forums, we have focused on trying to curate a high-quality mental health knowledge base, which is based on guidelines and the literature and other kinds of clinical information, to really ground responses in clinical evidence. That's going to be a really exciting and interesting space, as we go into the future, where we have high-quality clinical information that can be used to provide people with much more information about their own health situation.

Bianca: Awesome, and I think you mentioned around how things have changed so quickly in relation to even describing services — I think it's probably the most simplistic example I can think of. Think of another example — a friend's husband, he sat down, he saw his GP, he had a list his wife had given him of all the things to go and talk to the doctor about, but for the first time in years, the doctor actually looked at him and spoke to him, because previously the doctor was too busy taking their notes, and just kind of taking notes — but it was so amazing because he actually felt seen and heard, because they had the scribe taking the notes, and that personal connection, as you said — whilst AI, obviously everyone can be a bit dubious about the role that AI can play, it can actually be an enabler because it brings back that human connection. You think about keeping the human in the loop — nothing's ever going to replace an actual human-to-human connection where someone needs that advice from a clinical professional, but I think that's where it can actually free people up in different sorts of ways, and you've already touched on that.

Frank: Yeah, no doubt, I mean we know that when people have an advocate in care, like a family member, or are just really motivated to learn more about their condition and take more information to a doctor, they tend to do better — and this is across healthcare. So I think we're seeing a real emergence of that kind of thing in the AI and mental health space in particular, where consumers are going to be more informed and are going to ask smarter questions that are relevant to them, and even have the tools to track the things that they need to track, to make that contact with their clinician much more effective than it ever has been in the past. So what would have taken maybe months to try and unpack and learn, you could maybe unpack very quickly in a short period of time, now with these kinds of tools that we have available.

Bianca: Absolutely, and I think you also mentioned around some of the knowledge sets that you and the Sydney and Brain and Mind Centre team are actually developing, which I think is really valuable, because when you think around — there's risks and there's rewards with all things AI — and just democratising that type of data and that information, where people have concerns around AI has been around, what are the guardrails, what are the safety measures around it, because you don't want ChatGPT or any of the other AI solutions out there to be giving wrong advice, wrong information, or encouraging people to self-harm — we've all seen those headlines, and obviously we're trying to protect people in those sorts of ways. What I love about some of the work that you're doing, though, is that you're creating these knowledge banks that are actually a great resource for the clinicians to also have a safe space, for lack of a better phrase, to say, "if I've got a patient who's presenting with these types of symptoms, what are some aspects, and how I could help that patient in a different way." Can you share a little bit more about that, because I think that's also something that's very different, because that's actually being built for the clinicians, not necessarily for the consumer or the end client. So how are you seeing that research build out, and what impact do you think that will actually have?

Frank: Well, the premise for the project — it all started with the idea about, what if you had Australia's best psychiatrist? And I work with Professor Hickie, and it was like, could we take what he knows, the expertise that he has in his head, and put that into a digital tool? So that has been one of the guiding principles, because we know, as psychiatrists, there are reports showing that a very high proportion feel unable to provide quality care because they feel that they're overburdened and the workload is too large, and something like 70% are considering leaving the profession in the next three years. So we're facing a bit of a crisis around specialists and expertise. And so the goal for this project has been, could we use AI and digital tools like this to embed clinical expertise and make that widely available? And so that involves having a large knowledge base that is relevant to that domain and that field, and so that's what we've been curating and creating. The other aspect, which you touched on when you were speaking about guardrails, is around nuances of clinical decision-making — and in certain circumstances, when you see certain characteristics, how would an expert clinician respond to that? And so part of what we've been doing is trying to train these systems to respond in a similar way, and that involves responding to and escalating risky kinds of conversations that might get into suicide ideation — how do you escalate that to a human, or how do you escalate that to the right services? But then it moves away from risk, and to more nuanced things, around how to ask the right questions if you suspect someone has a mood disorder — how do you then ask the right sequence of questions, or get the right levels of assessment needed, to then understand if this person is at risk for a mood disorder. So all of those nuances are things that expert clinicians do naturally, through years and years of experience. And so trying to embed that in a digital tool and AI is part of what we're trying to achieve.

Bianca: That's huge, and I think it's really exciting because it's almost like having a coach, or a virtual assistant or a virtual coach that guides that clinician as well. And as you were saying, if it's providing that real-time guidance, and clinical guardrails, I think that could have a huge impact to enable more care, more services, regardless of where you're located.

Frank: Yeah, that's where we see the potential. Well, I mean really it's trying to increase the consistency and quality of care across Australia — so if you think about it, we have people trained in different professions, in psychology or social work or psychiatry, but then you add in they come from different regions, they're in different health settings, so all of these things add to — and then they have their own personal experiences, right — and so that adds to the variability in how they respond to a specific situation. And so that variability leads to differences in the quality of an assessment, or the quality of a recommendation about interventions. And so I think with a lot of these AI tools, we can reduce that variability and increase the quality. So we're saying, okay, clinicians using AI will be able to perform at a higher level, and more consistently, to provide better recommendations. That's the future, and I think that's the path we're on. I think that's the path we should be on, because as you know, expertise is the thing we're lacking, and specialists are the thing we're lacking all across the country, and so trying to address that using AI, I think, is going to be really effective.

Bianca: Yeah, awesome. So with the trends that you're seeing around wearables, and particularly I think that is an area that I've seen — as you know, last year we were both in Toronto at the EIC conference, and I know you were speaking to some Canadian organisations at the time — I'll come back to Canada, but I think one of the things that I heard at that conference was around the impact not only of wearable devices, but the predictive approach — I think, in terms of how tech can actually help predict whether or not someone potentially might be about to have a mental health episode. Is that something that you're seeing as part of the Sydney Uni team and the BMC team, as part of your research? What are those kinds of trends that you and the team are seeing at the moment?

Frank: Yeah, absolutely — I mean, prediction has always been a really big focus, of not just mental health but medicine in general, and so we have been doing that kind of thing for a number of years now. Really, part of my early work was really trying to predict trajectories of functioning — so who is at risk for functional impairment, so being disengaged from school or work, so having major functional impacts of having a mental illness — so trying to identify who those people are early, so that we can allocate resources more effectively, that kind of thing. But prediction is also interesting from the perspective of trying to identify who's at risk for more serious disorders — so maybe a major depressive episode, or something like bipolar disorder. These conditions are really burdensome to people, and can be hard to diagnose and hard to predict early. So focusing on trying to use as much information as we can, from clinical information but also genetics and other cognitive tests, to try and understand who is at risk for those kinds of illnesses. So yeah, prediction is a big part of what we try to do, and it's really about trying to do early intervention or indicated prevention. Because once someone develops something serious, the interventions are more costly, it takes longer for them to recover, it might have impacted their lives already quite significantly. So trying to focus on who's at risk, picking them up early, trying to give them effective interventions at that point in time, can reduce costs to them but also to the health system, and more intervention doesn't always mean medication either — if you intervene early enough, you can provide effective care with other kinds of behavioural or psychological interventions.

Bianca: Amazing. So Frank, if I was a young person today in Australia and I recognised that I needed some mental health assistance, what's the current journey that a young person goes through today when they're navigating Australia's mental health system, and what would be your ideal state — you know, if you think about what it is today, and what's the beautiful Frank Iorfino world of what you'd like it to be — what does that look like?

Frank: Okay, so I think we do a lot of work with lived experience, so we have lots of insights into how people do view the mental health system today. I think one way to describe it is it's kind of like navigating a maze, maybe without a map as well. So someone might present to a service, let's say headspace, which is a great open door for getting people into care, but then from that point on, maybe they don't quite feel like that service is meeting their needs, or they're not getting better, or they might need to go somewhere else. And so getting somewhere else can often be associated with a longer wait time, higher costs, not a clear pathway as well — it might be a referral, and the referral might get lost. So we have lots of different services and different information systems, different ways of assessing, there's often criteria to get into a service — so maybe I'm trying to get from headspace to another service, but maybe I don't meet some threshold for a particular symptom or disorder, and so that's a barrier that then gets me sent back. So there's a lot of bouncing around and trial and error of trying to find out is this working for me. There's obviously the same kind of thing happening in the digital space too, where we have lots of great digital tools, lots of online CBT, lots of online services — again, a lot of it's trial and error, so you sign up or you go to that service, you see if it works, some of them might be doing measurement-based care, some might not, so there's lots of inconsistency, and there's a lot left on the person and their family often, to try and figure out is this what I need, and if it's not, where do I find what I need. So all of that is very opaque, and you have to do lots of searching, often lots of advocating, lots of speaking to professionals, and sometimes it's just by chance — you speak to the right person that you can get to where you need to go. So that's the current state, I would say, or a rough overview. And so the future state, I think a lot of these AI tools we're looking at now are empowering the consumer — so I see a much more person-centred, consumer-centred future state of the mental health system, where you have a kind of guide that helps you accurately identify your needs, it helps search for on your behalf where those services are, what interventions are available, what are the criteria for entry, and helps you navigate — or actually, in an ideal sense, they're not sending you somewhere, but rather bringing the services to you. So removing the idea of navigation, and bringing services to you. And so that's why I do think the future is focused on digital, because if you think about the workforce shortages, if you think about regional access problems — all of these things can't be solved with just more services or more people in the system, it requires smarter solutions, which I think are digital. And so I think that future state is more about bringing the right services to you — oh, there's a psychologist down the road that has an availability next week, or here is an online module or CBT module that suits your current rumination, or your current sleep and circadian needs could be tracked by an activity device that can give us information about your circadian profile and its impact on your mood. So all of those things being brought together in a kind of intelligent, AI-based solution that's trying to make sense of all that information for the consumer.

Bianca: That's amazing. So what you're sort of saying is, at the moment, the way that youth effectively navigate the current Australia's mental health system, or just the mental health system in general, is really like trying to navigate a maze without a map. We've all been in those mazes and they're not fun — you know, they definitely feel overwhelming when you don't know how to get out of that particular maze. And so if you think about going from navigating a maze without a map, through to having that guide in your pocket that's giving you that assistance almost before you even know you need it, I think that's game changing.

Frank: So maybe the digital solutions is basically a bulldozer that's just erasing the maze — just takes the maze down entirely.

Bianca: That's I love that. That's pretty — I'm just picturing you driving the bulldozer, just getting rid of that maze. But I think it's a really cool concept to think about how fast things are changing, particularly, as you're saying, leveraging AI — it's not something to be scared by, it's actually something that when used well, and grounded in research, which is what the BMC does, you can actually see how it can transform mental health globally, not just in Australia, but whether you're in Australia, Canada, UK, whichever market that you're in, to really help people, because it is really hard to navigate. And you hear these stories — I think of so many stories we hear of parents who, exactly as you describe, are trying to help their young person navigate a system with no map, and not knowing where to go to get assistance, or what the timeframes are to get that assistance. And for some of them, the higher the risk, the more on edge that particular parent is. This is a way to effectively say, "hey, download this solution, this is actually going to help based on your health data, whatever the case may be, actually really help you before you even know you need it potentially as well."

Frank: And I'm always wary to make it sound like this silver-bullet solution — it's probably not one thing, we're talking about a future kind of mental health system that really has a digitally enabled ecosystem, so absolutely everyone's got to work together.

Bianca: Yeah, like you avoid the hype of making it seem like there's just one silver bullet to that problem — that's kind of, hopefully it's not perceived that way.

Frank: It is more complicated than that, but I think we need to have that vision in mind, in order to get to that solution, because otherwise we keep going at the same problem we've had for decades, using the same solutions — like, the recent kind of financial commitments from the government around mental health solutions was a lot more services, a lot more people, and it really wouldn't have looked out of place if that announcement was made in 2005. And so that's where I think we need to realign to what is the vision for the future of mental healthcare. I don't think it's based on services and buildings, it's based on smart digital services.

Bianca: Well, that's going to be scalable, it's much more scalable from that perspective — tech is more scalable, and it can reach thousands, if not millions, of people a lot more easily than trying to hire 50,000 physicians, whatever the case may be.

Frank: And we're seeing this globally too — I mean, a lot of other countries who don't have as developed a health system as Australia does, they're skipping trying to establish the bricks-and-mortar health system, and just going straight to digital. So in South America we're seeing lots of these things happen, where they actually have better internet connection and technology than Australia does, but that's enabled them to go, let's focus on building a robust digital infrastructure to support these kinds of mental health solutions, because one of the benefits of mental health is that a lot of it can be done remotely, through digital technologies. So I think we're seeing that globally, and I think digital mental health — Australia has been a leader for a long time, going back to the Black Dog Institute and Helen Christensen's research, really leading the way in that kind of digital mental health space for a long time, and we've also been world leaders in the youth mental health space, with Ian Hickie and Pat McGorry leading that space internationally in terms of youth mental health movements, early intervention in the youth mental health space. So I think we're positioned in Australia really effectively to be the world leaders in youth and digital innovations for mental health, and be world leaders in that space.

Bianca: That's super exciting, that's amazing, because I think, you know, we as Aussies, we typically think that we punch — we punch well above our weight, we're always so far away from everyone else, but I think it is really amazing and inspiring to hear that, as you said, we are leading the world in many aspects, and I think particularly, you know, we were in Toronto late last year attending a conference over there, and you were obviously doing some research there as well, visiting different centres. What do you see as some of the similarities or differences, I think, between different countries, whether it be Canada, Australia, and what are some of those global trends, I think, where you're seeing that we're positioned to be able to really change the game?

Frank: I mean, we definitely are positioned as world leaders, but I think people are catching up quite a lot. So I think in Canada they've really taken to the idea of measurement-based care — so at a government level, nationally for them, and at a state-based level, they're really focused on making measurement-based care core business of healthcare. In Australia we haven't quite got there with that — we're still focused on activity, so counting how many sessions people have and that kind of thing, rather than focusing on outcomes, are people actually improving. And actually the UK has also adopted this, in terms of their national psychology treatment approach, which has adopted measurement-based care. So in that area I would say we're kind of slightly behind at the moment, and so there's a real need for us to make it core business in Australia, to make measurement-based care standard practice. But then also in terms of the actual wider AI and digital space, I think America — a different approach to regulation, which means they're able to probably move a bit faster than we are — I don't really have a take on whether that's better or worse, I think it's hard, you need innovation, you need to enable that innovation, but you do need some form of safety net, regulation and safety net, so maybe the jury is still out on how that plays out. But I think we're seeing this race on AI solutions playing out, where the US in particular, even parts of Europe, are trying to really drive smarter AI solutions in health systems.

Bianca: Amazing, thanks. So Frank, thank you, we've covered a lot, we've unpacked a ton of themes and insights, and this is obviously — you have so much research in that brain of yours — I know it's been really wonderful just hearing and having you share that with us today. So we've covered some of the trends that we're seeing in youth mental health, we've seen the impact of technology and the role that AI can play, we're seeing the impact around access to resources in regional settings, and just the challenges that I think exist in the youth mental health space. Any final comments, anything you'd like to add?

Frank: No, it's been great chatting with you today, I mean I'm really passionate — I know you are too — about technology, and I think it's just worth pointing out, too, that we don't do this for technology's sake, it is really about people. And so all of the things we've talked about are really about just trying to make healthcare, mental healthcare, better, which really does mean leaning into more of the human aspect, and using technology and these things we've talked about as ways that can enable that and make that better. So coming back to the idea that it is really all person-centred, so no, it's been great chatting with you today, thanks for having me.

Bianca: Pleasure. I'm sure this will not be your last time on the couch, so thanks so much for joining us, Frank, appreciate it.

Frank: Thank you.