Non-Pharmacological Interventions – The Growing Role of Technology

Non-Pharmacological Interventions – The Growing Role of Technology

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While, we are, transitioning. To the next topic I do want to check to see if we have some. Of our presenters on the line as well, so. In the room for our next session is. Dr. Jeff Kay but, on the phone do we have dr. via, I'm. Here all right and dr. Molly. Thank, you dr. Hepburn. Okay. So that's our last presenter before, Laura so hopefully, he'll come online shortly all, right I'm gonna turn this over to Alan and ask him to kind, of introduce our next session, well thanks Angela so the next 90 minutes we're gonna talk about the growing role of Technology, and non-pharmacological. Interventions, as. Well as I think using technology. For outcome. Measures and so this is a really, important, rapidly, growing area. We, know it's it's, a challenge, in any research study or for that matter for clinicians, health care providers, to actually monitor, progress and you. Know we often do it in a laboratory, or, clinic setting periodically. Every 6 or 12 months when. Really the, goal is to monitor, how people are doing at home in, the community and to deliver interventions. At home and in the community I think as we look towards a different, future. And. So the and currently the tools that we use to monitor. Outcomes, are very imprecise, they're, not rare they're very general, tools are not personalized. And. We have to begin to take you know account, of people's backgrounds, their experiences, their abilities, their, home situation, etc so. Technology development, for 80 and 80 are related. Disorders, is largely a underrepresented. Area. Of research until recently, and it's got a some, room to grow, to. Use real, world ecologically. Valid outcome, measures, and deliver, technologies. Our. Next session is really going to attack tackle, these areas, our first speaker, is dr. Jeffrey, K at Oregon Health Sciences University he's. The director of the Alzheimer's disease Research Center and, he's been a pioneer, in the use of technology, for dementia, he. Leads an, NIV, a a funded, collaborative, that's called cart which stands, for collaborative, Aging in Place research. Using, technology, so, this, initiative. Is, Boal the United Sen ih academic, and industry experts to. Develop tools. That record and track real-time changes in adults older adults health, status, and activities. So. Jeff's, gonna give an overview I think of the state of the art and then, we will have a, couple, sessions one, is first session will be on the interventions, for people with dementia. And, that's going to be with dr. via and, dr.. Malley dr.. Byas a medical, director of geriatric, psychiatry. Outpatient. Services at McLean Hospital, and. We'll be discussing. Use, of tablet computers for. Interventions. For managing agitation. And then. Dr. Malley is a professor, of cognitive linguistic. And psychological, sciences at Brown University and. Will. As, an expert in social cognition social, interactions, you. Will be talking about affordable robotic, intelligence, for elderly support, and. Then. If we get our other, speaker, on the line we're going to talk about interventions, for caregivers. Dr.. Ken Hepburn as professor, of Nursing at Emory, and. Leader of the outreach core. Of the Alzheimer Center there he. Has developed technologies. To. Call. Tellus a V which is to reach out to caregivers, for caregiver, training and education, and then. Our own dr., Laura Catlin, is going to close. The session talking, about the we care advisor. So. That is my introduction, and we'll turn it over to the expert, dr., kay. Thank. You Alan and thank you all for having me it's a real honor it's it's great to see I think we can do something with this group. All. Right I'm gonna. Dive. Into my presentation, and. I'm gonna start by Framing, the. Discussion by. Reading. A file. Which. You probably some of you already know whose. File this is but the. Doctor, says how long have you been here, she, seems to be trying to remember three. Weeks what. Is this I show. Her a pencil, a pen, a Persky, diary and cigar are identified, correctly when. Objects are shown to her she does not remember after, a short time, which objects, have been shown and so. You probably you know that. This is. Alzheimer's. Notes, on, his patient, his. First series August, eater and just. To, point out that this, kind of query. Is. An examination. Is. A hundred years old and it's really what we've been doing and continue to do and.

It's. Probably, time, to change, and I'm going to talk, about what why, that is and how we can get there, so. To quote. Paul. Simon. We're. Still crazy after all these years but I think we are going to change. That a bit so right now, there, might be a problem with a patient this is a photo from a family, that sent me referred, to me a patient we. Bring, the person, usually, to a clinic, and. There's history taking, and lots, of exams. And. We assume that this is equivalent to what's happening, in the real world but. Unfortunately this kind of assessment which is inherently, brief. Sparsely. Spaced Trepak. Episodically. Occurring. Clinic. Based with. Largely, subjectively. Obtained, information. That. Is true, civ and inconvenient. Not, only to the the patient but also to the the, clinical teams as well so, this. Isn't an equivalent, assessment. This. Is just to highlight, some. Of the challenges, of the kinds of data that we get, from, this kind of process, so the top, panel is spaghetti, plots, from some Adney data going, left to right are normals, mci. Patients, and individuals, with mild. Alzheimer's disease and you can see the, tremendous heterogeneity. These, are the memory, composite. Scores in, heterogeneity. And. Intra-individual. And between, individual. Cases. Making, it very hard to really tease, out through. The noise what's, happening. The lower panel is another. Just a small study showing, self-report. Data using. The UCLA, loneliness, scale over time again the same kind of pattern. Is, seen and shows how difficult it can be, to detect, meaningful. Change. So. The way it. Should be or, could be or can, be, is. To. Hopefully change the the paradigm. So, that we collect. Much more. Comprehensive. And holistic. And. Multi-domain, data that gives you a full picture of the individual, in their home so. This whole we've already heard today, a lot of, interest. And need to be home-based but, also that. The information, comes as continuously. As possible, it's, as objective, as possible and. Unobtrusive. Ideally, without, the person having to do, involved. Having to do too much, extra. Activity, to, disrupt their day. Now. This idea. Of, delivering, this kind of information, from technology. I'll. Talk about the technologies but I want to just, highlight at. A high level how they, might. Improve. What we're doing and there's three high-level areas, I want to just mention. First. Of all the. Idea that we can transform, the way that we detect meaningful. Change and what I mean it's not we're, not looking at surrogates, like how many words you can remember from a list but, really, can, you remember to take your medication, on time for example, we. Can also increase, the speed, or efficiency, of, clinical, trials themselves, because the methodology. Improves. The generative the conduct, of the, research, and then finally something I think is not. Fully, appreciated, but will be increasingly, appreciated is these. Technologies, when deployed. In large. Scales. In, home, environments, can, provide really, new insights, into human, biology, and behavior. So. Just highlight these three points I'd, like to show this figure. Where, I'd indicate, a typical. Individual. Being, assessed. Sparsely. Or episodically, over time this could be blood pressure cognitive, function, functional, assessment, scale and we, tend to try to make a inference.

That Something's, happening, based on the sparse data it. May get more calm, kaida because, a patient, or caregiver may, report some symptoms and then we have to try to relate what's going on with. All this data but, imagine if you had data, that came in every day or continuously, you, would realize that in fact there was no change in the mean over time but. If you look more carefully, there's. A change in the variance. Or the variability day to day and this, itself may be of you insight, into early. Detection so. That's a just an example, I'll show real. Data, to sort. Of suggest that that's real the. Second area of improving, clinical. Trials, I think is really important this is from the pharmaceutical, manufacturers. Association. It's a pharmacologic. Example, but it's entirely. I. Should, say whether, it's pharmacologic. Or non non, pharmacologic, it's, all about logic so. So. We. We all face the same problem. Of having, tremendous. Opportunities, so there's thousands. Of compounds, that are available to be tested, there, are thousands, of non pharmacologic, interventions, that need to be tested, and we, have this bounty, really of opportunity. We, have a big problem though in that we can't move these fast enough to. Get to phases, where we have confidence, that these these, these. Interventions. Really work and, I think this is really the opportunity, space for. Technology, to, really move that arrow further, and. Actually, not just end up with one treatment but, end up with many treatments, really what we need and, this. Just is a figure. From a paper of, Hiroko. Dodge a simulation. Of sample, size is needed using, conventional, measures versus, continuous. Digital. Technology, based measures computer, use and walking speed in this case compared. To the logical memory or, memory tests. So you need thousands, of patients typically. Now for example of foreign prevention. Kind of trial where as you need, orders of magnitude, fewer it's, important to realize it by reducing, sample, sizes alone, you, reduce the exposure, to harm, and. You also by. Using very, frequent, dense data you can increase the, ability to actually. Get intra-individual. Change not, just group, change and then finally. The. Cost can be reduced in, the sense that we. Make decisions into, pushing. Therapies. Into. Larger. More expensive studies. On really. Not very high. Quality data, we. Can improve that by using these technologies and. Then lastly just to highlight the point of. Improving. Insights. Into biology this is just a small. Example of. Looking. At in. Freight Ian's or seasonal, rhythms so, the the figure on the bottom there, is just. Total. Sleep time using, home, passive, monitoring in. A cohort of normal aging folks. The. Red. Lines. Are, the length of night so in the winter the I it's, it's longer we hibernate. We tend to sleep more this is a normal pattern and then, here just showing on the left side the top is actually the same data but the the, line is a cosine, or function, to model, the periodicity. Of the, normal group but, the bottom group are those with MCI and you can see this flattening of in, fraidy and rhythms there's no response. To the seasonality, in this group and this is something you could never see with this without this kind of approach. Okay. So now. That I've convinced you that this, is what everybody should be doing, the, problem, is how do we do it how. Do we enable. Researchers. To be, able to, take. Advantage of these various technologies and some you're gonna hear some details, later from, colleagues, but, here. I want to point out that and, actually, thank the NIH, foresight and funding, actually, at our institution, a Roybal senator Orca tech which. Enabled us to develop this. Platform. Of technology, to facilitate this kind of research and now more, recently the card initiative, as Alan. Briefly. Mentioned so, what you see here is a home layout. You'll. See there's no real technology it's all based on not technology. But what the technology needs to be able to do the use cases and the. Use cases have been focused, on function. So. That's, what these major domains, are. And then if you think about it well how can the technology, reveal. Or help, assess these functions, better so, for example in the domain of activity, mobility, and sleep you can use passive, sensing with IR. Motion detectors, or, wearables. Are perfectly fine, there, are even bed mats there are many ways to do this it's not about the technology it's about what technology, gives you the best information in the, domain of physiology, and health there. Are many kinds, of, physiologic. Monitors Wireless, scales blood. Pressure monitors, and, electronic. Pill taking, the, tracking, devices which can, tell you about whether, persons taking medication, but also it's a memory test as well, which, brings me to the domain, of cognition, and behavior. Here. Much information, can be gained by monitoring, computer.

Use Whether it's a tablet laptop smartphone, it doesn't matter it's, about the technology. That gives you the best information, and. Then similarly. These kinds, of technologies, can be used, to monitor and, assess, caregiver. Interactions, and. Safety. And and caregiving. Activities. Looking, at things like time out of home or phone use and then, finally, just something. That we've been particularly interested in looking at safety, and cognition, through. Driving, and here, monitoring, driving. On a continuous, basis by tapping in the data port of automobiles. Now all, of this technology are different devices different, functions. And it's important to realize it's been designed so that you can plug into this system based. On standardized. Communication. Protocols. Like Wi-Fi, Bluetooth to. Get the data to aggregate, so, you can if you have something new or something different, it can be integrated, and. Most, importantly, is that all the data goes out securely. I said. Securely that's really important these days and. His, us and is aggregated. In a server so that there is the. Ability to share this data, broadly. With the research, community now, this has been done now for over a decade in a number of studies. The. Life lab study or. Cohort, is part of Orca tech for many years but now more recently, I want, to emphasize the cart initiative. As well the. Cart initiative has allowed us to continue. To evolve, this system this is a system diagram, I'm not gonna go into any, of the detail or there to point out that on, the left the turquoise box was basically, the, home you saw with, all the, devices. And sensors in it but on the right is an extensive back-end, that's needed to, operate. And do this research. In. A timely, and secure fashion so. Cart. Was. The. FO. A was, in 2016. This. Began. In earnest in 2017. It. Was established, to, address the. Recognized, need to increase, the capability, to use.

To, Use the technology, and build evidence to how this would work. And, to, allow a. Really. A scalable. Disseminated. Platform, or system to. Be deployed. Ultimately. To hopefully, tens, of thousands of homes and many many researchers. Importantly. There's a focus on diversity, so. The cohorts, in in cart currently. Are. Low-income. Seniors. African. Americans, in actually. In Chicago. Veterans, living. In primarily. Rural areas and a Latino. Heritage. Or. Latino individuals or, seniors in the Miami area. The. Technology, is agnostic as, I said it's not focused, on a particular wearable. Or app, it's. Use it's. Flexible, for its use case and hopefully it'll be sustainable. And. A, resource. Into. The future for sharing. It's. Actually, led. By, the niña. But there's other important. Institute's including as, you can see here and inds and many, others and very. Importantly. The VA and. There's. A big, research team which. I don't, have time to unfortunately, honor. You. Know silver in the NRA. Tremendous. Science. Liaison, for all of us and, this. Is just a map of the, sites there, they're, obviously more than four sites here because the the. Platform. Is now being adopted, by other studies, so. They're about. Two. Hundred three, households, 387. Participants, and, we hope to continue to grow this. Enterprise. I now. Want to quickly turn to some, examples, more, concrete, examples, of understanding, the technology. Actually. There are toilets that can, be used this. Is, there's. Things you really can do for metabolomics. And. Biome. Studies, and so forth but. So. First of all just, to point out us the kinds of data so, we're at what's shown here are spiral, plots of. Activity. These are 24 hour clocks, with, midnight at the top and. Noon. At the bottom this is 8 weeks of data going outward, and what, you see here is bicolor, and dots where activity is occurring the, wedge on the sort. Of the right, upper quadrant, if you look over on the left plot, is. Typical, of people sleeping at night but getting up to go to the bathroom or move about a little bit and over, time going to the right this, individual, developed mci and you can see that there was this change, another. Quick example as. A person, who developed Parkinson's disease, so you can see on the left the. Normal, pattern and then as the, time proceeds, the individual in the middle is diagnosed, with Parkinson's, disease has a very disruptive pattern including, sleep and then, when.

Treated With Sinemet, the pattern normalizes, somewhat, showing. That you know one can sensitively, I'd see these changes obviously this has tremendous implications, for example for Lewy body and other related. Dimensions, that have parkinsonian. Symptoms. One. Can also differentiate. Different. Types. Of groups, with, or without mild, cognitive, impairment or other dementia so here's a study. That was published by, a Minako, in Clark he was in Toronto at the time University, Renault showing. Room transition, in patterns. Do, predict, or differentiate, people with MCI or not. Hiroko. Dodged several years ago looked at gate speed and the variability, of gate speed over time that, suggested, that there were patterns, that were different. Between early and later stages, of MCI. Sleep. Anybody, want to go to sleep it's your. Sleep latency is the shortest, right now 2 o'clock or, so. But. You wouldn't know that because if you self-reported. It as shown in this, this. Table, so this is a table of. Individuals. With. MCI. To. Non-m, message a message MCI, and normals. Age-matched normals and the, report on the pittsburgh sleep scale they don't see any differences, however. If, you, monitor these individuals, this is data over 26 weeks from tomorrow Hayes's work, that. Shows using. Just passive, sensing so this is not wearables, or bed mats that you can see these differences in in. Sleep, this. Is just recent data using the cart system, and it's wearable. And. Another, study sister. Study evaluate, showing. Patients. With MCI in the middle differing. In their total sleep time over. 179, consecutive, nights on average. So. Just to give you a sense, of the kinds of things you can do in the diversity, of ways, that you can get this data and again that the self-report is just inadequate. Another. Major area is cognition. Behavior. Motor, function all can be assessed using computer, use the. Plot that you see is the downward. Use time. Of use of the computer over time and individuals with MCI but. There. Are other aspects, the computer use that are incredibly. Helpful, and, informative. So, some data cannot, be. Monitored. Objectively. You have to ask people how they feel how is, their mood how can you rate your pain so these are things that that. We have asked and others on. A regular basis we do it once a week with good response and and. You. Get very. More. In, the moment information you. Also get, a bonus that, you can get, characteristics. Of, sickle characters of how the individual, responds. And the, time it takes even just to do the survey, has been shown to, differentiate. People who, are developing MCI, or actually who will develop MCI, in the future. This. Is just a little table that's hard to see but it shows that the mouse movements, of individuals, MCI is different this work of a Drew Seeley who's at University.

Of Minnesota and the Minneapolis, VA. The. Last topic I want to talk about in this, mid. Section of my presentation, short, presentation, is. About, issues, of validation, so there's a lot of work that still needs to be done. The. The images, you see on the top is an, MRI. Overlay. Of atrophy. Relative. To a loss, of or. Decreasing. Computer use time in MCI so there's this intriguing. Correlation. Of medial temporal lobe atrophy, in this MCI cohort, so work of Lisa, Silbert. This. Is new that I've never shown this before I just got this data very, excited, about it, we've. Been monitoring. People for over 10 years now and, it. Turns out many of these individuals have now died and, donated, their brain and so, this is the first data. Correlating. The, sort. Of the digital pathologic. Correlation, in for, domain so cognition, here is related. To computer use mobility, at a walking speed sleep. Is sleep time and socialization. Is time out of home so these are just canonical, digital. Measures and what you see here is Brok stages, going, from left to right. Grouped. Into one. Two two three three. Three four five six and the. Results. Are. Show. That there is this very clear relationship. To the. Neuropathology. This. Is the same kind, of analysis, with plaque scores, and, then what I did because this I was really excited, about the data. Was. I created a, digital, composite. Putting, together. Mobility. Cognition. Sleep and socialization. And. Then look at these four examples relative. To, plaque score showing, that even with mild you know going from none, to mild to, moderate. Densities. Of plaque, emily, plaque, there. Was this clear, relationship, so. That's important. Foundational. Information and. Background for, the. Remaining, time which is. Not. Much I. Want. To just give. Some examples, of how. These technologies. Can be used in interventions. So. The first example. Is. A failed not. Failed but a inconclusive. Study, that. Came it was my r1 so I can alcohol it failed, but. It wasn't my fault, the. Ambient, independence, measures, study. Was, to, try, to see if we could create we. Knew that these kinds of measures can predict actually quite well when, people might be transitioning, to a nursing, home or, higher, in the little need of care. The. Point of this study was to see if we provided, this digital data to the care communities, and this was performed, in seven care communities. In, Portland, and, there was a randomized, design, if this, give, just giving this data would actually delay this a transition to high levels of care and the bottom line is we gave they designed, their own dashboards.

We Gave them this information and. And. We. Were able to measure. Quite precisely the engagement, of the participants. So we could you know we could say that they spent X amount of time looking at a page, or. Which, patients, they were looking at but. As, it turned out and. We've. Heard so much today I think, it's. The care system problem, it's not it's, not the technology problem. So. The, engagement with the metrics, was low it. Was too low to be conclusive, as to whether this would really help and what. We found in our exit interviews. With the care community. Staff was. That. They're geared up for crisis, intervention. They. Like the idea of being able to look at proactive, trend data but, they don't have time to do that when they're worried about you know the, patience. Whose persons. Toilets. That now been you, know clogged for you, know three times in the last two weeks. Second. Quick example, is how. The, technology. Can enhance the, meaningfulness, of data. So. This is a study of. An. Art therapy, socialization. Intervention, small pilot study. Where. The. Technologies. That would assess this were made into a model of social engagement, or, social, activity. Time, out of home, time. On telephone computer use and so forth, and. These. Are just the results of we. Could predict quite well. How. The technology. Or these outcomes rather. Related. To the, intervention, the. Intervention itself using, the UCLA loneliness, scale, was. Successful. In the sense that it created, a two point improvement, and alone on the scale. Problem. Is I, don't know how to what, is a two point change on this scale mean, so. What, the technology, I think can help is we, found that it did weak the intervention. Increased, the time measured, time out of home number. Of computer, sessions. Walking. Speed telephone. Calls so you get the idea so I'm just going to give you concepts, here. Another. Important, area cultural. Relevance. Technology. Should. Not be a barrier it should actually be an enhancer, of. This. Kind of research this, is a terrific, program headed, by arena kroff, that's. Call it's sharp it's a multimodal intervention, for brain health, encompassing. Walking. In dyads in, historically. Gentrified, communities, in Portland in. The african-american community. And, include some on online activity. The. Individuals. Walk with a phone. That. Has. Preset. Walks it, has memory markers that are meaningful to the past history, of these individuals, they. Have they, stopped they talked about those events those, are recorded, later for research purposes, and then ago and this. Has been a wildly, successful. Project. Because it's very meaningful to, the, community. And. Participants. And, it's actually, fun. Similarly. There. Is another example. Using. Of trying, to increase. Social. Engagement, and therefore improve, not, only brain health, isolation. But, actual, cognitive, function these are a series of studies now they've been conducted, by.

Haruka Dodge. Using. Direct. To home daily, video chats with a trained. Conversationalist. And the. Preliminary the initial studies were again. Surprisingly. Effective much more adherence. Than any drug, study we've ever done. People. Loved these conversations. The. Nice thing about this kind of research though again the technology, brings this is you, can monitor. Very. Quantitatively. For. Example recording, the audio of, the conversations. Changes. In. Functional. Cognition. So for, example the people, with MCI spoke, more words than the not. Than the conversationalist. And even. There were different kinds of words spoken. By those, with MCI. These. Are very early. Preliminary data so I'm not gonna make a big deal about it but so the words there, were the swear words we're not, really. High, if you can see in that table, there. And. Now this is going to be scaled. Out to, a larger study using, some additional, technology. The pillbox, collect Roenick pillbox and so forth, in. Detroit. And Portland, and. And. I'm. Very I think, this is very important, it's very important because direct. Home video appointments. And care. Management as we're gonna hear. Even more later is, is, the way of the future and we just need more research, to really understand, how to best do this most. Effectively. I'm. Down, to my last two. Quick, examples so please. Bear with me. So. This. The second last example, is as. A, study that was begun. Last. Year, it. Has a long. Acronym. Evaluate. Ad ecolodge, eval at ambient longitudinal, and unbiased assessment of treatment efficacy and, Alessandra disease. But. Not that much alcohol was used to come, up with that. But. The, importance of this study. Was to use, that, full. Suite. Of technologies as, a cart platform, essentially to. See how. Couples. Where, one a member, of the couple have. MCI. Or Allison MERS disease, how. Various. Kinds of treatments. Call. Nestor ACE inhibitors. Antidepressants. And health, events, affect. Changes. In those major, kinds, of functions, that I showed. In previous, slides and and. So, just as a quick example I've. Shown this before but. You. Know caregiving. Interaction. So. How much simply, how much time a, couple spends, together separate. Or out of the home may. We, anticipate. May. Change very. Importantly. Depending. On the type of. Therapy. That's, or, interventions, that are. Instituted. So in this spiral, plot, what's. Shown here red, is. The. Time together. Blue. Is separate, and black is out of the home over, 24-hour, period this is 30 days of data for, this one couple who, spends. An. Average of 21, that can, read I think it's 21 hours if I recant a call, together. Which. Is a lot of time. Well. It depends on what you how you feel about your spouse excuse. Me. Be. Careful about that and. Then. Finally, you. Know the, there's a, spectrum. Of needs, and a spectrum, of, natural. History of. Dementia. Unfolding. So, I think actually an under, very underappreciated but. Incredibly. Powerful, space for technology, is improving. The ability to do, understand. Weather assess. Interventions. For. Later. Stage. Symptomatology. In. Dementia, are. Working. Or not so so. Right now in, the ad CSP, sadie's study of praises, in for agitation there'll. Be a. Longer. Term digital. Agitation. Assessment, using classic. Actigraph. But, the real exciting. I think direction, is. To, to combine, this with other kinds. Of measurements, so we're. Doing a pilot we, call it moderate. Another. Acronym but. This. Is to not only use. Look. At things like sleep. Using bed, mats or passive, activity, using, passive sensors but, also to look at the environment and here you can quantitate. This by, measuring noise, levels. The. Temperature, in the room and. And. The. Light ambient, light which you probably have my. Guess. Is these have more effect, than anything. We commonly. Do but we don't have good ways of measuring these, and. So, rather than just adjusting, our data for the. Person's sex, and age we, might want to adjust it for the ambient, environment. And. So with that I want to thank you I know I ran over, I. Want. To and. You. Know really encouraged the research. Community everybody, to, collaborate. The. Cart, platform. Is available, it's. Intended, to be used and. Please. Contact, me or my colleagues if you want to and I'll. Turn this over now to Angela, thank.

You Very very much, it's. Just a fascinating, presentation and, and I should have mentioned this early, when, we got started but you know, our topic, today really, crosses. Over multiple goals within the plan. And I think it's, kind of more impactful, to review, those goals now in light of what you just heard but, that you know obviously you know when we talk intervention, we're talking about prevention, and treatment so, you've seen how technology. Can play a role in measuring. Efficacy. We're. Talking about optimizing, care, quality well. By, understanding what's. Really going on in the home and we can then evaluate how. Does that impact a. Person's, quality of life based. On some, of the interventions and then lastly supports, for people living with Alzheimer's disease and their family caregivers I think this the. Role of Technology, overlaps all of these areas and I think there's. Just great, things coming in the future so thank you so much we. Are going to have discussion. At the end of this session so I'm gonna ask you guys to hold your your. Questions for now. We. Have four, more presentations, and I do not I do know that dr. Hepburn is on the line now so we're going to start with dr., via as we, heard earlier and, we'll. Ask, you to take it away from here dr. Braga and Lori, do you want to do the slides okay, all, right and if you just let us know when you're ready for us to advance the slides we'll do that for you sounds. Good thanks um I'll just say next so I have my slides open in front of me this is going to be interesting because I have no idea what you guys are seeing. So. Let's. Just go with the flow there's a couple of slides with animation, so I'm just going to say next, every time I, want to right click sounds. Okay. Yeah. That sounds good thank you very much, Thanks. So thank. You for the invitation, um honored. To present our work I have crossed paths with a few people in the room but my name is absurd waha I'm a geriatric psychiatrist, by trade and I oversee, the Jurassic outpatient, programs at McLean I'm, also the medical director of the Institute for technology in psychiatry, here which is sort, of a pan hospital, unit focused, on incorporating. Technologies, into both measurement, and. Care. For people with psychiatric disorders, my own work focuses, on dementia and, what I'm going to talk about today is is, an earlier, study that we did about four, years ago that.

Is Open the door for quite a bit of the work we're doing, more. Recently, so. Next, slide. So. I, start. With a quick story that goes back to 2013 I, used. To be at UC San Diego before I moved to McClain and. One. Evening I was at a restaurant called. The Kensington, grill with some friends and their hyperactive, four-year-old, and this kid was essentially. Bouncing off the walls and I thought my friends did something interesting one. Of them took out an iPhone, and he, used this iPhone, to keep him calm during dinner and we made it through three courses and dessert and this. Basically triggered a simple idea if you just press next which. Is if, you can use an iPhone to keep a. Behaviorally. Activated. Child under control, could you use an iPad which is more senior friendly to. Control the behavior of someone functioning. At the level of a four-year-old. Essentially. Someone with severe. Dementia. So. Next slide. We. Took this back to the UC San Diego senior Behavioral Health geriatric, psychiatry, inpatient, unit we, applied for a little pilot, funding and we got some devices and, we. Did a study. Among. Patients with a history of behavior, symptoms, of dementia so, essentially, agitation, that. Required psychotropic. Medications, like antipsychotics. But also mood stabilizers, or other. Medications, a threshold. For, recruitment. Was relatively, low and. We. Set a procedure, for an open, trial where all consented. Patients were, trained in iPad used by staff the. Way we implemented, this was we. Developed. A, menu of about 70. Apps the study was not formally, funded so we had a little pilot money that let us buy the devices, but, the only used apps that were available free of cost on the App Store and, that. When patients became, agitated. They. Were given, these iPads, by research, staff the IRB required, that patients. Not handle, the devices. Independently. That a, research, staff members sit with them I guess. They were concerned about. The. Tablets being weaponized, by agitated, dementia, patients, it, didn't happen so, in. That sense the. Safety. Of the device was a hundred percent and we. Had a very simple outcome, measure because of the. Fact that this was a simple pilot study which was just a subjective reduction. In behaviors, as rated. By staff, members that were accompanying, the patients. Over. The course of the study the. Most commonly, used apps. In. Rank, order next, slide were. YouTube. Safari. Or Chrome and, order. To listen to music, number. Five was Google Maps and Google Earth but the one that stayed with us was this app called amazing, dogs which. Is essentially, an app that has about 700 pictures, of cute puppies and all. You do is you swipe at. One picture and you see the next cute puppy picture and essentially. That was it so among. Other things we valid the hypothesis, that cute puppy pictures can control agitation, and dementia. If. You go to the next slide after that we. Came up with a system for, rating app complexity.

The Challenge for us was we found that there, was quite a bit of heterogeneity. Between. Patients, depending, on their level of dementia, and the severity of agitation symptoms, and how they were able to engage with these devices. So. Our process, would be at intake, we would do. A cognitive intake. So. A cognitive, assessment and, we, did quite a long. Lifestyle. Questionnaire, where we tried to learn about each person's, likes and dislikes and what, what. Their hobbies had been what their background, was and we created. Off this master, menu of 70 apps a personalised, suite of apps for each patient and then, depending on what that cognitive, level, was we. Tried to give them apps that were relatively, simple, for the more severe dementia or relatively. Complex, for. The. Less severe dementia and. The way we determined. Complexity, was we. For. Each app by consensus. We. We. Tried to determine. How, many cognitive, domains were. Required, so a simple, act a simple, app like Pandora which is required some massive. Attention that was rated a1 and much more complex apps like Sudoku that required some motor function, memory. Mathematical. Ability and reasoning and learning those. Were rated number 10. And. We, graded, each of our 70 apps along this scale, next. Slide I won't. Walk I won't go. Through this entire complicated. Table with you if, we just click Next, our primary outcomes, are in the red box at the bottom and. The. Next slide has these, data. Expanded. You. Will see that if. We looked at the median, number of unique apps, per. Participant. It. Seemed, to be about 3 apps overall, for the mild and moderately, impaired, and the severely impaired patients use about 2 apps now we. Did try and customize it based on their preferences, but really it. Was mostly selected, by the participants, themselves. If. You looked at the median complexity. Of the apps that that lines. Up nicely the mildly impaired, patients, mean. Complexity, was about 5.3. 3.0. For moderate, and 2.1. For for the severely impaired, that's. The only one of the variables, that came close to achieving statistical.

Significance, But this was really a very small pilot, study the, N was 27, and it. Was not powered, to detect these effect sizes so. We're hoping. To replicate this now in a larger sample where, we actually look for some of these effects and, power, the study for statistical. Significance if. You look at the mean, total, time using these tablets, as. We. Expected, the mildly impaired group used. It for almost three hours now this is over the course of the entire hospitalization. And the average length of stay is. About. Two weeks on the inpatient unit so. They weren't using the apps for very long overall, less than an hour total for the moderate and severely impaired trooper about three hours total, for the mildly, troupe we, did not allow people to use these apps just for. Engagement. Purposes, they were used strictly as an intervention. For. Each instance, as you, might expect it was much, more for the mildly impaired group and then for the moderate and severely impaired group it. Decreases, progressively. The. Most interesting, finding we had was the one in the last row where, the. Rating. Scale of the magnitude, of reduction, of agitation, was basically staff members were asked, to what extent, in their opinion, they thought a single, use of the app resulted. In a reduction in agitation. Symptoms, so. One. Was the, least impact. And five was the highest impact and we. Found that it seemed to be most effective, for mildly. Impaired, least, effective, for the severely impaired, but it was still higher than 2.5, across. The sample. So. These are you know we don't want to over. Interpret, these data this was a very, small pilot study but. I think it's given us some very interesting signals. To build on. Chief. Among which is that, you can actually use, iPads, even for people with severe dementia and for this study that was defined as a mocker, score of eight or below so people with even minimal linguistic, function were able to engage with the more simple apps we, found that it was safe and the people would engage with them even when they were agitated, the. Only signal we had and we didn't have data to back this so, this is anecdotal but when. The agitation, seemed to be related to acute anxiety. They, would refuse to engage with the device but. Even. Then we, did not see any adverse, use of the device so there was no threatening or hitting the device or throwing it or any, of the kind any, of those things and the.

IRB Did require us to get military-grade. Protective. Covers for the app. And it you'd be amazed by what's out there there was foam padding designed to protect both the person being hit and. The. Device itself which made us wonder why such. A thing exists, to begin with clearly others must be weaponizing these devices. I'll. End on a lighter note so when this do this paper was published. If you go to the next slide, it. Got quite a bit of media attention a, globally. And across all. Multiple. Media panels and if. You click once and then twice. Our. True marker that this is important, was that it actually even, made fake news and I. Hope you're looking at the same slide that I am, but. We did not say that tablet device is making our dementia. So. I'll keep the discussion shot. But. Our overarching principle, for this was that as, dr., kay said it's really not about the technology at, all it's about. How. It is applied and if you click, on the last slide I'll end with a quote that I like which is that no one wants a drill they. Just want the hole that it makes and. There's. A large team of people both in. San Diego, and then subsequently, at McLean Hospital in, Boston that helped. Us put this together my, next slide is just. A. List of names and I'll, stop there okay. Thank. You very much doctor hyah okay. Next we have dr.. Molly. Yeah. I. Will. Also have a challenge, of multiple. Imp. Animations. But I'll just pretend, to. Do this and we'll, guide, you as well so. This project is called Ares, affordable, robotic intelligence, for all of these support and, the. Second slide shows, the, interdisciplinary team, from, behavioral science and design to. Computer, science robotics the. Kaya tree. Geriatric. Psychiatry, and our, industry partner, because, this is a NSF. Partnership. For innovation, grant and the. Original need was Hasbro, but. Aegis, innovation, spun. Off in a friendly, manner from Hasbro and is now our partner, and I'll say a little more about aegis innovation, in a second, the, next slides has, line, by line to an, explanation of what aims we have so, I just want to clarify that our aim is not an, intervention to combat, dementia, rather.

It's, An intervention to support individuals. And, in particular to support the with challenges, of aging and I'll tell, you a little more about what kind of challenges, we think are realistic to, tackle and we, expect. Of course we're looking at. Adults. Older adults about. About, 60, 65 that, some of them will have of course dementia, but this, is not our sole. Focus in the project, the, second, clarification, is not to replace health care professionals, or family members this is very important, to us because robotics, shouldn't. Be. Designed, to, take. The place of something and typically doesn't do it as well but rather we need to complement, so a technology. That. Helps lighten the burden is what we try. To develop the, burden both for family members and the, healthcare system as a whole, further. Next, line just. To, explain. That as well the affordable assistance. Should. Be small and help, with challenging, tasks, of daily. Living it should connect, the, participant, or the care, recipient, with friends and family and of, course the hope is that it will relieve, some psychological, symptoms such as agitation. And loneliness, and related. Issues. The. Disclaimer. Is not, a remote robot server, therapist. Or entertainer, you will see in a second, it is a pet companion, and we. Intentionally, tried not to raise the expectations too, high. Final. ID on this slide it, should be comforting. It should be understandable. To, use and it should help with, some of the concrete issues that I'll explain, in a second so it's a robot companion. Not. Necessarily. A therapist. Or. Somebody, who can cook for you any of these roles next. Slide as. A starting, point a few, pictures of the joy for all companion. Pets that currently, exist, for. About $100. And. Really. What, we are trying to do is take these are starting points, they're quite popular if you look at the Amazon, reviews, take. These and make them more intelligent, already. Now this is the one animation. The. Company, has received several, the, smart, award. Recognitions. And the caregiver, friendly award so this is a really good start but really, these pets cannot do much that nice. To hold nice, to, pet. And they give, off a few, sounds. And make a few small movements, but they're really not intelligent, so they can't be any help with, other than these indirect, psychological. Support issues, the. Next slide now. It tells us existing, strengths of these pets. As currently. Down the market and the new intelligence, we, try to build on the existing strength. Side you can just click, down the three main points, it. Is comforting, is, a familiar shape, and it's. Non-threatening. And this is very important, when you build robots, that are even. Of smaller size they're, quite scary, for some people. The. Pet, companion creates, limited expectations. As, I said it's not going to cook for you it's not going to help you with a lot of physical tasks, it is there for you in, some. Very small ways but. It remains affordable right now it's about a hundred dollars, we're trying to build these, next-generation, prototypes. For. Under 200 dollars so it should really be available.

To A lot of people, not like robots, often our to, a few people who have the money to afford that, the. New intelligence. That we're trying to build in. Course. Perception, memory nonverbal, communication, are some basic principles that, you have to put into these systems and the, particular task that we're focusing on at the beginning includes. Tracking, of lost objects, misplaced, objects, of course is a very common. Issue and. Then, helping. Find, them as is important, it's not going to fetch, the, object for you but rather it will guide you to, help, it, to. Find it so the robot. Companion helps the, care recipient, and the care recipient, helps the robot companion, so together they can solve some of these tasks. Another. Set of objectives. Fall detection that's, relatively, easy than many. Systems. That can do this but, imprecisely, so, by having the companion, around the house is of course very, much about. Aging in Place. There, is a continuous. Data, collection. That is possible, and then maybe a more fine-grain distinction, is the person lying on the floor because they're doing a Pilates exercise, or because they fell down, obviously. The, common goals of medication, reminders, social, contact reminders, and also, and I was quite inspired by dr.. K's presentation. Vitals. And other behavioral, data that can be collected not, necessarily, about a pet companion but by an associated, intelligent, data, collection, device next. Slide the project compare components. And we can really. Go down and click 6. Times here, we're using behavioral science. Methods to, assess the, major challenges, of daily living and I'll show you a few first results, on that and of, course we cannot help with all those challenges, but only with a small affordable, set, sorry. With a set that the small affordable robot, can help with we. Are, committed to inclusive design, principles, and cutting-edge computer science and of course that, is how we try to tackle. These challenges that. Currently, these, even. In small home robots, can't really help with, we. Also, using. Our nutritional assessments, of the developed system to actually have good outcome, measures to, establish, it they're safe efficacious. And that, they're actually accepted. And liked. And. Used, by, our target. Population. Next. How do we assess, challenges. Well this is currently what we're doing we're really at the beginning, of this, project. But, we have now in-person standardized, interviews, with. People. In independent, living facilities, and we're just starting in memory care facilities, these, are interviews that are actually surveys, that, we're also in. A couple of weeks launching, in a national representative sample. And, what. We're doing here is trying and, if you click down a couple of lines. Trying. To, get. Information both from care recipients. And from informal, caregivers. About. The. Daily. Living challenges. That, they experience, and maybe even get a priority, order and then find out which, of these, our, probe. Companion, can tackle the. Next slide shows preliminary, results, on 50, healthy, adults all above, 65. Which is heavily biased towards, female participants. And, we're trying to of course, remedy. This with our national representative, example, if. You click top five, challenges and then click again then you'll get a table and what, you see here is, that these are all people who are, really. Pre dementia, there are a couple of people who report. Memory. Issues and one, of them has, received, a diagnosis, but this is for the most part at the transition, to this. Potential, challenge, but. They talk about difficulties. With technology. Which. It was, great, to hear that even. People with moderate dementia can, use tablets, but the subjective experience is, definitely that these are challenges so our robot companion. Needs, to be tied with very. Simple technology, doesn't. Shouldn't. Require a manual to be operated. Difficulties. With misplacing. Losing things this is very important, to us to confirm, that this is really an issue because, this is one of our main technical, challenges, in this first phase of creating, this robot. We. Cannot help with difficulties, moving on self-conceited, to standing position but. We can't help we believe with difficulties, with moods giving, a positive outlook, and again. Not as a therapist, but by just being there being a companion. Being. Made use, useful. And used that. Can have, an impact difficulties. With speech and language also. One thing that we, cannot help with directly although, there.

Might Be ways to expand that I like, the idea of trained. Conversationalist. And the global companion could encourage having, such a conversation, then. If you click again top six adoption, reasons and click for the actual table when. We ask people if, we presented, you with the opportunity, to have a robot companion for, what kinds of things would you adopt it people. Talk about measuring vitals, so that really also supports, dr. K's idea. Locating. Lost objects, again affirmation, of our plan detecting. Falls playing. Cognitive, games we're, not currently doing this but again there might be encouragement, to go to the iPad. Do this obviously. Remind us medication appointments. And so on and connecting, with friends and family, so, these are all important. Elements that at least our initial sample has told us they, care about and a, number of them we can address with our robotic. Companion. Next. Slide shows just briefly. Some additional data from this sample we. Were interested in whether particular shapes, appearances. Of the, robot companion would be preferred, and. You see here the, top four, of a. Number, of nine of, these, shapes, and the. Top, and the. Dog. And the cap are, exactly, the shapes that currently. This. Joy for all companion, pet, has. We, tried a few other ones apparently the rabbit is quite liked and a. Version, of a robotic, dog and. Generally. People were a little skeptical if you look at the percent don't like it, they're almost nobody who said hate it but. Really. Does the dog is the only one that gets a clear majority and the ones who like it and that's surprising. Because when. People actually touch and interact with these companions, they. Particularly have a very positive response. Finally. This last slide I'm not going to go into much detail, just. To give you a sense how. We're doing it we're working with multiple sensors. Infrared, and. Also. Some acoustic sensors, we need redundancy. The, idea is basically that the let's. Call it the cat, tracks. Object, significant, objects eight to ten objects, that it initially, learns to, recognize to. Know its default location, to. Be able to then track, it's either. Default, location, or where it was misplaced and then. When the care, recipient asks oh I don't know where my reading glasses are then, the robot can actually guide the person you may hold a cat and, the person the guide is.

Through, Head-turning or paw acting. Into, the right room towards. The object, and the, cab really needs the person, to be carried. There but also can you. Rely. On the person's, eyes and recognition. So they really collaborate, together. On, finding these misplaced, objects, and the, software development is of course one of the biggest challenges, although things, are really moving, so fast currently, that we're quite. Optimistic there. Want. To stop here and I know it will have some questions at the end but thanks, for your attention at this point, thank. You very much dr. Molly. Fascinating. And we look forward to hearing more about the study as as, more. Data, is. Available, next. We'll turn it to dr.. Ken Hepburn, who's, going to take. Us through, the. Telus IV program. Thanks. Laura and hello, to everybody from, Atlanta. Where I think you'll be amused to know that tomorrow. Emory, University, is closed because of the severe weather warning, we're getting snow. I, want. To describe a. Project. In process. Can you all hear me yes. Okay, I want, to describe a project, and process, the telus Avey project. Hi. And my co-principal. Investigator. Patricia. Griffiths, are, running. This project out of Emory's and, I go sweater alzheimers. Disease Research, Center. Hi. I'm from the School of Nursing and, Patti. Is from the School of Medicine, next. Slide please Laura. So. This, is a word from our sponsors, we. Piloted. The tell, us a V program. Through. A grant. From the VA office of geriatrics. And extended care, and, from. Our. Own ADRC. And. We. Are being. Supported in the current randomized, trial. By. An. Award from ni, a. So. Thank you to all those hunters. Next. Slide please I. Want. To just describe briefly the savvy caregiver, program. The. Savvy caregiver, program is, a six-week. In-person. Group. Psycho. Education. Program. Generally. Given. To, six, to twelve family. Caregivers. But. Concede, if you will of the program is. That. Caregiving. Is a newly acquired role. That. Is actually a little bit clinical, in nature, and. The the caregiver. Needs, to develop, you. Know skill, and, knowledge, for. This role. If, you think about the word savvy, it, it. Really means being, street smarts, we're trying to promote the, the. Notion that caregivers. Can, become more street, smart. In their, caregiving. That they can, be come. Better. At. Guiding, behaviors, where they need to be guided and, in, promoting, what. We call contented, involvement, or simply, meaningful. Engagement, for. The person, to, improve. His or her quality, of life. The. Curriculum. Because it is a curriculum. Draws. On multiple. Disciplines. And it I think. We lean a lot on nursing, but also it, takes an occupational, therapy, based approach, much. Like dr.. Goodwin's, therapeutic. Program. Tailored. Tailored, activities, program. The. Program was. Developed. After a couple of randomized, trials of similar. Psycho education, programs, these trials are funded by the National. Institute on nursing research. Navi. Is one of the programs. Like reach that's, been identified as, being highly evidence-based. And so it's been it's widely, available through. Administration. Community living grants, we, think it's. A, at. In play in 1415, states and probably, 20,000. People have taken part over the last 15 years but. It's. An in-person program, and. We know from working in stages, rural areas. And, also working in Los Angeles with. An impossible transit. System that it's really hard to get to in person for on a regular and reliable basis. And. So an addition, people have to you, know provide. Care for the person I was living with also so there there. Are limits, to attend, so. Next slide please so. We. Thought. We. Would like to develop a virtual group, program, tell us a V we. Began, by deconstructing. The, Savi curriculum. And we can reconfiguring. In a way that would. Allow us to maintain a, group. Format, through an online synchronous. Online, group, format. Platform. That. Is now offered, in seven weekly. Online. Sessions, about 75, to 90 minutes each. Augmented. With. Daily, video lessons, roughly. 8 to 10 minutes in length. Except. When we went, one of our neurologists, loose and then he went 20 or 25 minutes but. These, are provided, daily. Through emails. And. They're available through, a. Commercially. Available pledge. Occasional, at forum called, canvas, so. If you picture it person. Starts, on day one with a video group for. The rest of the week she, gets a daily, video lesson, the next, week, there's a online, group, and so forth over. The course of essentially, forty, three days. So. Next, slide please the. Video. Conferences. Are. Led by an experienced. Savvy. Facilitator. Nobody. Who's done this over a number of years and, these. Conferences. Are designed, to focus on the portions, of the curriculum, that really. Need. Interaction. A. Lot. Of the promotion, of caregiving mastery. Relies. On bandura's. Work. On, mastery, so. Practice. Reporting. Success, hearing, others success, we. Do a lot of that in the early part, of each session through, a kind of a goat.

Segment. And then. We do exercises. Like. Brainstorming, or. Using. Guided imagery to help, create. Empathy, for the kind of confusion that, dimension. Might produce in a person living with that illness. And. Also key talks talks, that we don't want to have, offline, we want to have an opportunity for people to react and. To and to be have. Questions answered. So. If, it's, a videoconference, typically. Six or seven people. It. Is provided, on a zoom platform. Which. Is a really, quite, easy to use. But. We do have navigators. Doctoral, students. In. The background, who watch and make sure the people are, connected, and. Stay. Connected, though. These these, have gone quite well and quite easily. Next. Slide please. The. The, daily, video lessons. Are. Provided. These are these are scripted. So when we deconstructed. The curriculum, we wrote, scripts, for these and then enlisted. Faculty. And others to. Be the the. Presenters. So we have. An interdisciplinary faculty, which, I'll show in a minute and, it focuses, on content so we want people to become more, knowledgeable about, dementia. About. The kinds of losses and cognition. Behavioral. And emotional self-control. That, occur. Progressively. In these these illnesses. We. Demonstrate, models, of how, behavior works, and how it might be guided, and. That. Those are really the kind of major portions. Of the curriculum but we also focus, on, self. Care for the caregiver. Identify. Issues and family, family. Issues and caregiving. And. Provider. Kind of strategies, for making the decisions, caregivers. Are now. Progressively. Faced. So. If we can look at the faculty in the next slide. We've. Got. Two. Nurses, dr., Angela, a Marne Carolyn, Clevenger, a. Social. Worker Clint. Two, social workers Clint, Diane Susan. Peterson Hazen. Paddy. Is a psychologist. I'm a gerontologist. Jim. Lausanne, neurologist and ivory shields is an occupational, therapist, and each, of these gives one, or more of the, daily. Lessons. Though. The next slide please so. When. We ran up a pilot that was funded by the VA and ADRC, with. 64, participants. Enrolled, from, oh my. Phone was ringing enrolled. From. 14. Different states. It. Was a pre post no control, design. And. We had. We. Showed significant, reductions, in, caregiver. Burden using. Xerath and. Spri post caregiver. Depression with, a CESD. Average. Frequency of the behavior and psychological. Symptoms of dementia using, the revised. Memory and behavior problem checklist, Taryn Linda Terry's list. And. And a significant. Increase in caregiver, mastery, so remember, we, were trying to promote mastery. In. Caregiving. And. We saw that, and. We then saw and in the, increased, mastery, significantly. Was linked to those, reductions, in. Post, per post, program burdened depression, etc. I'll, just point out that the average age of the caregivers, is all on your slide. Was. About 63, years, and the care recipients, 70, almost. All were women a rather. Well-educated group, at about a third were African, American we had very low attrition. We had we, were yeah. So, that was reported. A. Couple, of years ago then of those results, if. You go to the next slide, so. The, trial is now being, conducted. From Emory, we. Have we're, collaborating. With three other. Alzheimer's. Disease centers and I said, ia centers, at, Northwestern. Dr.. K's Center and, at Rush so. We have a national, recruitment. Program. Going on. It's. A three arm study so there people. Are either, immediately, assigned to tell us a V. Immediately. Assigned to a healthy living attention, control group which this. Is a group that has, an. Equivalent amount. Of video conferencing, and daily videos and. It's focused, on healthy living and uses. The ni. A go4life and the cdc health promotion, materials. Or. A, person, this is a silent, evil. Character. Are invited. To take part in tell us a V, so. Everybody is kind of assured and we're in a weightless way, of. Participating. In tell us a V. We're. Randomizing. On a two to one ratio. Immediate. And, healthy living or two and two unusual care, is one. After. Baseline, we have data. Being gathered at three six nine and twelve months and. These, are gathered. By video calls as well so. We're. Doing a little bit of that. Chatting. That hiroko Dodge is doing as well. These. Are my interviewers, have blind to condition. Okay. So we can go to the next slide, what. We're looking at is.

How. Well. Does. Tell us a V improve, caregiver, psychological. Well-being. Using. Measures the usual suspect, measures. Well does it improve mastery, and does it improve caregiver, quality of life as measured. By, reductions. Of the. Symptoms, and. Which we're exploring, salience. Across, racial, groups. Next. Slide. So. What we know so far because, we're not breaking the. Data to look at there or any early results, is we we built it and they're coming, so. Caregivers. So. Far. 124. Have been randomized, into the study from they're coming from 23, states and one from Canada. They. Are attending, and they're participating. Our. Observers, the the. Doctoral students, and the facilitators. Are. Reporting, that a group. Nespresso. Say that the entity, caregivers. Are interacting, with one, another and it. Feels like an in-person group, in that regard. Nutrition. Is low. There. Are good students, there they, watch they do their homework they. Watch the videos quite. Faithfully. And. There's a very wide distribution we've. Had people from Maine, to Hawaii we actually, had one participant. Who. Took who was in northern England, for it for a holiday and took part. These. The. Caregivers, are almost. The same age as the pilots, 62. Years of age, the. Care, recipients, about 70. We. Have about 72. Percent female. And. About 20 percent african-american. So. We're getting a relatively. Good distribution, I mean next slide I'll quickly end here, the. Big challenge is. Where. We're. Recruiting, across, five time zones with, people who are either working or not working so. Some people could only meet certain times and putting. The cohorts, together has been a challenge, and probably. So. I think this is once we can demonstrate its, effectiveness going. To be ideal for. Health systems who, are statewide organizations. Where they can schedule them within. The same time zone and for similar. Clientele. We've. Had, surprisingly. A few, technical. Problems basically only. Link to bandwidth, or more. Really old equipment and I'm. Just going to pitch this the next slide please, we're, still recruiting so. If anybody. Can. Can refer to us. These. Are the these are the eligibility. Criteria. A

2019-02-07 13:00

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