 So we have a very exciting panel, women, I will add. So I will stop moderating the intro and pass it on to the presenters now. Thank you, everyone. It's Susan here and I'm here representing the old guard. But it is truly my pleasure to be on the panel with the other presenters. And I think you will see, you know, what exciting work and interesting connections they have made. But just to give you an understanding, I have been involved in the CLSA since its inception and have been working with Armander and Tina since 2001 on the CLSA. And I hold a major, I hold a number of roles and you can read them there, but essentially along with Parmander and Tina and others I'm part of the scientific management team. And also I'm the site lead for Delhousie for both the DCF and the Caddy site there. And I oversee all of the Caddy and then have a number of other responsibilities around ethics and REB and also around data and sample access. I have used the CLSA on a number of different projects, all of which have been really, really interesting. And as well as trying to look at some of the bigger issues around the interplay of factors and understanding the trajectory of aging. So it's really been quite remarkable. And Jennifer asked us all for a quote and you can read this here, but really, you know, the CLSA has actually shaped my career. And, you know, it really, as an epidemiologist has been absolutely fascinating to be able to design a study of this magnitude and not just design it but then turn around and implement it as well. And, you know, not too many people get to do that. It's a really, it's a really big thing. But what I see is that, you know, the CLSA becomes increasingly valuable as we go forward. The data becomes richer and richer as we start to have longitudinal data and the interplay of all of the, you know, various factors like genetics and things like that really makes it incredibly valuable as both a national and an international resource. In terms of connecting with the CLSA, I really, you know, I think back on the early days of when we very first came together. You know, it's interesting because the CLSA even had the name the CLSA before we started. It was always going to be the Canadian Longitudinal Study on Aging. But there was a request for proposals that was released to the research community back at a conference in 2001. And Parminder and Tina and I hardly knew each other at the time. We, you know, really had never significantly worked together in a big way. And we ended up, you know, here we are like literally a lifetime later still involved in this very, very unique study. But I think what is really important is there's always been a really rich history of collaboration in the field of aging. And this really set the stage for us to be able to move this along. And, you know, one of the most exciting things that we ever did is create the design. And that is something that we did do literally from scratch. And it was, you know, probably one of the most heavy experiences that you could ever have. It was really remarkable. But coming back to that, looking back on it now, that was actually the easiest part. It's, you know, all of the things that have occurred since have, you know, put that into light. But, you know, in those very early days, the thing that we did is reach out to a number of investigators because although, you know, we were all epidemiologists, we had lots of experience around design. We've been working in the aging field for a long time. But to design a study like this that is so interdisciplinary and covers every aspect of aging, we knew we couldn't do it ourselves. And, you know, we reached out and when we did submit the proposal, there were 176 investigators involved across 26 institutions. And that's only just continued to grow. So it really is a collaborative initiative that we engage in. You know, we came together around a very important issue initially and we keep coming back together. And, you know, the CLSA is now such a great platform to springboard off. And there's all kinds of things that we've been able to do. You know, we've been able to use it in greater depth to understand or to begin to understand dementia, for example. And when COVID-19 came along, we realized that we had a really good opportunity to move very quickly and to start to pull together some information for the Canadian population. And again, you know, researchers jumped on board. Jacqueline and Nicole are here today to tell you a bit about it too. But that has been a really, really interesting experience. In terms of how we engage, you know, I think the biggest thing is the data and the fact that we are a platform and that the data is accessible to the research community. The best way to get involved in the CLSA, from my perspective, is to bring a student into the CLSA. We have great policies around access to data for students. And this allows students to, you know, become immersed in the data. It also, through students, allows faculty members right the way across the country to become more familiar with the CLSA data and to be more liable to use it in the future. We also, we don't have training programs per se in the CLSA, but we do a number of initiatives around training. And in particular, we have always been involved in the summer program on aging, which is a CIHR sponsored initiative. And in the absence of COVID, we would have actually been a, the CLSA and Mira would have hosted a spa this summer. And something that I'll just put on your radar is that we've just, well, we were partners with a group called Candy Three that is out of McGill, being led by Emily Vinal-Calcuale. And this is a training program and it's all, it's a consortium on analytics for data-driven decision-making. And it's really about developing talent to look at aging research. And so this is something that will become more and more prominent and the CLSA is a partner and I think there's lots of opportunities for students there. Just before I leave you, I would say that there are numerous ways to get involved and you'll hear some of the ways that the other panelists have gotten involved. But some of the key things that you can do are consider joining a committee. We always need members on the data and sample access committee and also on the publications committee. You could contribute to a working group if that's something that interests you. You can start your own research group either with local investigators who are also using the CLSA or with like-minded people across the country. And one of the things that we do is post on the website all of the summaries of various projects that are funded. So it's a great place to look and see what others are doing and whether there's similarities across the country and who you might reach out to connect with and to come together with. And I'll just leave you with a bit of a message that the website really is the go-to place for everything. Sometimes it takes a little bit of time to find it but it's virtually always there. I hope you enjoy the webinar. That is really a way of connecting as well. And we are on social media. So please feel free to follow us there. I'm gonna leave it at that and pass it on to the next presenter. Thank you. Thanks Susan. Just before you do that, I think what I'll do is after each presenter maybe follow up with one or two quick questions as we go. I think a lot of the, you touched on a lot from sort of beginning to end but I'm just wondering thinking back to when you were your younger self and launching the CLSA, what would you tell your younger self about taking on a project of the magnitude of the CLSA has become? Quite frankly, it's a good thing that my younger self didn't know about it. It would have been too overwhelming and too daunting and too, like if I'd known the things that I had to know I would have just turned the other way and run. But it happened gradually over time and I wouldn't do anything differently but I wouldn't want to know what was ahead. Times it's better to have the unknown just jump right in. Okay. And I think another thing that this isn't a question more of a statement is just I think you pointed out a lot of the opportunities that exist for research to engage with the CLSA and beyond just requesting data. So for the participants out there listening, again, I think it's a great message you gave that there's so many opportunities to participate. And I think as we go on with our presenters they will also be able to highlight their experiences. Well, and just one thing that I think is critically important is that if you start using the data, well, whenever you start using the data but if you start using the data as a student this can be a lifelong research course for you. There's so much information in the CLSA you will never get bored. You will never get tired. You will never make it all the way through the data. And there are always, the more that you get into the data the more questions there are. And the fact that we have such multidisciplinary data is really, really a great thing. So I'm sure that people are gonna make their careers just like we have on the CLSA. Thank you, Susan. So we'll go to our next presenter now which I believe is Jacqueline. So Jacqueline, I will let you take it away. Great, thanks, Jennifer. So my name is Jacqueline. I'm a geriatrician at the University of Calgary. And my connection to the CLSA is that I am recently one of the state co-leads of the Calgary site for the CLSA and I've been involved with the CLSA COVID-19 study over the past several months. The quotes that I would like to share, I'll go back one slide because it's still on the front one is kind of carrying off of what Dr. Kirkland was just speaking to as well that the CLSA contains a bounty of data related to all aspects of aging. And as a geriatrician, I'm acutely aware of the multidisciplinary nature of care of the older adult and the CLSA is the ideal platform for answering a myriad of questions related to human aging. So the reason I put up the next slide with the cheetah is that there's lots of ways that you can approach the goals that you have in life. If you want to go fast, go alone. But if you want to go far, go together. And I think that this really encompasses the opportunities that you'll have if you use CLSA data. If you want to answer the question of is this statin better than that statin, go for it and you'll find an answer and it will be really interesting. But clinically, when we're thinking of the aging of older adults, it's not that simple and it's never that simple. And the CLSA houses data that helps you answer questions that are actually relevant for older adults. So we know that older adults, a lot of their success with aging relates to who do they live with, how's their hearing, how's their cognition, how's their swallowing for all of those many pills that we're prescribing to them. So it is really the ideal platform for answering those questions that are actually clinically meaningful. And so if you want to look at a question related to aging and older adults or research questions, you need to collaborate because as a geriatrician, I am very narrow in my skill set and I often need the help of others who are social workers or occupational therapists or pharmacists or epidemiologists. So collaborating is really the key to success, especially when you're thinking about older adults and aging and research questions related to those people. I think that the last thing that I would add, so there will be lots of questions that you may have along the way and you might run into barriers along the way, but I think that when you encounter those barriers and you feel like a door is closing, open the door. It's a door. That is how they work. And so just carry on and speak to people around you who have more expertise and more knowledge and more experience and be humble and just ask for help, but definitely carry on because the things that we're passionate about, we're gonna be naturally drawn to want to read broadly around them and really put a lot of effort into those studies. So think about the questions that you have related to older adults and aging and I would guarantee that you'll find within the CLSA data set that many and all of those questions can be answered in some way or another. Thank you, I will leave it there. Thank you, Jacqueline. Such a great message about interdisciplinary collaboration and collaboration. So thank you for that. So I'll start by asking you a question. I wanna learn about a little more for the sake of our participants in the webinar. If you can tell us a little bit what it's like to be a co-lead of the CLSA site in Calgary and maybe a little bit about what challenges you face in balancing your clinical responsibilities with research requirements. Sure, that's great. So Dr. David Hogan has been the site lead here for a number of years and he is also one of my mentors and he was my supervisor for a thesis recently. And so he has been a source of knowledge and expertise and we're working very closely together. And I guess some of the things that I've learned along the way is just communication and interpersonal skills are really key to success. And so being able to communicate clearly with the people that you work with can help mitigate any potential challenges that might arise. And I think many of us are good communicators and we try to be, but it is really central. And then as far as balancing work, doing, trying to do research work as long as well as clinical work is that it just takes a bit of scheduling and discipline. And really you wanna avoid some of the vacuums that exist in life like Netflix is a vacuum and sometimes social media can be a vacuum and it really can suck the time out of your day when you enter into a vacuum. So try to avoid those things when you're trying to be productive. Like we all need outlets and we all need places to kind of enjoy life but definitely if you're seeing hours go by those might be lost hours. So sometimes just scheduling and being quite disciplined can be helpful. And another question, just sort of learning from your experience as a clinician researcher, how can the CLSA platform be of benefit to clinicians like yourself in particular those engaged in research like yourself? Well, certainly I can speak to people who look at aging research and older adults and geriatricians. And I think that almost any question that I could come up with the answer is probably somewhere in the CLSA data set because the CLSA data is so comprehensive and covers so many different aspects of life much beyond just medical comorbidity. And so that would be one thing I would think of is that almost any research question that you can think of, I would go to the CLSA site and see if there's something related to it there because I wouldn't be surprised if you can find it there. Thank you again and I will likely have some more questions at the end of all the presenters. So next, I believe it's Nicole. Yep, so I'll let you take it away now. Excellent, thank you so much, Jennifer. Hi everyone, my name is Nicole Basta and I'm a professor at McGill University. It's really a pleasure to be here today and to have the opportunity to share my experience working with the CLSA over the last couple of months. I'm actually really relatively new to the CLSA and new to Canada as well. When I joined the faculty and McGill back in January, I knew though that one of my top priorities was to try to understand the landscape of available data here in Canada. So that's kind of what motivated me to kind of get started in looking for opportunities to work with existing data. As an infectious disease epidemiologist, my primary focus in the past has been on identifying risk factors for infectious diseases and evaluating prevention strategies that can prevent and control infectious diseases. And that includes assessing the uptake of vaccines. And I've primarily worked on issues affecting children, teens, and young adults. But in recent years, I've started to become more interested in preventing infectious diseases across the life course because it's such an important aspect of healthy aging. So for example, many of you will know that influenza pneumococcal pneumonia in particular disproportionately affect older adults and both can be prevented via vaccination. So we have a really great opportunity to try to ensure that aspect of healthy aging. So when I began looking for data sets, I wanted to make sure that there would be some availability of data that could help me address these types of questions and look for opportunities to prevent infectious diseases. Next slide, please. So a colleague recommended that I check out the CLSA. And so I was really brand new to the study. It seemed from the beginning that it had quite a lot to offer and a wealth of information and wealth of data. But I really had to start from scratch and trying to understand what was available. So maybe I'll share with you a couple of the steps that I took to try to become more familiar with what I could access with the CLSA and how I became involved in a couple of different aspects of the study. So first, I found the website to actually be full of a wealth of information about the design of the study, especially the questionnaires that are available on the website really gave me a sense of what questions were being asked. They're really comprehensive and the different ways of the study have collected a lot of different data. So it really gives you a chance to kind of look at the scope of what's out there and think about it in terms of types of questions that you're interested in and the types of research that you're interested in pursuing. Next, I read a number of the summary that Susan mentioned of other investigators who have proposed studies using CLSA data and use those to try to get some ideas about the kinds of scope of studies that I might be interested in and to also see kind of how the CLSA has been utilized in the past. There's also a publication that was published in 2019 in the IJE that's the cohort profile for the CLSA and I really recommend taking a look at that if you're thinking about using CLSA data. Then lastly, I was trying to prepare a grant application at the same time that I was trying to design the study using CLSA data. So I reached out to one of the CLSA COTIs, Keena Wolfson, to ask a few questions and to get a little bit more information to make sure that I was proposing the appropriate scope for the study that I was looking at. So it was through this process of trying to investigate what was available in the CLSA, how it aligned with my interests and then getting in touch with someone who was on the CLSA team that I was able to put together this proposal along with a number of team members to assess influenza and mucoccal vaccine uptake among Canadian adults. So that's the first bullet that I've listed here. And our goal in this study is to identify opportunities for improving vaccination. We submitted this as part of a data access request for the deadline a few weeks ago and we're really looking forward to taking on this study once the request is approved in the coming months. And many people have mentioned that there's a lot of ways that vaccine uptake is assessed in the population and so there's a lot of different data sources that you can use. But one of the things that's really unique about the CLSA is all of the associated data that's collected about comorbidities, the biological markers, the sociological markers, so it really gives us a chance to really hone in on those who are missing out on the opportunity to be vaccinated and try to identify how they might most benefit from vaccination going forward. So we're really excited about this project and moving forward. So around the time that I was preparing that study idea was right when in March, when COVID-19 was beginning to see the cross-Canada in the world. And so during my discussions with Tina, I had the opportunity to get involved with the CLSA team as they were developing the COVID-19 studies that are underway and some of them that are still in the works. And this has been a really unique opportunity for me as an infectious disease epidemiologist to really see how this really comprehensive and robust cohort could adapt in a very nimble way to deal with an ongoing challenge in a timely manner and to just see the incredible effort that goes into every decision about the COVID surveys, what questions to include, how to implement them, logistics of pulling that all off has been a really, really unique opportunity for me and it's given me a great deal of insight that I think will inform my future studies as well as a researcher. And as we've been designing these COVID-19 studies, especially the surveys and the result of the survey, it's become really clear just how valuable and timely the COVID survey data that we're collecting will be. COVID has had an impact on every aspect of all of our lives but it has particularly affected older adults. So we've learned so much already from the baseline survey and we wanted to make sure that the results are going to be shared as soon as possible so that different stakeholders can really take advantage of the lessons that we're learning from the data that's being collected. So another contribution that I'm making to the CLSA is that I'm working with some of the data teams to develop a Shiny dashboard that is interactive and that allows users to go on the website and look at the different COVID data that we've been collecting from the baseline survey in a lot of different ways to compare by age group or across the provinces and really understand what the differential impact of COVID and the mitigation strategies to control COVID have been here in Canada. So it's really been a unique opportunity to serve at the interface of translating the results to sharing the lessons learned with the public, participants and other stakeholders. So that's the third bullet that I've listed here on the slide. So I think I'll just summarize and wrap up there. So I've gotten involved with the CLSA for the last few months and it's been a really rewarding experience all around. I'm really thankful that I've had this opportunity in a couple of different ways to contribute to the ongoing efforts of the CLSA and I really encourage you if you're even considering it to take a look at some of the data sets that are available and think about how they might match with your interests. Because I really think that one of the strengths of the CLSA is the openness of their platform and the opportunity to really adapt some aspect of the data that's been collected to pursue a research interest and contribute to the research agenda across Canada. So with that, I think I'll wrap up. Thank you. Thank you so much, Nicole. I think, again, I find each of these presentations are building so nicely on each other and I think yours was a great example of a door being opened as an infectious disease epidemiologist when the pandemic hit and your interest in the CLSA. I mean, I think you've taken advantage of that and I think you've been a great value to the COVID related work that the CLSA is doing. I think the one question that I'm gonna, for those of you who know me from my background in knowledge translation, I think the work that you have been doing on the CLSA dashboard has been very intriguing. So I'm just wondering what other opportunities in knowledge translation you perceive with the CLSA COVID-19 study or even the CLSA more in general? Yeah, that's a great question. Thank you, Jennifer. I think with what we're trying to do with the dashboard is just make some of the results a little bit more accessible so that as different stakeholders and different organizations are thinking about planning to kind of mitigate the effects of the pandemic in the coming months and the effects of the lockdown of different populations and the different policies that have been put in place for social distancing, they can really see what types of impact have been occurring in different age groups across different locations and think about how to use that evidence to build it into their future interventions and future programs in order to mitigate the impact of the pandemic. So I think that's one of the ways that I see the dashboard being really valuable to that aspect of stakeholders. I also think that it's actually really valuable for the participants as well and for other researchers in addition, I think we're all kind of going through the pandemic it's such an unusual time. It's really valuable to kind of know what the nature of the shared experience is and kind of what data has taught us about how people are experiencing the pandemic. With some of the others with the influenza and pneumococcal vaccine study that we're planning, we're really hoping that that analysis of CLSA data will really just be kind of the first step to designing an intervention that will improve vaccine uptake among Canadian adults. And we're hoping to use that analysis to inform what the nature of that intervention will be and to use that knowledge to be able to actually take public health action and improve vaccine uptake and prevent these infectious diseases. So that's our hope for the future down the line. Great, thanks for that. The other question I was wondering about is I think what your uniqueness to this panel you bring as an infectious disease epidemiologist and again, not necessarily coming from the that aging research world. I'm just wondering what advice you would give to early career researchers who are looking to get involved in a large national project such as the CLSA whether or not it may on the surface fit with your regular research interests or not. That's a great question as well. My take on the CLSA is there really is something for everyone and so I was really thankful that you invited me to speak on this panel as an infectious disease epidemiologist because the more that I delved into the questionnaires and the more that I looked at the data availability there really seems like there's something there for everyone and there's such a wealth of data that I think as long as you as a researcher kind of know the topics in the area as the umbrella of topics that you're interested in you can find something that will likely match with those interests. So I just really encourage people to take a look at the resources that are available on the website to start seeing what the possibilities are. And if that becomes challenging take a look at some of the previous studies that have been proposed and kind of use that as inspiration to get some ideas going forward. Thank you. I think we will, if anybody else has any questions for Nicole or any of the other presenters obviously we can ask them at the end but now we'll go to Carly Whitmore and we'll get your take on your experiences with CLSA. Thank you. And thank you all for those who've joined us today really is a privilege for me to be here to share my experience working with CLSA as a graduate student. As was said, my name is Carly Whitmore. I'm a PhD student at McMaster University and a trainee with the aging community and health research unit also at McMaster. I am a registered nurse with expertise in psychiatric and mental health. And so it's from this lens that I really position myself and the work that I'm doing with CLSA. And so we've heard some really great examples of how you can engage with CLSA through working groups and ongoing projects but I'm gonna pivot the discussion a bit to speak more about my experience and what a trainee can do with CLSA. And so we'll go back to that previous side. Perfect, thank you. And so at present as part of my dissertation work along with my supervisor Dr. Maureen Merkel-Reed I am co-leading a CLSA approved and catalyst grant funded project entitled explaining self-reported health among community dwelling older adults with multimorbidity and depressive symptoms using a resilience framework. And so I encourage you as other panelists have brought up to check out that approved project list and it's there that you can see my project and those others that have been approved. So because my project serves as a component of my dissertation work it's for this reason that I really do believe that using CLSA data as a graduate student poses not only a fantastic opportunity to use rich and comprehensive multidisciplinary data but also really presents an incredible opportunity to be a part of a broader research community. And so with that I think it's helpful for me to share what drew me to use CLSA data and to also speak about my process. So as I've mentioned as a registered nurse interested in applied health research there really are a lot of opportunities and advantages to using CLSA data. My supervisor had not led a CLSA approved project before but one of my committee members Dr. Catherine Fisher had and she really encouraged me to think about using CLSA data as she was familiar not only with the capacity of the dataset but also the significant opportunity that it presented. So for the sake of this I thought it would be interesting to maybe share what motivated me to use CLSA. We've spoke about the comprehensiveness in the multidisciplinary nature of the data. There was also the opportunity at the time of my application we were just releasing the longitudinal data. And so I was able to build that into my protocol. There's also opportunity to use this data as a launching point for mixed methodological inquiry and that's something that I'm doing in my dissertation. And ultimately the types of questions like was said by Nicole and Jacqueline can be answered by this data. There's few things that I think you could not answer with the comprehensive data that is available. And let's not forget the added perk that as a graduate student using CLSA data is free and that's a pretty big perk when you maybe don't have project funding. And so after speaking with the CLSA team and confirming the variables that are available to me I began that process. And so my experience as a trainee is probably more typical to that of what many people would engage with CLSA through. And even with this typical level engagement there are a lot of benefits and a lot of opportunities specific not only to my career but also my career trajectory like Susan had mentioned. So for example, even in just applying for the data access the data access application in itself much mimics grant applications. And so getting that practice and having that opportunity to flesh out my project was very helpful. It was also very helpful to have the support of the research team and support team at CLSA, they're able to confirm variables that are available to you. They're able to run some preliminary tests that you know what you may be doing once you do get that. Another benefit of this engagement is the collaboration opportunities that exist within this network of researchers. So from data proof project list the social media accounts, ongoing webinars there really are lots of opportunities to collaborate with other trainees as well as the researchers doing similar work. An example of this was when I was applying for the catalyst grant I was able to go into the approved project list and see who was doing similar work and then connect with potential co-applicants and collaborators for this project. And in another world, the summer program on aging would have been a great opportunity this summer for me but in 2021 we'll get there. And there are also quite a few funding opportunities available specific to CLSA such as those catalyst grants. And I think one of the great opportunities that exists is that as we continue along with this project there really is the opportunity to build a career out of the CLSA and the data that exists. And that's what I have to share. Thank you so much, Carly. Again, I think a great example of a trainee that has started to develop her career related to the CLSA. Couple questions for you. One question is what has surprised you most about you explained your story of how you became engaged in the CLSA research but what has surprised you most about how you've been engaged with the CLSA and the CLSA data to date? Yeah, not surprising for those who know me but maybe surprising to others is that I am not a quantitative researcher. This has not been my experience leading into my dissertation. And so it was with this that I was maybe a bit nervous coming in and still maybe a bit nervous about using CLSA data. But what was surprising to me as a nurse and as an applied health researcher was how much I connected with the data. And maybe that sounds a bit silly but as I'm going through and cleaning the data and building some of my own variables I'm really starting to piece together some of these participants and their experiences. And so again, it sounds maybe a bit silly but for example, when you're working with some of the depressive symptom variables and you're starting to see some of the scores and thinking, Jesus, does that person have the supports they need and what could we be doing better in the communities to support people like this? Obviously you can't do that for all the thousands and thousands of people in this data set but what was surprising to me was because it's so comprehensive I was able to connect with it in that way. So I think it's a good point that I think when people think of the CLSA data set it's obviously quantitative research but your research involves a mixed method approach. So you've already touched on a couple challenges but what do you think the biggest challenge is in using the CLSA data set for this type of research one? Yeah, that's a really great question. The biggest challenge at this time for me is the sample. So because CLSA data has been collected and it's been collected from that national sample historically in mixed methods research they suggest and strongly suggest that you use the same sample to do your quantitative and your qualitative analysis. Given the nature of the data collected, that's impossible. That being said, there really is this delicate balance with prudence and stewardship of data. If it's been collected, do you go out and collect what's already available? And so in wanting to be responsible and infill some of those gaps related to potentially some of the limitations in a data set devising a way to sample for qualitative inquiry was really important to me. And so we're in the midst of that. And although that was an expected challenge, we're working towards some of the ways that you can theoretically sample based on variables available in the data set. And so maybe we can check back in a year or so and I can report back how that's going. But for now, that's one of the bigger challenges. And one final question for you, at least for now. I guess as a trainee, what has been your experience connecting with other trainees who might be using the CLSA data and then what has there been a benefit to having this network? Yeah, so my connection with other trainees has really been informal connections. But that being said, it's something that was really important to me as I progressed and as I'm learning. So CLSA Twitter account I'm engaged with and anytime a new project is put out and I'm looking at the project, I'm seeing if there's a trainee involved and you can connect with people that way. I also have the pleasure of connecting with some trainees who are using CLSA data through McMaster and through Mira. The benefit for me has really been support. As I said, I am not familiar or not as familiar with quantitative analysis. And so as I'm problem solving my way through some of this, it's good to have another trainee who's done it or is in the process of doing it. And the other thing I think about is in this climate of large team-based grants, the collaborations I'm making now as a trainee are likely to be potential research partners in the future. And so building these connections at this point is very helpful. So if there are trainees on the call who are interested, always happy to talk and share my experience. Okay, well thank you again to our panelists. I'd now like to open it up to some general questions. We have about just under 15 minutes left. Just a reminder that muting will remain on, but you can enter your questions into the chat box in the bottom right corner of your WebEx. I'm having actually some issues reading the chat box in my field. So I'm going to do my best to decipher what I can read and just sort of go over a couple quick questions first. So I'm gonna say now, if we do miss a question because I, again, it's kind of mumbled up, I do apologize and we will make sure that we follow up with you if we miss your question after. So just quickly, I think one of the first questions I saw was when the dashboard will be available. And so this is something that Nicole can also comment on this. Actually, I'll just let Nicole comment. I'm just gonna, I'm a moderator. I should be talking so much. Well, thank you, Jennifer, but we would welcome your comments as well. Thank you for this question and the interest in the dashboard. The COVID-19 dashboard isn't available quite yet. We haven't released it, but it will be available on the CLSA website. There will be a link to it. However, in the meantime, there is a data access portal for CLSA, for previous data that's been collected, not the COVID data, but for previous data. So I would encourage you to check that one out before in the meantime, while you're waiting for us to release the COVID data, we're hoping to get it out as soon as possible or just finalizing and fine tuning some of the results. Great. And we also had a question about accessing the COVID data. So maybe I might let Susan answer this question. Can you just touch on what we know so far about accessing the COVID data and whether or not you've been a data user so far? Sure. So we're in the midst of collecting the COVID-19 data. So the way that the COVID-19 data works is that there's a baseline questionnaire and then it switches to either weekly or bi-weekly for one month and then it switches to monthly for at least four months. And so we're in the weekly bi-weekly phase right now. We have finalized the baseline data collection and we have almost 30,000 responses to the baseline which is really fantastic. And that's both from participants who were in the tracking and in the comprehensive. And we're in the process of doing a little bit of cleaning of that data. And what will happen is that the COVID-19 research team will work to produce some kind of general profile of what that baseline data looks like. And what we'll probably do is wait until all of the data is available before it's released through the data and sample access committee. Thanks Susan. We also have a question about, and maybe Carly can talk about this a little bit about the fee waivers. Maybe you can just describe a little bit about how you went about that. And if Susan maybe can comment on, I think there's a question about getting a fee waiver if your project was a catalyst grant or not and that might be, we might need to look at specific cases offline because I'm not sure, but so maybe Carly you can just touch on what getting that fee, what that process is and then Susan you can fill in any blank. Yeah, so initially when I was filling in the data access application, there's a tick box that says, are you a graduate student? And if you are, you tick that box and it says underneath of it that the fee would be waived if the project is approved and that you are a graduate student. That being said sort of to lead into that next part because I did receive a catalyst grant that fee waiver doesn't apply in my instance anymore but for graduate students, yeah, the fee is waived. So I can just depend on that. So if you are a graduate student either a master's or a PhD student and are using the data for your thesis, you can get access to the data. You can also have access to the data if you are a postdoctoral fellow and the limit is one access per fellowship. But there is a caveat around the catalyst. Because the catalyst come with funding, there's a requirement that you build in the data access fees to the catalyst grant. And the reason that we do that is because, I mean really we generally operate on, it's not a cost recovery basis, that's for sure but it's a cost supported basis. And if we know that people are getting funding from another source then it's a useful way to be able to support the CLSA as well. We did have one question and I'm about the nature of the longitudinal data and there only being two time points available for some of it right now. I am gonna suggest to the Russell Kabir. Maybe that's more of a methodological question we could take offline. But the question was basically whether any of you know about any ways to, any statistical techniques when you don't have, when you only have two time points and how you can get a sense of that longitudinal data. Very long, I won't read it word by word but any comments on that? That's what I thought. I go back. Yeah, I mean it's not truly longitudinal in that there's only two data points but it's also no longer cross-sectional. So there's a bunch of things that you can do. You can map change or you can build in a lag time. There's a number of strategies that you can utilize to make it useful in a longitudinal sense but it will become even more useful as each data point comes along. And just in response to when the follow-up one data will be available. So follow-up one data has been collected. Some of it has been released or will be released shortly but because we're doing the COVID study at the same time and there's a number of pressures from various different avenues, it will be a little bit yet. Thanks, Susan. Okay, so another question just about, we usually always get this question from somebody who's late and that's about whether they'll have access to the webinar and yes, the webinar will be available and the recording afterwards. So it will come via a link. So question now from David Daw. Can CELSA data be linked with provincial administrative databases? Susan, did you wanna take that one? Sure. All right. I think answers to that question. Yeah. Technically, yes. Realistically, no. At least at this point in time. So we're working a lot right now with the provinces, with Kaihai, with Statistics Canada and also with the Canadian data platform around issues related to this. The challenge with the CLSA is that it's a national study and as you know, administrative data is within the provincial jurisdictions. And we have one pilot study that is currently underway to look at the way in which this could work and we're going to slowly roll it out and work with other provinces but it's a very big challenge to do it across the board. And so we really have not gone there yet. But we will. Yes, Susan McDaniel also asked a question about linkage and that was whether we can link to stats. Stats can micro level data available in the RDCs. And again, I think that's something that we've been exploring and it will happen. It's just a matter of. It's just a matter of time. Yeah. And maybe that's a nice topic for a future webinar about initiatives that we have on data linkage. OK, so we'll move on with a few more here. The link to the recording is now posted for anyone who just wants to be able to go into it. A question from Anne Lynn. Is there any scope for collecting more comprehensive dietary data such as using using a full FFQ in future? I don't know. I can answer that. We explored this issue a lot. And currently the there's issues around software compatibility and, you know, there's the length. I don't discount that it could not happen at some point in the future, but it's been really difficult for us to figure out how to use the how to get the micro files that are needed or a food frequency questionnaire. And then also just the burden on participants to do it. I just I notice usually around this time people start dropping out. So I just wanted to remind if you're able for participants to complete the evaluation before you pop out. That would be great. But we do have a few more questions that I'd like to try to get through. One is from a PhD student, Madara, who's the CLSA who's planning to use the CLSA data for their thesis. How long approximately does it take to access get access to the data after a request is sent in? So, Carly, how long did it take to get your data once you requested it? Do you recall? It's been a bit. There are a number of steps along the way. And so I think it would be hard to comment on how long from application to actually receiving the data. And there are meetings that occur. So it's all in how you time your application when those meetings co-assign with review. A couple of months, I think, would have been a fair estimation from application to actually having data. And I think some of that was my own doing. I can fill that in a little bit too. So usually what happens is from the time that the deadline, so there's usually three deadlines to submit applications in a year. And from the submission date, it takes us about two months to process the application. It has to go through reviewers. We have to meet. It has to be recommended to the scientific management team. It all has to be approved. And then we're at the point where we can create a data access agreement with you. And the data access agreement is done between institutions. And again, it can be variable at that point because it's no longer in the CLSA's hands once it goes to the institution. And sometimes there's back and forth with the institution. Sometimes people just let it fall off the radar for a while and it can take a little bit. But I think if everything goes smoothly from beginning to finish, three months is a realistic picture. Okay. Thanks, Susan. And I know at the last few questions, I think are from our international audience. One is just some lovely comments from Rosa in Mexico, hoping to collaborate potentially sometime in the future on a similar study. Amanda, who I know is in Detroit because we've just recently touched base during this webinar, we did our postdoc work together. She's wondering when biospecimens would become available. And then the last question is about just international researchers accessing the data. So Susan, maybe you can touch base about the biospecimens quickly and also researchers outside Canada. Sure. A lot of the biospecimen data is already available and you can find it, you can find out what's available on the website. And we have some of the genomics data available as well. And we're continually processing, we have metabolomics data available and also epigenetics data available. So that is increasing, as well as the basic biochemistry markers and some analytic biospecimens as well. So there's a fair bit out there already. Sorry, what was the other question? Oh, international researchers. So the data is available to international researchers. It's a slightly higher fee, but not astronomical. And, but if you are an international student, you don't qualify for the same level of access to data. So you have to be either enrolled at a Canadian university or you have to be a Canadian student enrolled overseas and hold a Canadian award. But there's no restriction on accessing the data. Thank you, Susan. And I think this is probably a good time to end. I know we're two minutes over. Thank you again to all of you. We really appreciate your participation in the CLSA webinar series and in particular this one today. The next deadline for applications is October 7th of 2020. Please visit the CLSA website under data access to review what data is available. Any further information and details about the application process. I'd also like to remind everyone to complete their survey located under the polling option. If you don't see it beside the chat button, then please click the dropdown arrow. Thank you to everyone who tuned in to our CLSA webinar series today and to all of those who responded to our feedback poll. We will resume our webinars in September after hiatus over the next couple of months, over the summer. And remember, the CLSA promotes this webinar series using the hashtag CLSA webinar. So we do invite you to follow us on Twitter at CLSA underscore ELCV. And thank you again to the presenters and all of you for attending and Shirley and Laura in the background. I hope you all have a great summer and a great long weekend coming up. Bye everyone.