WEBVTT Kind: captions Language: en 00:00:00.400 --> 00:00:06.960 All right, thank you so much. So I want to share  some of the work that I've been doing in my lab,   00:00:07.920 --> 00:00:13.600 specifically looking at psychological well-being.  So it nicely segues from the previous speakers.  00:00:14.880 --> 00:00:21.520 So we have lots of reports that  through the pandemic individuals   00:00:21.520 --> 00:00:27.280 have been impacted as far as their mental  health. As far as self-reports about greater   00:00:27.280 --> 00:00:33.040 distress during the pandemic to higher  prevalence rates of depression and anxiety.   00:00:34.480 --> 00:00:37.920 And some of the work that I've done  where we've actually been able to,   00:00:37.920 --> 00:00:43.840 you know, assess people and compare their  depression and anxiety and stress levels   00:00:43.840 --> 00:00:51.120 to their pre-pandemic levels. And we've seen  significant increases. But people have experienced   00:00:51.120 --> 00:00:56.800 the pandemic and been affected by it differently  and so what we've been focusing on is really to   00:00:56.800 --> 00:01:04.160 think about how groups may differ as far as the  consequence, the psychological consequences.  00:01:05.120 --> 00:01:12.000 And one distinction we've been focusing on is to  think about different age groups. And so what got   00:01:12.000 --> 00:01:19.360 us sort of started on this is thinking about older  adults who are at higher risk for severe illness,   00:01:19.360 --> 00:01:26.960 hospitalization, higher mortality rates. And so  with that then does this place them as far as   00:01:26.960 --> 00:01:35.200 with this disease risk at maybe a worse position  as far as thinking about the impact the pandemic   00:01:35.200 --> 00:01:40.800 is having on their psychological well-being?  So we could see greater levels of depression   00:01:40.800 --> 00:01:46.640 and anxiety in our older population.  Alternatively that might not be the case.   00:01:47.200 --> 00:01:53.840 So what we know prior to the pandemic - with age  we generally have better psychological well-being,   00:01:54.560 --> 00:01:59.840 on average. And there's a phenomenon  - the well-being paradox - in which,   00:01:59.840 --> 00:02:05.280 you know, although there are many negative things  that come with aging as far as thinking about   00:02:05.280 --> 00:02:11.440 health declines, loss of loved ones, we see this  better emotional and psychological well-being.   00:02:11.440 --> 00:02:18.560 So alternatively, with the pandemic we may not  see, like I said, as much of an impact or as   00:02:18.560 --> 00:02:26.240 great of an impact in our older population. So we took the the project that we were doing   00:02:26.240 --> 00:02:32.160 funded through NSF to really try and tease this  apart and look at potential age differences.   00:02:32.800 --> 00:02:41.840 So we recruited a national sample of U.S. adults  through Qualtrics and we had a relatively equal   00:02:41.840 --> 00:02:46.560 number of different age groups. So we have  our younger middle aged and older adults.   00:02:47.520 --> 00:02:54.880 And we surveyed them across time, but I'm going  to focus in on sort of our initial surveys early   00:02:54.880 --> 00:03:01.040 in the pandemic where we were seeing higher levels  of depression and anxiety. And so as part of our   00:03:01.040 --> 00:03:06.480 survey we had the patient health questionnaire  for depression and generalized anxiety   00:03:06.480 --> 00:03:14.000 disorder. Seven was our anxiety measure. And on average, like others, we did find   00:03:14.000 --> 00:03:19.520 higher levels of depression and anxiety -  significantly higher than pre-pandemic levels.   00:03:21.840 --> 00:03:28.640 But there were differences across the age span.  So our older adults were reporting less depression   00:03:28.640 --> 00:03:33.600 and anxiety than our younger adults. And so to give you a visual of kind of   00:03:33.600 --> 00:03:39.840 the breakdown of this - what I have  here on the x-axis we have our degree   00:03:40.640 --> 00:03:47.360 or severity of depression and anxiety symptoms.  Our white dotted bars are our younger adults.   00:03:47.360 --> 00:03:53.440 Our striped bars are middle aged adults. And our  gray bars are our older adults. And the bars are   00:03:53.440 --> 00:03:58.400 simply the proportion in each age group that  fell into these different severity categories.   00:03:58.960 --> 00:04:07.840 So what you'll see for our older adults, about  70% were reporting minimal to no symptoms of   00:04:07.840 --> 00:04:14.080 depression or anxiety as compared to our younger  adults who are just under 40% - I think I might   00:04:14.080 --> 00:04:19.440 have said that wrong, sorry! Just under 40% in  our younger adults. So we see this big difference   00:04:19.440 --> 00:04:25.440 as far as thinking about the breakdown and it  really is our younger and middle-aged adults who   00:04:25.440 --> 00:04:30.000 are driving in those higher rates of depression  and anxiety that we were seeing in our sample.  00:04:31.520 --> 00:04:33.120 So to add to this then,   00:04:34.720 --> 00:04:41.680 you know, what stood out within our sample - older  adults were more concerned about COVID, so they   00:04:41.680 --> 00:04:47.120 were more worried about COVID, but we weren't  seeing higher levels of depression and anxiety.   00:04:48.160 --> 00:04:54.560 Particularly this stood out to us when we look at  the association between COVID concerns and mental   00:04:54.560 --> 00:05:00.000 health. Those who thought they were more likely  to contract COVID were reporting greater anxiety.   00:05:00.000 --> 00:05:04.400 But like I said, we weren't seeing that  come out when we broke it down by age  00:05:05.360 --> 00:05:12.320 So when we looked at that moderation, and so here  on the y-axis we have anxiety, x-axis we have   00:05:12.320 --> 00:05:19.280 perceived likelihood of contracting COVID. For  our younger participants, with the dotted line,   00:05:19.280 --> 00:05:25.200 we have that positive association. The greater the  likelihood that I'm going to contract COVID the   00:05:25.200 --> 00:05:31.200 more anxious I am. But for our older participants,  that solid line, we saw no significant   00:05:31.200 --> 00:05:38.080 association. So despite this heightened concern  that wasn't then - I said sort of translating - to   00:05:38.080 --> 00:05:44.000 greater anxiety. And some of this we think is  probably due to thinking about that well-being   00:05:44.000 --> 00:05:50.320 paradox. As we get older we're better able to  regulate our emotions, we have better coping   00:05:50.320 --> 00:05:56.160 strategies, we've been through more stressors, and  so we maybe have some greater resilience with age.   00:05:56.160 --> 00:06:03.600 And so we're not seeing those negative or as great  of an impact as far as psychological well-being.  00:06:05.200 --> 00:06:12.720 To expand on this, then, we started to also think  about the different pandemic related stressors and   00:06:12.720 --> 00:06:18.080 what are the factors that are contributing  to declines in depression or exceeding   00:06:18.080 --> 00:06:24.160 increases in depression and anxiety.  And so beyond our concern about COVID,   00:06:24.800 --> 00:06:31.920 disease threat, there is social isolation with  self-quarantining, working and schooling from   00:06:31.920 --> 00:06:38.080 home, less social contact - that generally has  negative consequences for our mental health.   00:06:39.920 --> 00:06:47.040 A lot of financial, economic concerns, job,  food insecurity, disruption to daily life,   00:06:47.040 --> 00:06:51.840 we weren't able to do and many of us are still  not doing the things we normally would do   00:06:51.840 --> 00:06:57.360 on a day-to-day basis. All of these  things affect our psychological well-being   00:06:57.360 --> 00:07:03.360 so what we wanted to do is really think  about these simultaneously to tease apart   00:07:03.360 --> 00:07:09.040 what are the stressors that really seem  to be driving anxiety and depression.  00:07:10.560 --> 00:07:17.120 So with the sample that we had previously  surveyed, we actually looked at a sub sample   00:07:17.120 --> 00:07:23.920 specifically looking at participants who had  indicated some level of employment. So we kind   00:07:23.920 --> 00:07:29.600 of took out our retirees and students  basically, so that we could look at   00:07:29.600 --> 00:07:36.880 job insecurity. And we surveyed these individuals  in early to mid-April, so again, still early in   00:07:36.880 --> 00:07:41.680 the pandemic where we were seeing particularly  heightened depression and anxiety levels.  00:07:42.960 --> 00:07:47.680 We had our same measures of depression and  anxiety, and then like I said, we assessed   00:07:47.680 --> 00:07:53.200 a variety of different pandemic stressors  from simple concern and worry about COVID, job   00:07:53.200 --> 00:07:59.760 insecurity, financial concerns, social distancing,  self-quarantine, main disruption to daily life,   00:07:59.760 --> 00:08:04.480 and then we also asked about how much they  were following news coverage of COVID.  00:08:06.640 --> 00:08:14.560 Now, at a bivariate level, if we just look at each  of those stressors in relation to depression and   00:08:14.560 --> 00:08:21.200 anxiety, and I'm going to zero in your attention  to this this section of the table. So in columns   00:08:21.200 --> 00:08:26.320 one and two here we've got our anxiety and  depression levels. All of our predictors - all   00:08:26.320 --> 00:08:33.920 of our stressors except for social distancing were  significantly associated with worse mental health,   00:08:33.920 --> 00:08:39.040 right? So the more concerned you were about  finances, your job, the more concerned you were   00:08:39.040 --> 00:08:43.520 about COVID, the more you were following  news coverage and self-quarantining,   00:08:43.520 --> 00:08:49.840 the greater your depression and anxiety. What  I will highlight, and similar to what Valerie   00:08:49.840 --> 00:08:55.600 was saying, a few of these are particularly,  you know, thinking about the effects are much   00:08:55.600 --> 00:09:03.200 stronger. So financial concern, job insecurity,  perceived likelihood of contracting COVID,   00:09:03.200 --> 00:09:10.960 were sort of more the stronger effects. Now  beyond the bivariate association, because we're   00:09:10.960 --> 00:09:15.920 not just experiencing one of these stressors,  we have a lot of these going on all at once.  00:09:16.480 --> 00:09:19.840 We wanted to know if we  consider these simultaneously,   00:09:20.400 --> 00:09:26.880 which are the stressors that really stand out  as being related to anxiety and depression?   00:09:26.880 --> 00:09:32.480 So we ran some regression models and we also we  controlled for a number of different demographics   00:09:32.480 --> 00:09:39.360 and participant health status. And what we  saw when we took all of the predict - all of   00:09:39.360 --> 00:09:46.720 the stressors into account at once with regard to  anxiety - the stressors that that were significant   00:09:46.720 --> 00:09:53.200 and stood out [were]: that perceived likelihood  of infection, if you were watching more news about   00:09:53.200 --> 00:10:01.120 COVID, and financial concerns were the strongest  predictors for depression. So we have this kind   00:10:01.120 --> 00:10:08.240 of odd negative association with the extent  to which we're following news. That may be a   00:10:08.240 --> 00:10:14.720 suppression effect or it may be some indication  of behavioral activation if people were - if   00:10:14.720 --> 00:10:21.120 you're less depressed and more engaged, maybe you  were engaging with this material more. But we did   00:10:21.120 --> 00:10:26.960 see that job insecurity. The more worried you were  about your job, the higher your depression levels.  00:10:28.880 --> 00:10:35.600 So with this, as others have pointed out, we  are seeing significant impact on psychological   00:10:35.600 --> 00:10:42.240 health stemming from and during the  pandemic. Groups are experiencing this   00:10:42.240 --> 00:10:49.600 differently within our sample. We saw that  our older participants were faring better,   00:10:49.600 --> 00:10:55.680 not to say that they were unaffected by any means  but compared to younger adults we weren't seeing   00:10:55.680 --> 00:11:02.400 the levels of anxiety and depression. And those  pandemic stressors - there are a variety of them,   00:11:03.520 --> 00:11:10.080 but certain ones stood out as being particularly  concerning: financial concerns, job insecurity,   00:11:10.080 --> 00:11:15.840 that perceived likelihood of infection. So moving  forward, and what we're kind of focusing on now,   00:11:15.840 --> 00:11:21.920 is taking this information and looking at  the time course of psychological well-being   00:11:21.920 --> 00:11:29.360 across the pandemic and how that maps onto changes  in those stressors and to what extent those   00:11:29.360 --> 00:11:35.680 patterns differ across groups. Looking at age,  but we're also doing quite a bit looking at   00:11:36.480 --> 00:11:42.080 racial and ethnic groups that have been  affected very differently. And the importance   00:11:42.080 --> 00:11:48.240 of doing that looking at this group by stress or  interaction as far as developing interventions,   00:11:48.240 --> 00:11:55.760 targeted interventions, to really speak to what  are the the most prevalent and salient stressors   00:11:55.760 --> 00:12:00.640 and how can we provide support to reduce  that and improve psychological well-being.  00:12:02.800 --> 00:12:08.640 So thank you to NSF and thank you to my graduate  students for all of their help. Thank you   00:12:08.640 --> 00:12:11.760 and I'm happy to answer any questions.