Understanding the impact of the COVID-19 pandemic on U.S. older adults: self-reported pandemic-related concerns and consequences in a cross-sectional survey study.

Background and objectives: The purpose of this study was to explore COVID-19 pandemic-related concerns among a racially and ethnically representative sample of older adults in the U.S. Research design and methods: Participants were 501 English-speaking adults 60 years and older recruited online nationally across the U.S. from Amazon Mechanical Turk (mTurk) and Prolific Research Platforms during June of 2020. Data comes from a larger cross-sectional survey. We content analyzed open-ended responses about pandemic-related concerns and observed responses to a checklist of items created by the research team to assess for specific physical, social, and financial consequences experienced due to the pandemic. Results: A majority of the sample (92%) reported at least one pandemic-related concern, with the highest percentage expressing concerns coded as Concern for Others (28%), Physical Health (27%), Socializing (24%), Finance (15%) and Socio-Political-Economic (14%). Participants reported high concern severity (M = 4.03, SD = 1.04) about their concerns mentioned in response to the open-ended concerns question. When prompted with a checklist of items, participants frequently endorsed disruption in social activities as a consequence of the pandemic (83%), disruptions that could impact physical health (45%), and concern over finances as a consequence of the pandemic (41%). Discussion and implications: Older adults most frequently mentioned concerns about the well-being and behavior of others, one's own physical health, and the impacts of the pandemic and social distancing policies on social activities. Findings align with the Socioemotional Selectivity Theory and point to the importance of supporting older adults to maintain meaningful social engagement under conditions of a pandemic and social distancing policies.

Recruitment and Retention in Remote Research: Learnings From a Large, Decentralized Real-world Study.

BACKGROUND: Smartphones are increasingly used in health research. They provide a continuous connection between participants and researchers to monitor long-term health trajectories of large populations at a fraction of the cost of traditional research studies. However, despite the potential of using smartphones in remote research, there is an urgent need to develop effective strategies to reach, recruit, and retain the target populations in a representative and equitable manner. OBJECTIVE: We aimed to investigate the impact of combining different recruitment and incentive distribution approaches used in remote research on cohort characteristics and long-term retention. The real-world factors significantly impacting active and passive data collection were also evaluated. METHODS: We conducted a secondary data analysis of participant recruitment and retention using data from a large remote observation study aimed at understanding real-world factors linked to cold, influenza, and the impact of traumatic brain injury on daily functioning. We conducted recruitment in 2 phases between March 15, 2020, and January 4, 2022. Over 10,000 smartphone owners in the United States were recruited to provide 12 weeks of daily surveys and smartphone-based passive-sensing data. Using multivariate statistics, we investigated the potential impact of different recruitment and incentive distribution approaches on cohort characteristics. Survival analysis was used to assess the effects of sociodemographic characteristics on participant retention across the 2 recruitment phases. Associations between passive data-sharing patterns and demographic characteristics of the cohort were evaluated using logistic regression. RESULTS: We analyzed over 330,000 days of engagement data collected from 10,000 participants. Our key findings are as follows: first, the overall characteristics of participants recruited using digital advertisements on social media and news media differed significantly from those of participants recruited using crowdsourcing platforms (Prolific and Amazon Mechanical Turk; P<.001). Second, participant retention in the study varied significantly across study phases, recruitment sources, and socioeconomic and demographic factors (P<.001). Third, notable differences in passive data collection were associated with device type (Android vs iOS) and participants' sociodemographic characteristics. Black or African American participants were significantly less likely to share passive sensor data streams than non-Hispanic White participants (odds ratio 0.44-0.49, 95% CI 0.35-0.61; P<.001). Fourth, participants were more likely to adhere to baseline surveys if the surveys were administered immediately after enrollment. Fifth, technical glitches could significantly impact real-world data collection in remote settings, which can severely impact generation of reliable evidence. CONCLUSIONS: Our findings highlight several factors, such as recruitment platforms, incentive distribution frequency, the timing of baseline surveys, device heterogeneity, and technical glitches in data collection infrastructure, that could impact remote long-term data collection. Combined together, these empirical findings could help inform best practices for monitoring anomalies during real-world data collection and for recruiting and retaining target populations in a representative and equitable manner.

Effectiveness of Mental Health Apps for Distress During COVID-19 in US Unemployed and Essential Workers: Remote Pragmatic Randomized Clinical Trial.

BACKGROUND: During the COVID-19 pandemic, the general public was concerned about the mental health impacts of unemployment due to COVID-19 and the stress essential workers experienced during this time. Several reports indicated that people in distress were turning to digital technology, but there was little evidence about the impact of these tools on mitigating distress. OBJECTIVE: This study seeks to determine the acceptability, feasibility, usability, and effectiveness of mobile mental health apps for decreasing mental health symptoms in essential workers and unemployed individuals with suicide risk. METHODS: We recruited participants who indicated that they were unemployed because of COVID-19 or were COVID-19-designated essential workers. Participants were randomized to 1 of 4 free commercial mobile apps for managing distress that were (1) highly rated by PsyberGuide and (2) met the criteria for intervention features these participants indicated were desirable in a previous survey. Participants used the apps for 4 weeks and completed baseline and 4-week self-assessments of depression, anxiety emotional regulation, and suicide risk. RESULTS: We found no differences between the apps in any outcome but did find significant changes in depression and anxiety over time (Patient Health Questionnaire [PHQ]-9: estimate=-1.5, SE 0.2, 95% CI -1.1 to -1.8, P<.001; Generalized Anxiety Disorder Scale [GAD]-7: estimate=-1.3, SE 0.2, 95% CI -1.0 to -1.6, P<.001). We found no significant changes in suicidal behavior (Suicide Behaviors Questionnaire-Revised [SBQ-R]) or emotional regulation (Difficulties in Emotion Regulation Scale - Short Form [DERS-SF]) for the 4 weeks. We did find a significant dose-response pattern for changes in depression and anxiety. Using the app at least once a week resulted in greater improvements in treatment conditions over time on depression (estimate=-0.6, SE 0.2, 95% CI 1.0-0.2, P=.003) and anxiety (estimate=0.1, SE 0.2, 95% CI 0.4-0.6, P=.78). There was no association between app frequency and changes in suicidal behavior (SBQ-R) or emotional regulation (DERS-SF). We further found a significant difference between the conditions with regard to app usability, with the control app being the most usable (meanBeautiful Mood 72.9, SD 16.7; meanCOVID Coach 71.2, SD 15.4; meanCalm 66.8, SD 17.3; mean7 Cups 65.2, SD 17.7). We found no significant differences for app acceptability or appropriateness. CONCLUSIONS: Few studies have evaluated prospectively the utility and usability of commercial apps for mood. This study found that free, self-guided commercial mobile mental health apps are seen as usable, but no one app is superior to the other. Although we found that regular use is indicated for effects on depression and anxiety to occur in those who are more symptomatic, regression to the mean cannot be ruled out. TRIAL REGISTRATION: ClinicalTrials.gov NCT04536935; https://tinyurl.com/mr36zx3s.

"Do More, Feel Better": Pilot RCT of Lay-Delivered Behavioral Activation for Depressed Senior Center Clients.

This pilot randomized control trial (RCT) tested "Do More, Feel Better" (DMFB), a lay-delivered Behavioral Activation intervention for depressed senior center clients. The study examined: (1) the feasibility of training older lay volunteers to fidelity; and (2) the acceptability, safety, and impact of the intervention. Twenty-one lay volunteers at four senior centers were trained in DMFB. Fifty-six depressed clients were randomized to receive 9 sessions of DMFB or Behavioral Activation delivered by social workers (MSW BA). Research assessments of overall client activity level (BADS) and depression severity (HAM-D) were conducted at baseline and Weeks 3, 6, and 9. Eighty-one percent of lay volunteers who underwent training were formally certified in DMFB. Depressed clients receiving each intervention reported high levels of satisfaction and showed large and clinically significant changes in 9-week activity level (d ≥ 1.35) and depression severity (d ≥ 3.34). Differences between treatment groups were very small for both activity level (dMSW = 0.16; 95% CI, -0.70 to 1.02) and depression (dMSW = 0.14; 95% CI, -0.63 to 0.91). Increases in activity level were associated with decreases in depression (ß = -0.42; 95% CI, -0.55 to -0.30). Both interventions appeared to work as intended by increasing activity level and reducing depression severity. "Do More, Feel Better" shows the potential of evidence-based behavioral interventions delivered by supervised lay volunteers, and can help address the insufficient workforce available to meet the mental health needs of community-dwelling older adults.

Generational Perspectives on Technology's Role in Mental Health Care: A Survey of Adults With Lived Mental Health Experience.

INTRODUCTION: Personal technology (e.g., smartphones, wearable health devices) has been leveraged extensively for mental health purposes, with upwards of 20,000 mobile applications on the market today and has been considered an important implementation strategy to overcome barriers many people face in accessing mental health care. The main question yet to be addressed is the role consumers feel technology should play in their care. One underserved demographic often ignored in this discussion are people over the age of 60. The population of adults 60 and older is predicted to double by 2,050 signaling a need to address how older adults view technology for their mental health care. OBJECTIVE: The objective of this study is to better understand why digital mental health tools are not as broadly adopted as predicted, what role people with lived mental health experience feel technology should play in their care and how those results compare across age groups. METHOD: In a mixed-methods approach, we analyzed results from a one-time cross-sectional survey that included 998 adults aged 18-83 with lived experience of mental health concerns recruited from Prolific, an online research platform. We surveyed participant's use of technology including their perspectives on using technology in conjunction with their mental health care. We asked participants about their previous use of digital mental health tools, their treatment preferences for mental health care, and the role technology should play in their mental health care. RESULTS: Across all age groups, respondents had favorable views of using digital mental health for managing mental health care. However, older adults rated their acceptability of digital mental health tools lower than middle-aged and younger adults. When asked what role technology should play in mental health care in an open-ended response, most participants responded that technology should play a complementary role in mental health care (723/954, 75.8%). CONCLUSION: Digital mental health is seen as a valuable care management tool across all age groups, but preferences for its role in care remain largely administrative and supportive. Future development of digital mental health should reflect these preferences.