Formative Evaluation of a Student Symptom Decision Tree for COVID-19.

Objectives: In support of schools restarting during the COVID-19 pandemic, some schools partnered with local experts in academia, education, community, and public health to provide decision-support tools for determining what actions to take when presented with students at risk for spreading infection at school. Methods: The Student Symptom Decision Tree, developed in Orange County, California, is a flow chart consisting of branching logic and definitions to assist school personnel in making decisions regarding possible COVID-19 cases in schools which was repeatedly updated to reflect evolving evidence-based guidelines. A survey of 56 school personnel evaluated the frequency of use, acceptability, feasibility, appropriateness, usability, and helpfulness of the Decision Tree. Results: The tool was used at least 6 times a week by 66% of respondents. The Decision Tree was generally perceived as acceptable (91%), feasible (70%), appropriate (89%), usable (71%) and helpful (95%). Suggestions for improvement included reducing the complexity in content and formatting of the tool. Conclusions: The data suggest that school personnel found value in the Decision Tree, which was intended to assist them with making decisions in a challenging and rapidly evolving pandemic.

Comparing Real-World Impacts of Cohorts using the Translational Science Benefits Model

OBJECTIVES/GOALS: The Translational Science Benefits Model (TSBM), developed at Washington University in St. Louis, was used to create a survey to collect group-level data on the real-world impacts of research. It was used with two cohorts of CTSA-supported pilot studies to compare the benefits of campus-community partnerships to campus-only projects. METHODS/STUDY POPULATION: Investigators from two funding streams were surveyed: a campus-based cohort (n=31), and a campus-community partnership cohort (n=6). All studies were related to COVID-19. The Translational Benefits Survey collected quantitative and qualitative data for each of the 30 TSBM benefits, in 4 benefit categories: clinical, community, economic and policy. Text provided by investigators to support each reported benefit was evaluated by two coders through a process that required coder consensus to verify a benefit as realized. Verified benefits were aggregated for each cohort, and the percentage of projects per cohort with realized clinical, community, economic and policy benefits were calculated. RESULTS/ANTICIPATED RESULTS: Campus-community partnerships did not realize any clinical benefits, whereas 26% of campus-based projects realized at least one clinical benefit. In contrast, campus-community partnerships were more likely to realize community health benefits (17% vs 10% of campus projects) and economic benefits (17% vs 13% of campus projects). We identified a substantial amount of self-reported benefits (64% across all categories) that were unable to be confirmed as realized using the provided text, which either described activities not relevant to the selected benefit, or lacked critical details needed to verify that the benefit was realized. DISCUSSION/SIGNIFICANCE: This project demonstrates that the TSBM can be utilized to collect group-level data and to compare cohorts'real-world benefits. It also illuminates the need to improve the process for verifying self-reported benefits. Sharing data on these real-world impacts has the potential to convey the strengths of translational science to the public.

The Relationship Between Exercise Habits and Stress Among Individuals With Access to Internet-Connected Home Fitness Equipment: Single-Group Prospective Analysis.

BACKGROUND: Physical activity (PA) confers numerous benefits to health and health care costs, yet most adults are not meeting recommended PA guidelines. Stress may be a factor that influences PA behavior. Research investigating the impact of stress on PA has yielded inconsistent findings. Most studies find that stress negatively impacts PA, but there is some evidence that habitual exercising buffers this association. OBJECTIVE: This study aims to examine the relationship between stress and exercise habits among habitual exercisers with internet-connected home fitness equipment (Peloton Bike) during the COVID-19 lockdown. METHODS: Participants were recruited through Facebook (N=146) and asked to complete an internet-based survey that assessed COVID-19-related stressors, perceived stress associated with those stressors, and general perceived stress. Self-reported exercise was assessed on the survey using the Godin Leisure-time Exercise Questionnaire (GLTEQ). Participants were also asked for consent to access their Peloton usage data through the Peloton platform. From their usage data, the frequency and duration of cycling classes was calculated for 4 weeks prior to and 12 weeks following the survey. Hierarchical regression equations tested the association between stress reported on the survey and subsequent exercise participation. Exercise participation was quantified both as the frequency and duration of Peloton cycling over the 12 weeks following the survey and as self-reported moderate to vigorous activity on a second survey completed by a subset of participants 12 weeks after the initial survey. RESULTS: There were 146 participants in our Peloton analysis sample and 66 in the self-reported exercise analysis. Peloton user data showed that study participants cycled frequently (mean 5.9 times per week) in the month prior to the initial survey, and that presurvey Peloton use was a strong predictor of exercise frequency (R2=0.57; F2,143=95.27; P<.001) and duration (R2=0.58; F2,143=102.58; P<.001) for the 12 subsequent weeks. Self-reported overall exercise likewise showed that this sample was very active, with an average of more than 8 times per week of moderate to vigorous exercise at the initial survey. Self-reported exercise on the initial survey was a strong predictor of self-reported exercise 12 weeks later (R2=0.31; F1,64=29.03; P<.001). Perceived stress did not impact Peloton cycling duration or frequency (P=.81 and .76, respectively) or self-reported exercise (P=.28). CONCLUSIONS: The results suggest that stress did not negatively impact exercise participation among habitually active adults with access to internet-connected home fitness equipment. Habitual exercise may buffer the impact of stress on participation in regular moderate to vigorous activity. Future research should examine the role that the availability of home-based internet-connected exercise equipment may play in this buffering.

Feasibility and acceptability of a structured quality by design approach to enhancing the rigor of clinical studies at an academic health center.

INTRODUCTION: Clinical trials are a critical step in the meaningful translation of biomedical discoveries into effective diagnostic and therapeutic interventions. Quality by design (QbD) is a framework for embedding quality into the design, conduct, and monitoring of clinical trials. Here we report the feasibility and acceptability of a process for implementing QbD in clinical research at an academic health center via multidisciplinary design studios aimed at identifying and prioritizing critical to quality (CTQ) factors. METHODS: The Clinical Trial Transformation Initiative's Principles Document served as a guide to identify and categorize key CTQ factors, defined as elements of a clinical trial that are critical to patient safety and data integrity. Individual trials were reviewed in CTQ design studios (CTQ-DS) and the feasibility and acceptability of this intervention was examined through post-meeting interviews and surveys. RESULTS: Eight clinical research protocols underwent the QbD evaluation process. The protocols ranged from multicenter randomized clinical trials to nonrandomized investigator-initiated studies. A developmental evaluation informed the iterative refinement of the CTQ-DS process, and post-meeting surveys revealed that CTQ-DS were highly valued by principal investigators (PIs) and resulted in multiple protocol changes. CONCLUSIONS: The present study demonstrated that QbD principles can be implemented to inform the design and conduct of clinical research at an academic health center using multidisciplinary design studios aimed at identifying and prioritizing CTQ elements. This approach was well received by the participants including study PIs. Future research will need to evaluate the effectiveness of this approach in improving the quality of clinical research.

Rise in Use of Digital Mental Health Tools and Technologies in the United States During the COVID-19 Pandemic: Survey Study.

BACKGROUND: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically. OBJECTIVE: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health. METHODS: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects. RESULTS: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types. CONCLUSIONS: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy.