ABSTRACT
In response to the rapidly evolving coronavirus disease 2019 (COVID-19) pandemic, the All of Us Research Program longitudinal cohort study developed the COVID-19 Participant Experience (COPE) survey to better understand the pandemic experiences and health impacts of COVID-19 on diverse populations within the United States. Six survey versions were deployed between May 2020 and March 2021, covering mental health, loneliness, activity, substance use, and discrimination, as well as COVID-19 symptoms, testing, treatment, and vaccination. A total of 104,910 All of Us Research Program participants, of whom over 73% were from communities traditionally underrepresented in biomedical research, completed 275,201 surveys; 9,693 completed all 6 surveys. Response rates varied widely among demographic groups and were lower among participants from certain racial and ethnic minority populations, participants with low income or educational attainment, and participants with a Spanish language preference. Survey modifications improved participant response rates between the first and last surveys (13.9% to 16.1%, P < 0.001). This paper describes a data set with longitudinal COVID-19 survey data in a large, diverse population that will enable researchers to address important questions related to the pandemic, a data set that is of additional scientific value when combined with the program's other data sources.
Subject(s)
COVID-19 , Population Health , Humans , United States/epidemiology , COVID-19/epidemiology , Ethnicity , SARS-CoV-2 , Longitudinal Studies , Minority GroupsABSTRACT
The objective of this study was to understand how pain patients and health care providers (HCPs) are engaging on Twitter and what insights this engagement might provide. By identifying how information is spread by and between these audiences, organizations such as patient advocacy groups may be better poised to develop and share materials that facilitate online communication between HCPs and pain patients, with an end goal of improving a shared decision-making process around pain management. We analyzed the Twitter audiences most engaged on pain topics by conducting a Social Network Analysis (SNA) of a large network of connected users on Twitter. The analysis segmented users based on the sources they cited and measured their influence based on who follows them. As a point of comparison, we also conducted an SNA of Twitter audiences most engaged on oncology topics. Oncology was chosen as a comparison due to what was perceived to be a highly developed online network of both patients and physicians. The populations included in this research included 12,086 accounts that were highly engaged on pain-related topics, and 12,617 accounts that were highly engaged on oncology-related topics. Network statistics were generated for variables including: word use, sources cited, retweets, and mentions. We also statistically analyzed the Twitter follow relationships among select HCPs and patient groups within each SNA. The creation of separate pain and oncology SNAs allowed the team to compare relationships and engagement related to these topics. We found that on Twitter, pain patients and providers appear to interact less than oncology patients and providers. Pain patients do not appear to follow medical professionals or share medical or health-related information on Twitter to the same extent as oncology patients. In addition, we found that pain patients do not communicate on Twitter in the same language as HCPs. Our results are important because they underscore that challenges in communication are not just problematic in face-to-face interactions, but also in digital social network (Twitter) interactions, serving as an additional roadblock to what can be shared decision-making opportunities around pain management. Contributing to this roadblock is access to quality information and a potential need for an online, evidence-based resource hub that could benefit the pain patient community in the same way that cancer.gov serves as a source of aggregated materials for oncology patients and HCPs. This study is an illustration of how social media networks like Twitter can be used to better understand the relationships, language gaps, and shared resources between pain patients and providers and offers a template for using digital social network (Twitter) interactions to research other difficult-to-treat or rare disease states.