Lessons Learned From Interdisciplinary Efforts to Combat COVID-19 Misinformation: Development of Agile Integrative Methods From Behavioral Science, Data Science, and Implementation Science.

Background: Despite increasing awareness about and advances in addressing social media misinformation, the free flow of false COVID-19 information has continued, affecting individuals' preventive behaviors, including masking, testing, and vaccine uptake. Objective: In this paper, we describe our multidisciplinary efforts with a specific focus on methods to (1) gather community needs, (2) develop interventions, and (3) conduct large-scale agile and rapid community assessments to examine and combat COVID-19 misinformation. Methods: We used the Intervention Mapping framework to perform community needs assessment and develop theory-informed interventions. To supplement these rapid and responsive efforts through large-scale online social listening, we developed a novel methodological framework, comprising qualitative inquiry, computational methods, and quantitative network models to analyze publicly available social media data sets to model content-specific misinformation dynamics and guide content tailoring efforts. As part of community needs assessment, we conducted 11 semistructured interviews, 4 listening sessions, and 3 focus groups with community scientists. Further, we used our data repository with 416,927 COVID-19 social media posts to gather information diffusion patterns through digital channels. Results: Our results from community needs assessment revealed the complex intertwining of personal, cultural, and social influences of misinformation on individual behaviors and engagement. Our social media interventions resulted in limited community engagement and indicated the need for consumer advocacy and influencer recruitment. The linking of theoretical constructs underlying health behaviors to COVID-19-related social media interactions through semantic and syntactic features using our computational models has revealed frequent interaction typologies in factual and misleading COVID-19 posts and indicated significant differences in network metrics such as degree. The performance of our deep learning classifiers was reasonable, with an F-measure of 0.80 for speech acts and 0.81 for behavior constructs. Conclusions: Our study highlights the strengths of community-based field studies and emphasizes the utility of large-scale social media data sets in enabling rapid intervention tailoring to adapt grassroots community interventions to thwart misinformation seeding and spread among minority communities. Implications for consumer advocacy, data governance, and industry incentives are discussed for the sustainable role of social media solutions in public health.

Using cognitive interviews to improve a measure of organizational readiness for implementation.

BACKGROUND: Organizational readiness is a key factor for successful implementation of evidence-based interventions (EBIs), but a valid and reliable measure to assess readiness across contexts and settings is needed. The R = MC2 heuristic posits that organizational readiness stems from an organization's motivation, capacity to implement a specific innovation, and its general capacity. This paper describes a process used to examine the face and content validity of items in a readiness survey developed to assess organizational readiness (based on R = MC2) among federally qualified health centers (FQHC) implementing colorectal cancer screening (CRCS) EBIs. METHODS: We conducted 20 cognitive interviews with FQHC staff (clinical and non-clinical) in South Carolina and Texas. Participants were provided a subset of items from the readiness survey to review. A semi-structured interview guide was developed to elicit feedback from participants using "think aloud" and probing techniques. Participants were recruited using a purposive sampling approach and interviews were conducted virtually using Zoom and WebEx. Participants were asked 1) about the relevancy of items, 2) how they interpreted the meaning of items or specific terms, 3) to identify items that were difficult to understand, and 4) how items could be improved. Interviews were transcribed verbatim and coded in ATLAS.ti. Findings were used to revise the readiness survey. RESULTS: Key recommendations included reducing the survey length and removing redundant or difficult to understand items. Additionally, participants recommended using consistent terms throughout (e.g., other units/teams vs. departments) the survey and changing pronouns (e.g., people, we) to be more specific (e.g., leadership, staff). Moreover, participants recommended specifying ambiguous terms (e.g., define what "better" means). CONCLUSION: Use of cognitive interviews allowed for an engaged process to refine an existing measure of readiness. The improved and finalized readiness survey can be used to support and improve implementation of CRCS EBIs in the clinic setting and thus reduce the cancer burden and cancer-related health disparities.

A Novel Bayesian Spatial-Temporal Approach to Quantify SARS-CoV-2 Testing Disparities for Small Area Estimation.

Objectives. To propose a novel Bayesian spatial-temporal approach to identify and quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing disparities for small area estimation. Methods. In step 1, we used a Bayesian inseparable space-time model framework to estimate the testing positivity rate (TPR) at geographically granular areas of the census block groups (CBGs). In step 2, we adopted a rank-based approach to compare the estimated TPR and the testing rate to identify areas with testing deficiency and quantify the number of needed tests. We used weekly SARS-CoV-2 infection and testing surveillance data from Cameron County, Texas, between March 2020 and February 2022 to demonstrate the usefulness of our proposed approach. Results. We identified the CBGs that had experienced substantial testing deficiency, quantified the number of tests that should have been conducted in these areas, and evaluated the short- and long-term testing disparities. Conclusions. Our proposed analytical framework offers policymakers and public health practitioners a tool for understanding SARS-CoV-2 testing disparities in geographically small communities. It could also aid COVID-19 response planning and inform intervention programs to improve goal setting and strategy implementation in SARS-CoV-2 testing uptake. (Am J Public Health. 2023;113(1):40-48. https://doi.org/10.2105/AJPH.2022.307127).

Census Tract Patterns and Contextual Social Determinants of Health Associated With COVID-19 in a Hispanic Population From South Texas: A Spatiotemporal Perspective.

BACKGROUND: Previous studies have shown that various social determinants of health (SDOH) may have contributed to the disparities in COVID-19 incidence and mortality among minorities and underserved populations at the county or zip code level. OBJECTIVE: This analysis was carried out at a granular spatial resolution of census tracts to explore the spatial patterns and contextual SDOH associated with COVID-19 incidence from a Hispanic population mostly consisting of a Mexican American population living in Cameron County, Texas on the border of the United States and Mexico. We performed age-stratified analysis to identify different contributing SDOH and quantify their effects by age groups. METHODS: We included all reported COVID-19-positive cases confirmed by reverse transcription-polymerase chain reaction testing between March 18 (first case reported) and December 16, 2020, in Cameron County, Texas. Confirmed COVID-19 cases were aggregated to weekly counts by census tracts. We adopted a Bayesian spatiotemporal negative binomial model to investigate the COVID-19 incidence rate in relation to census tract demographics and SDOH obtained from the American Community Survey. Moreover, we investigated the impact of local mitigation policy on COVID-19 by creating the binary variable "shelter-in-place." The analysis was performed on all COVID-19-confirmed cases and age-stratified subgroups. RESULTS: Our analysis revealed that the relative incidence risk (RR) of COVID-19 was higher among census tracts with a higher percentage of single-parent households (RR=1.016, 95% posterior credible intervals [CIs] 1.005, 1.027) and a higher percentage of the population with limited English proficiency (RR=1.015, 95% CI 1.003, 1.028). Lower RR was associated with lower income (RR=0.972, 95% CI 0.953, 0.993) and the percentage of the population younger than 18 years (RR=0.976, 95% CI 0.959, 0.993). The most significant association was related to the "shelter-in-place" variable, where the incidence risk of COVID-19 was reduced by over 50%, comparing the time periods when the policy was present versus absent (RR=0.506, 95% CI 0.454, 0.563). Moreover, age-stratified analyses identified different significant contributing factors and a varying magnitude of the "shelter-in-place" effect. CONCLUSIONS: In our study, SDOH including social environment and local emergency measures were identified in relation to COVID-19 incidence risk at the census tract level in a highly disadvantaged population with limited health care access and a high prevalence of chronic conditions. Results from our analysis provide key knowledge to design efficient testing strategies and assist local public health departments in COVID-19 control, mitigation, and implementation of vaccine strategies.

Correction: Census Tract Patterns and Contextual Social Determinants of Health Associated With COVID-19 in a Hispanic Population From South Texas: A Spatiotemporal Perspective.

[This corrects the article DOI: 10.2196/29205.].

Rationale and design of the Prevent Anal Cancer Self-Swab Study: a protocol for a randomised clinical trial of home-based self-collection of cells for anal cancer screening.

INTRODUCTION: Squamous cell carcinoma of the anus is a common cancer among sexual minority men, especially HIV-positive sexual minority men; however, there is no evidenced-based national screening protocol for detection of anal precancers. Our objective is to determine compliance with annual anal canal self-sampling or clinician-sampling for human papillomavirus (HPV) DNA. METHODS AND ANALYSIS: This is a prospective, randomised, two-arm clinical study to evaluate compliance with annual home-based versus clinic-based HPV DNA screening of anal canal exfoliated cells. The setting is primary care community-based clinics. Recruitment is ongoing for 400 HIV-positive and HIV-negative sexual minority men and transgender persons, aged >25 years, English or Spanish speaking, no current use of anticoagulants other than nonsteroidal anti-inflammatory drugs and no prior diagnosis of anal cancer. Participants are randomised to either receive a swab in the mail for home-based collection of an anal canal specimen at 0 and 12 months (arm 1) or attend a clinic for clinician collection of an anal canal specimen at 0 and 12 months (arm 2). Persons will receive clinic-based Digital Anal Rectal Examinations and high-resolution anoscopy-directed biopsy to assess precancerous lesions, stratified by study arm. Anal exfoliated cells collected in the study are assessed for high-risk HPV persistence and host/viral methylation. The primary analysis will use the intention-to-treat principle to compare the proportion of those who comply with 0-month and 12-month sampling in the home-based and clinic-based arms. The a priori hypothesis is that a majority of persons will comply with annual screening with increased compliance among persons in the home-based arm versus clinic-based arm. ETHICS AND DISSEMINATION: The study has been approved by the Medical College of Wisconsin Human Protections Committee. Results will be disseminated to communities where recruitment occurred and through peer-reviewed literature and conferences. TRIAL REGISTRATION NUMBER: NCT03489707.