Predictors of COVID-19 vaccine uptake: an online three-wave survey study of US adults.

BACKGROUND: To effectively promote vaccine uptake, it is important to understand which people are most and least inclined to be vaccinated and why. In this study, we examined predictors of COVID-19 vaccine uptake and reasons for non-vaccination. METHODS: We conducted an online English-language survey study in December-2020, January-2021, and March-2021. A total of 930 US respondents completed all surveys. Multiple logistic regression models were run to test whether the early vaccine eligibility, demographic factors, and psychological factors predict getting at least one dose of a COVID-19 vaccination in January-2021 and in March-2021. RESULTS: The proportion of respondents who received ≥ 1-dose of a COVID-19 vaccine increased from 18% (January) to 67% (March). Older age predicted vaccine uptake in January (OR = 2.02[95%CI = 1.14-3.78], p < .001) and March (10.92[6.76-18.05], p < .001). In January, additional predictors were higher numeracy (1.48[1.20-1.86], p < .001), COVID-19 risk perceptions (1.35[1.03-1.78], p = .029), and believing it is important adults get the COVID-19 vaccine (1.66[1.05-2.66], p = .033). In March, additional predictors of uptake were believing it is important adults get the COVID-19 vaccine (1.63[1.15-2.34], p = .006), prior COVID-19 vaccine intentions (1.37[1.10-1.72], p = .006), and belief in science (0.84[0.72-0.99], p = .041). Concerns about side effects and the development process were the most common reasons for non-vaccination. Unvaccinated respondents with no interest in getting a COVID-19 vaccine were younger (0.27[0.09-0.77], p = .016), held negative views about COVID-19 vaccines for adults (0.15[0.08-0.26], p < .001), had lower trust in healthcare (0.59[0.36-0.95], p = .032), and preferred to watch and wait in clinically ambiguous medical situations (0.66[0.48-0.89], p = .007). CONCLUSIONS: Evidence that attitudes and intentions towards COVID-19 vaccines were important predictors of uptake provides validation for studies using these measures and reinforces the need to develop strategies for addressing safety and development concerns which remain at the forefront of vaccine hesitancy.

Veterans and Nonveterans Coping With Stress During 4 Months of COVID-19.

PURPOSE: Identifying how people have been coping with stress during the COVID-19 pandemic allows us to anticipate how the population may react to similar stressors over time. In this study, we assessed patterns of coping styles among veterans and nonveterans, and stability and change in these strategies at 3 time points during the pandemic. METHODS: Using an online survey platform, we circulated a questionnaire at 3 time points during the period when COVID-19 vaccines became widely available (December 2-27, 2020; January 21-February 6, 2021; and March 8-23, 2021). The questionnaire asked participants about their extent of use of 11 coping strategies, and symptoms of anxiety and depression. RESULTS: A total of 2,085 participants (50.8% veterans) completed the questionnaire at 1 or more time points and 930 participants (62.8% veterans) completed it at all 3 time points. Cluster analysis identified 3 distinct coping styles: adaptive, distressed, and disengaged. Compared with nonveterans, veterans more commonly had adaptive and disengaged coping styles, and less commonly had a distressed coping style. The majority of the cohort (71.3%) changed coping style at least once during the study period. Participants who used the same coping style across all 3 time points reported lower levels of anxiety and depression. CONCLUSIONS: Our data demonstrate a need to better understand the dynamic nature of coping with pandemic-level stressors across time. We did not find patterns of change in coping styles, but our findings point to potential advantages of stability in coping style. It is possible that less adaptive styles that are more stable may be advantageous for mental health. This research has implications for supporting patients dealing with stress in family medicine.

Telehealth Use During the COVID-19 Pandemic Among Veterans and Nonveterans: Web-Based Survey Study.

BACKGROUND: In the first year of the COVID-19 pandemic, studies reported delays in health care usage due to safety concerns. Delays in care may result in increased morbidity and mortality from otherwise treatable conditions. Telehealth provides a safe alternative for patients to receive care when other circumstances make in-person care unavailable or unsafe, but information on patient experiences is limited. Understanding which people are more or less likely to use telehealth and their experiences can help tailor outreach efforts to maximize the impact of telehealth. OBJECTIVE: This study aims to examine the characteristics of telehealth users and nonusers and their reported experiences among veteran and nonveteran respondents. METHODS: A nationwide web-based survey of current behaviors and health care experiences was conducted in December 2020-March 2021. The survey consisted of 3 waves, and the first wave is assessed here. Respondents included US adults participating in Qualtrics web-based panels. Primary outcomes were self-reported telehealth use and number of telehealth visits. The analysis used a 2-part regression model examining the association between telehealth use and the number of visits with respondent characteristics. RESULTS: There were 2085 participants in the first wave, and 898 (43.1%) reported using telehealth since the pandemic began. Most veterans who used telehealth reported much or somewhat preferring an in-person visit (336/474, 70.9%), while slightly less than half of nonveterans (189/424, 44.6%) reported this preference. While there was no significant difference between veteran and nonveteran likelihood of using telehealth (odds ratio [OR] 1.33, 95% CI 0.97-1.82), veterans were likely to have more visits when they did use it (incidence rate ratio [IRR] 1.49, 95% CI 1.07-2.07). Individuals were less likely to use telehealth and reported fewer visits if they were 55 years and older (OR 0.39, 95% CI 0.25-0.62 for ages 55-64 years; IRR 0.43, 95% CI 0.28-0.66) or lived in a small city (OR 0.63, 95% CI 0.43-0.92; IRR 0.71, 95% CI 0.51-0.99). Receiving health care partly or primarily at the Veterans Health Administration (VA) was associated with telehealth use (primarily VA: OR 3.25, 95% CI 2.20-4.81; equal mix: OR 2.18, 95% CI 1.40-3.39) and more telehealth visits (primarily VA: IRR 1.5, 95% CI 1.10-2.04; equal mix: IRR 1.57, 95% CI 1.11-2.24). CONCLUSIONS: Telehealth will likely continue to be an important source of health care for patients, especially following situations like the COVID-19 pandemic. Some groups who may benefit from telehealth are still underserved. Telehealth services and outreach should be improved to provide accessible care for all.

Demographic, structural, and psychological predictors of risk-increasing and mask wearing behaviors among US adults between December 2020-March 2021.

OBJECTIVES: To assess demographic, structural, and psychological predictors of risk-increasing and risk-decreasing behaviors METHODS: This study used data from an online longitudinal, three-wave COVID-19 survey (12/20-03/21) regarding the behaviors, attitudes, and experiences of US Veteran (n = 584) and non-Veteran (n = 346) adults. RESULTS: Inability to get groceries delivered emerged as the strongest predictor of more frequent risk-increasing behavior across all timepoints. Other consistent predictors of more frequent risk-increasing behavior and less frequent mask wearing included less worry about getting COVID-19, disbelief in science, belief in COVID-19 conspiracies, and negative perceptions of the state response. No demographic factor consistently predicted risk-increasing behavior or mask wearing, though different demographic predictors emerged for more frequent risk-increasing behaviors (e.g., lower health literacy) and mask-wearing (e.g., older age and urban residence) at certain timepoints. The most frequently endorsed reasons for having contact with others concerned health-related (food, medical care, and exercise) and social needs (seeing friends/family and boredom). CONCLUSIONS: These findings highlight key individual-level determinants of risk-increasing behaviors and mask wearing which encompass demographic, structural, and psychological factors. PRACTICE IMPLICATIONS: Findings can support public health experts and health communicators promote engagement with risk-reducing behaviors and address key barriers to engaging in these behaviors.

Parental Nonadherence to Health Policy Recommendations for Prevention of COVID-19 Transmission Among Children.

This survey study assesses whether parents had ever engaged in specific misrepresentation and nonadherence behaviors regarding public health measures for preventing COVID-19 transmission among children.

Misrepresentation and Nonadherence Regarding COVID-19 Public Health Measures.

Importance: The effectiveness of public health measures implemented to mitigate the spread and impact of SARS-CoV-2 relies heavily on honesty and adherence from the general public. Objective: To examine the frequency of, reasons for, and factors associated with misrepresentation and nonadherence regarding COVID-19 public health measures. Design, Setting, and Participants: This survey study recruited a national, nonprobability sample of US adults to participate in an online survey using Qualtrics online panels (participation rate, 1811 of 2260 [80.1%]) from December 8 to 23, 2021. The survey contained screening questions to allow for a targeted sample of one-third who had had COVID-19, one-third who had not had COVID-19 and were vaccinated, and one-third who had not had COVID-19 and were unvaccinated. Main Outcomes and Measures: The survey assessed 9 different types of misrepresentation and nonadherence related to COVID-19 public health measures and the reasons underlying such behaviors. Additional questions measured COVID-19-related beliefs and behaviors and demographic characteristics. Results: The final sample included 1733 participants. The mean (SD) participant age was 41 (15) years and the sample predominantly identified as female (1143 of 1732 [66.0%]) and non-Hispanic White (1151 of 1733 [66.4%]). Seven hundred twenty-one participants (41.6%) reported misrepresentation and/or nonadherence in at least 1 of the 9 items; telling someone they were with or about to be with in person that they were taking more COVID-19 preventive measures than they actually were (420 of 1726 [24.3%]) and breaking quarantine rules (190 of 845 [22.5%]) were the most common manifestations. The most commonly endorsed reasons included wanting life to feel normal and wanting to exercise personal freedom. All age groups younger than 60 years (eg, odds ratio for those aged 18-29 years, 4.87 [95% CI, 3.27-7.34]) and those who had greater distrust in science (odds ratio, 1.14 [95% CI, 1.05-1.23]) had significantly higher odds of misrepresentation and/or nonadherence for at least 1 of the 9 items. Conclusions and Relevance: In this survey study of US adults, nearly half of participants reported misrepresentation and/or nonadherence regarding public health measures against COVID-19. Future work is needed to examine strategies for communicating the consequences of misrepresentation and nonadherence and to address contributing factors.

Incidence Rate and Risk Factors Associated with Travelers' Diarrhea in International Travelers Departing from Utah, USA.

Despite knowledge on the causes and prevention strategies for travelers' diarrhea (TD), it continues to be one of the most common illnesses experienced by U.S. international travelers. However, studies of risk factors associated with TD among U.S. travelers are limited. In this study, we aimed to determine the incidence rate of TD, the proportion of travelers who experience TD, and to identify risk factors associated with TD. In this cross-sectional study, we collected and analyzed data from anonymous posttravel questionnaires submitted by international travelers recruited during their pretravel visit at two travel clinics in Salt Lake City, Utah, from October 2016 to March 2020. Of 571 travelers who completed posttravel surveys, 484 (85%) answered the TD question, of which 111 (23%) reported TD, for an incidence rate of 1.1 episodes per 100 travel-days (95% confidence interval [CI]: 0.9-1.4). In a multivariable model, visiting Southeast Asian (odds ratio [OR]: 2.60; 95% CI: 1.45-4.72) and African (OR: 2.06; 95% CI: 1.09-3.93]) WHO regions, having 10 or more individuals in the group (OR: 3.91; 95% CI: 1.50-11.32]), longer trip duration (OR: 1.01; 95% CI: 1.00-1.02), visiting both urban and rural destinations (OR: 1.94; 95% CI: 1.01-3.90), and taking medications/supplements to prevent TD (OR: 2.74; 95% CI: 1.69-4.47) were statistically significantly associated with increased odds of reporting TD. TD continues to be common in international travelers from the United States. Our findings provide insights regarding travelers' behaviors regarding TD in international travelers from high-income countries and shows the need for additional research into prevention strategies for travelers' diarrhea.

Communicating about COVID-19 vaccine development and safety.

PURPOSE: Beliefs that the risks from a COVID-19 vaccine outweigh the risks from getting COVID-19 and concerns that the vaccine development process was rushed and lacking rigor have been identified as important drivers of hesitancy and refusal to get a COVID-19 vaccine. We tested whether messages designed to address these beliefs and concerns might promote intentions to get a COVID-19 vaccine. METHOD: We conducted an online survey fielded between March 8-23, 2021 with US Veteran (n = 688) and non-Veteran (n = 387) respondents. In a between-subjects experiment, respondents were randomly assigned to a control group (with no message) or to read one of two intervention messages: 1. a fact-box styled message comparing the risks of getting COVID-19 compared to the vaccine, and 2. a timeline styled message describing the development process of the COVID-19 mRNA vaccines. RESULTS: Most respondents (60%) wanted a COVID-19 vaccine. However, 17% expressed hesitancy and 23% did not want to get a COVID-19 vaccine. The fact-box styled message and the timeline message did not significantly improve vaccination intentions, F(2,358) = 0.86, p = .425, [Formula: see text] = .005, or reduce the time respondents wanted to wait before getting vaccinated, F(2,306) = 0.79, p = .453, [Formula: see text] = .005, compared to no messages. DISCUSSION: In this experimental study, we did not find that providing messages about vaccine risks and the development process had an impact on respondents' vaccine intentions. Further research is needed to identify how to effectively address concerns about the risks associated with COVID-19 vaccines and the development process and to understand additional factors that influence vaccine intentions.

Validation of the SHEA/IDSA severity criteria to predict poor outcomes among inpatients and outpatients with Clostridioides difficile infection.

OBJECTIVE: To determine whether the Society for Healthcare Epidemiology of America (SHEA) and the Infectious Diseases Society of America (IDSA) Clostridioides difficile infection (CDI) severity criteria adequately predicts poor outcomes. DESIGN: Retrospective validation study. SETTING AND PARTICIPANTS: Patients with CDI in the Veterans' Affairs Health System from January 1, 2006, to December 31, 2016. METHODS: For the 2010 criteria, patients with leukocytosis or a serum creatinine (SCr) value ≥1.5 times the baseline were classified as severe. For the 2018 criteria, patients with leukocytosis or a SCr value ≥1.5 mg/dL were classified as severe. Poor outcomes were defined as hospital or intensive care admission within 7 days of diagnosis, colectomy within 14 days, or 30-day all-cause mortality; they were modeled as a function of the 2010 and 2018 criteria separately using logistic regression. RESULTS: We analyzed data from 86,112 episodes of CDI. Severity was unclassifiable in a large proportion of episodes diagnosed in subacute care (2010, 58.8%; 2018, 49.2%). Sensitivity ranged from 0.48 for subacute care using 2010 criteria to 0.73 for acute care using 2018 criteria. Areas under the curve were poor and similar (0.60 for subacute care and 0.57 for acute care) for both versions, but negative predictive values were >0.80. CONCLUSIONS: Model performances across care settings and criteria versions were generally poor but had reasonably high negative predictive value. Many patients in the subacute-care setting, an increasing fraction of CDI cases, could not be classified. More work is needed to develop criteria to identify patients at risk of poor outcomes.