Assessing the feasibility and sample quality of a national random-digit dialing cellular phone survey of young adults.

The majority of adults aged 18-34 years have only cellular phones, making random-digit dialing of landline telephones an obsolete methodology for surveillance of this population. However, 95% of this group has cellular phones. This article reports on the 2011 National Young Adult Health Survey (NYAHS), a pilot study conducted in the 50 US states and Washington, DC, that used random-digit dialing of cellular phones and benchmarked this methodology against that of the 2011 Behavioral Risk Factor Surveillance System (BRFSS). Comparisons of the demographic distributions of subjects in the NYAHS and BRFSS (aged 18-34 years) with US Census data revealed adequate reach for all demographic subgroups. After adjustment for design factors, the mean absolute deviations across demographic groups were 3 percentage points for the NYAHS and 2.8 percentage points for the BRFSS, nationally, and were comparable for each census region. Two-sided z tests comparing cigarette smoking prevalence revealed no significant differences between NYAHS and BRFSS participants overall or by subgroups. The design effects of the sampling weight were 2.09 for the NYAHS and 3.26 for the BRFSS. Response rates for the NYAHS and BRFSS cellular phone sampling frames were comparable. Our assessment of the NYAHS methodology found that random-digit dialing of cellular phones is a feasible methodology for surveillance of young adults.

Understanding the Impact of General Vaccine Attitudes on the Intent for Early COVID-19 Vaccination.

Despite relatively high rates of population spread, morbidity and mortality, the adoption of COVID-19 vaccines among the eligible populations was relatively slow. Some of the reasons for vaccination hesitancy and refusals have been attributed to unique aspects of this pandemic, including attitudes toward COVID-19 vaccines. However, little attention has been paid to the role of underlying vaccine beliefs in the likelihood of early vaccine adoption for COVID-19. This study provides a more comprehensive assessment of factors influencing willingness to get an early vaccination, and the relative contribution of general vaccine attitudes, compared to demographics, perceived threat and institutional trust. Monthly national surveys were conducted between June and November 2020 using a national consumer panel of U.S. adults (n = 6185). By late November, only 24% of respondents said they were very likely to get a Food and Drug Administration (FDA)-approved COVID-19 vaccine as soon as it became available. While COVID-19 risk perceptions, confidence and trust in key institutions and information sources, and some demographic variables, were predictive of early vaccination intent, general beliefs regarding vaccines played a significant role, even compared to demographics, perceived risk and institutional trust. This lesson from the COVID-19 experience could help inform public health communications in future epidemics.

Estimating Web Survey Mode and Panel Effects in a Nationwide Survey of Alcohol Use.

Random-digit dialing (RDD) telephone surveys are challenged by declining response rates and increasing costs. Many surveys that were traditionally conducted via telephone are seeking cost-effective alternatives, such as address-based sampling (ABS) with self-administered web or mail questionnaires. At a fraction of the cost of both telephone and ABS surveys, opt-in web panels are an attractive alternative. The 2019-2020 National Alcohol Survey (NAS) employed three methods: (1) an RDD telephone survey (traditional NAS method); (2) an ABS push-to-web survey; and (3) an opt-in web panel. The study reported here evaluated differences in the three data-collection methods, which we will refer to as "mode effects," on alcohol consumption and health topics. To evaluate mode effects, multivariate regression models were developed predicting these characteristics, and the presence of a mode effect on each outcome was determined by the significance of the three-level effect (RDD-telephone, ABS-web, opt-in web panel) in each model. Those results were then used to adjust for mode effects and produce a "telephone-equivalent" estimate for the ABS and panel data sources. The study found that ABS-web and RDD were similar for most estimates but exhibited differences for sensitive questions including getting drunk and experiencing depression. The opt-in web panel exhibited more differences between it and the other two survey modes. One notable example is the reporting of drinking alcohol at least 3-4 times per week, which was 21 percent for RDD-phone, 24 percent for ABS-web, and 34 percent for opt-in web panel. The regression model adjusts for mode effects, improving comparability with past surveys conducted by telephone; however, the models result in higher variance of the estimates. This method of adjusting for mode effects has broad applications to mode and sample transitions throughout the survey research industry.

Using the 5C model to understand COVID-19 vaccine hesitancy across a National and South Carolina sample.

Vaccine hesitancy is a serious threat to global health; however, significant COVID-19 vaccine hesitancy exists throughout the United States. The 5C model, which postulates five person-level determinants for vaccine hesitancy - confidence, complacency, constraints, risk calculation, and collective responsibility - provides one theoretical way of understanding COVID-19 vaccine hesitancy. The present study examined the effects of these 5C drivers of vaccine behavior on early vaccine adoption and vaccine intentions above and beyond theoretically salient demographic characteristics and compared these associations across a National sample (n = 1634) and a statewide sample from South Carolina (n = 784) - a state with documented low levels of COVID-19 vaccination uptake. This study used quantitative and qualitative data collected in October 2020 to January 2021 from the MFour-Mobile Research Panel, a large, representative non-probability sample of adult smartphone users. Overall, the South Carolina sample reported lower COVID-19 vaccine intentions and higher levels of 5C barriers to vaccine uptake compared to the National sample. Findings further indicated that both demographic characteristics (race) and certain drivers of vaccine behavior (confidence and collective responsibility) are associated with vaccine trust and intentions across samples above and beyond other variables. Qualitative data indicated that COVID-19 vaccine hesitancy was driven by fears about the quick vaccine development, limited research, and potential side effects. Although there are some limitations to the cross-sectional survey data, the present study offers valuable insight into factors associated with early COVID-19 vaccine hesitancy across the United States.

Better Understanding Adult COVID-19 Vaccination Hesitancy and Refusal: The Influence of Broader Beliefs about Vaccines.

Published surveys in the United States provide much evidence that COVID-19 vaccination is influenced by disease and vaccine-related risk perceptions. However, there has been little examination of whether individual's general beliefs about vaccines are also related to COVID-19 vaccination, especially among unvaccinated adults. This study used an August 2021 national survey of 1000 U.S. adults to examine whether general beliefs about vaccines were associated with COVID-19 vaccination status. In addition, it used multivariate analyses to assess the relative contribution of individual vaccine beliefs to current vaccine status independently of COVID-19-specific attitudes and experiences, and demographics. The findings indicated that, collectively, general vaccine beliefs mattered more than demographics, COVID-19-specific risk perceptions, confidence in government, or trust in public health agencies in COVID-19 vaccination status. Overall, the findings affirm the importance of vaccine education and communication efforts that help people understand why vaccines are needed, how vaccine safety is established and monitored, and how vaccines provide protection from infectious diseases. To achieve success among vaccine-hesitant individuals, communication strategies should target vaccine beliefs that most influence vaccination outcomes.

Physical measures and biomarker collection in health surveys: Propensity to participate.

Population-based surveys have long been a key tool for health researchers, policy makers and program managers. The addition of bio-measures, including physical measures and specimen collection, to self-reported health and health behaviors can increase the value of the research for health sciences. At the same time, these bio-measures are likely to increase the perceived burden and intrusiveness to the respondent. Relatively little research has been reported on respondent willingness to participate in surveys that involve physical measures and specimen collection and whether there is any associated non-response bias. This paper explores the willingness of respondents to participate in surveys that involve physical measures and biomarkers. A Census-balanced sample of nearly 2000 adults from a national mobile panel of persons residing in the U.S. were interviewed. Willingness to participate in six specific bio-measures was assessed. The survey finds a high correlation in the willingness of respondents to participate among these specific bio-measures. This suggests there is a general propensity towards (and against) bio-measures among potential respondents, despite some differences in willingness to participate in the more sensitive, intrusive or burdensome biomarkers. This study finds the general propensity to participate in bio-measures is correlated with a number of key measures of health and illness. This suggests that the inclusion of biomarkers in health surveys may introduce some bias in key measures that need to be balanced against the value of the additional information.