RESUMO
Researchers strive to design and implement high-quality surveys to maximize the utility of the data collected. The definitions of quality and usefulness, however, vary from survey to survey and depend on the analytic needs. Survey teams must evaluate the trade-offs of various decisions, such as when results are needed and their required level of precision, in addition to practical constraints like budget, before finalizing the design. Characteristics within the concept of fit for purpose (FfP) can provide the framework for considering the trade-offs. Furthermore, this tool can enable an evaluation of quality for the resulting estimates. Implementation of a FfP framework in this context, however, is not straightforward. In this article, we provide the reader with a glimpse of a FfP framework in action for obtaining estimates on early season influenza vaccination coverage estimates and on knowledge, attitudes, behaviors, and barriers related to influenza and influenza prevention among civilian noninstitutionalized adults aged 18 years and older in the United States. The result is the National Internet Flu Survey (NIFS), an annual, two-week internet survey sponsored by the US Centers for Disease Control and Prevention. In addition to critical design decisions, we use the established NIFS FfP framework to discuss the quality of the NIFS in meeting the intended objectives. We highlight aspects that work well and other survey traits requiring further evaluation. Differences found in comparing the NIFS to the National Flu Survey, the National Health Interview Survey, and Behavioral Risk Factor Surveillance System are discussed via their respective FfP characteristics. The findings presented here highlight the importance of the FfP framework for designing surveys, defining data quality, and providing a set a metrics used to advertise the intended use of the survey data and results.
RESUMO
When the novel coronavirus entered the US, most US states implemented lockdown measures. In April-May 2020, state governments started political discussions about whether it would be worth the risk to reduce protective measures. In a highly politicized environment, risk perceptions and preferences for risk mitigation may vary by political inclinations. In April-May 2020, we surveyed a nationally representative sample of 5517 members of the University of Southern California's Understanding America Study. Of those, 37% identified as Democrats, 32% as Republican, and 31% as Third Party/Independent. Overall, Democrats perceived more risk associated with COVID-19 than Republicans, including for getting infected, being hospitalized and dying if infected, as well as running out of money as a result of the pandemic. Democrats were also more likely than Republicans to express concerns that states would lift economic restrictions too quickly, and to report mask use and social distancing. Generally, participants who identified as Third Party/Independent fell in between. Democrats were more likely to report watching MSNBC or CNN (vs. not), while Republicans were more likely to report watching Fox News (vs. not), and Third Party/Independents tended to watch neither. However, political inclinations predicted reported policy preferences, mask use, and social distancing, in analyses that accounted for differences in use of media sources, risk perceptions, and demographic background. In these analyses, participants' reported media use added to the partisan divide in preferences for the timing of lifting economic restrictions and reported protective behaviors. Implications for risk communication are discussed. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s11166-020-09336-3) contains supplementary material, which is available to authorized users.