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Polls asking respondents about their beliefs in conspiracy theories have become increasingly commonplace. However, researchers have expressed concern about the willingness of respondents to divulge beliefs in conspiracy theories due to the stigmatization of those ideas. We use an experimental design similar to a list experiment to decipher the effect of social desirability bias on survey responses to eight conspiratorial statements. Our study includes 8290 respondents across seven countries, allowing for the examination of social desirability bias across various political and cultural contexts. While the proportion of individuals expressing belief in each statement varies across countries, we observe identical treatment effects: respondents systematically underreport conspiracy beliefs. These findings suggest that conspiracy beliefs may be more prominent than current estimates suggest.
The emphasis on team science in clinical and translational research increases the importance of collaborative biostatisticians (CBs) in healthcare. Adequate training and development of CBs ensure appropriate conduct of robust and meaningful research and, therefore, should be considered as a high-priority focus for biostatistics groups. Comprehensive training enhances clinical and translational research by facilitating more productive and efficient collaborations. While many graduate programs in Biostatistics and Epidemiology include training in research collaboration, it is often limited in scope and duration. Therefore, additional training is often required once a CB is hired into a full-time position. This article presents a comprehensive CB training strategy that can be adapted to any collaborative biostatistics group. This strategy follows a roadmap of the biostatistics collaboration process, which is also presented. A TIE approach (Teach the necessary skills, monitor the Implementation of these skills, and Evaluate the proficiency of these skills) was developed to support the adoption of key principles. The training strategy also incorporates a “train the trainer” approach to enable CBs who have successfully completed training to train new staff or faculty.
While research on conspiracy theories and those who believe them has recently undergone a renaissance, there still exists a great deal of uncertainty about the measurement of conspiratorial beliefs and orientations, and the consequences of a conspiratorial mindset for expressly political attitudes and behaviors. We first demonstrate, using data from the 2012 American National Election Study, that beliefs in a variety of specific conspiracy theories are simultaneously, but differentially, the product of both a general tendency toward conspiratorial thinking and left/right political orientations. Next, we employ unique data including a general measure of conspiratorial thinking to explore the predictors of specific conspiracy beliefs. We find that partisan and ideological self-identifications are more important than any other variable in predicting ‘birther’ beliefs, while conspiratorial thinking is most important in predicting conspiracy beliefs about the assassination of John F. Kennedy and the 9/11 terrorist attacks.
The correlation between ideology and partisanship in the mass public has increased in recent decades amid a climate of persistent and growing elite polarization. Given that core values shape subsequent political predispositions, as well as the demonstrated asymmetry of elite polarization, this article hypothesizes that egalitarianism and moral traditionalism moderate the relationship between ideology and partisanship in that the latter relationship will have increased over time only among individuals who maintain conservative value orientations. An analysis of pooled American National Election Studies surveys from 1988 to 2012 supports this hypothesis. The results enhance scholarly understanding of the role of core values in shaping mass belief systems and testify to the asymmetric nature and mass public reception of elite cues among liberals and conservatives.
It is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from ‘fundamental’ (necessary for all) to ‘specialized’ (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized.
We surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by ‘fundamental’ and ‘specialized.’
There were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one’s own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%).
We have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature.