Health Cognitions and Perceptions related to COVID-19: 1-year follow up
Creators: name: Mielicki, Marta
name: Sidney, Pooja Gupta
name: Scheibe, Daniel A.
name: Schiller, Lauren
name: Taber, Jennifer M.
name: Coifman, Karin
name: Fitzsimmons, Charles
name: Waters, Erika A.
name: Matthews, Percival G
name: Thompson, Clarissa A.
Publisher: name: Open Science Framework
Year: 2021
Subjects: subject: Social and Behavioral Sciences
subject: Developmental Psychology
subject: Education
subject: Adult and Continuing Education
subject: Health Psychology
subject: Cognitive Psychology
subject: Psychology
subject: FOS: Psychology

description: In March-April 2020, we collected baseline and daily diary data from a cohort of nearly 1,300 adults who were recruited by Qualtrics. Now, one year later, we will recontact these participants to assess their health-related math problem-solving, confidence, strategy reports and math anxiety. We will also assess the extent to which they consider themselves to be liberal vs. conservative and their cultural worldview. These latter two constructs were included at this follow-up because our funders (IES, U.S. Department of Education) requested that these variables, which may influence beliefs about COVID-19 be included as moderators of experimental condition on risk perceptions. We have uploaded the full survey, which we estimate will take participants approximately 20 minutes to complete. Research Questions and Data Analyses 1. How are responses on the follow-up survey associated with responses on the baseline and daily diary? a. To test this, we will explore correlations among all study variables and variables across time points. Specifically, we anticipate that math anxiety at follow-up will be positively associated with math anxiety from the baseline. Additionally, we will look at differences in math anxiety based on health-related math problem solving accuracy at baseline and follow-up. 2. Is there a lasting effect of the intervention on health-related math problem solving? a. To test this, we will conduct a logistic regression on the outcome of health-related math problem-solving accuracy (for the vaccine question) in which we enter baseline condition (intervention vs. control) as well as gender, math anxiety, PAE, baseline problem-solving accuracy as covariates. We do not anticipate that the intervention will have sustained effects over one year, given the brief nature of the intervention, but we believe it is important to examine whether condition does account for unique variance in follow-up health-related math problem-solving accuracy and/or strategy reports. b. It is important to note that this analysis hinges on whether there is a sufficient number of participants across the two experimental groups who decide to complete the follow-up survey and that the groups are approximately equal on baseline math skills. We will re-test whether groups are approximately equal on math skills (e.g., PAE, math anxiety, and pretest problem accuracy). Doing so will allow us to assess whether those who had higher overall math skills were the ones who decided to complete our 1-year follow-up survey. 3. What proportion of people make a whole number bias error when asked to compare the size of two fractions that included numerators and denominators which are the same as the COVID-19 and flu rates that were included in the intervention from one year ago? Are those who were accurate on the problem more confident than those who were not accurate? 4. Are follow-up item-level metacognitive judgments higher on each of the math items for those in the intervention vs. control condition (if indeed condition differences are found)? That is, do findings from Scheibe et al. (in preparation) replicate? a. To test this, we will run regressions as described above, but the outcome variables will be whether they believe they got the problem correct or not (logistic) as well as item-level metacognitive (confidence judgments linear). We will also account for baseline item-level metacognitive judgments (from pretest) and problem-solving accuracy on the follow-up health-related math problem of interest. b. We hypothesize that confidence will be higher for those who answered the math problem correctly relative to those who answered incorrectly. c. We will also explore whether participants’ confidence is calibrated with their performance by scoring the Yes/No confidence scale as 1 for yes and 0 for no and then taking the absolute difference (calibration) and raw difference (bias) between problem solving performance (0 = incorrect and 1 = correct). 5. Can adults identify the correct expanded notation of a number like 33.88 million? The our world in data website uses this notation to indicate the number of people who have been vaccinated across countries. a. We will explore which math variables as measured at baseline and follow-up data collections account for unique variance in accuracy on this problem. 6. Did math anxiety increase, decrease, or stay the same over a year’s time? We will compare anxiety in an ANCOVA with time-point (baseline vs. follow-up) and experimental condition (if indeed there is a condition difference in problem-solving accuracy at follow-up) as independent variables and gender as a covariate.