Political ideology predicted differences in responses to COVID-19 over time (part 1 of 3)
Today’s blog is Part 1 of a 3-part series explaining some of the background and results for a paper recently accepted in the journal Intelligence. In it, we examine ability-based polarization in COVID-19 and in non-COVID topics.
Shoots-Reinhard, B., Goodwin, R., Bjälkebring, P., Markowitz, D. M., Silverstein, M. C., & Peters, E. (2021). Ability-related political polarization in the COVID-19 pandemic. Intelligence, 88, 101580. doi: https://doi.org/10.1016/j.intell.2021.101580
You can download the paper for free before October 9, 2021 by using this link
In the UO-EPIDeMIC study (our longitudinal examination of COVID-19 reactions), we found that people’s personal risk perceptions and emotions appeared to track together over the year 2020—when emotions were the most negative, people thought they were more likely to get COVID-19 and were also more likely to look at statistics daily.
In addition to tracking responses over time, we also examined the role of political ideology on people’s reactions over time. As shown below, conservatives and liberals initially (February 17-25, 2020) did not differ much in terms of negative emotions. Negative emotions then increased over time for both groups, and an ideological difference also emerged and persisted. Conservatives reported lower negative emotions than liberals.
We asked participants to indicate “How does the coronavirus make you feel?” on a scale from 1 = “does not apply/describe” to 4 = “completely describes” for afraid, worried, and upset.
Similarly, people’s risk perceptions showed political polarization starting in March 2020—people identifying as liberal (vs. conservative) perceived the coronavirus as riskier over time.
Participants answered six questions about their risk perceptions to COVID-19. Risk perceptions are coded so that 1 is the minimum risk perception (e.g., “no risk”) and 6 is the maximum risk perception (e.g., “extreme risk”)
This research was supported by grants from the National Science Foundation (SES-20010000 and SES-2017651). Portions of these data will be published in the journal Intelligence (https://doi.org/10.1016/j.intell.2021.101580). You can download the paper for free before October 9, 2021 by using this link.