1) Have any data been collected for this study already? No, no data have been collected for this study yet.
2) What's the main question being asked or hypothesis being tested in this study? We hypothesize that a heightened manipulated threat through the Coronavirus is associated with increased use of compensatory defense strategies as defined by Jonas and colleagues (2014). In detail, we hypothesize an indirect positive effect of higher perceived Corona-threat to ingroup bias, ingroup entitativity, system justification, and conspiracy beliefs over enhanced behavioral inhibition.
3) Describe the key dependent variable(s) specifying how they will be measured. All variables will be determined via questionnaires within a qualtrics survey.
BAS/BIS: The state level of behavioral inhibition will be assessed via the following 8 items: „afraid, scared, frightened, nervous, jittery, shaky, inhibited, worried “
The state level of behavioral activation will be assessed via the following 10 items: “active, alert, attentive, determined, enthusiastic, excited, inspired, interested, proud, strong”
Ingroup Bias: Ingroup bias will be assessed by assessing the warmth-, and competence-level participants perceive for citizens of their own nation (USA) as well as for the citizens of China. Warmth will be assessed via the extent to which participants assign 2 characteristics (“warm”, “good-natured”) to the two people. Competence will also be assessed via the extent to which participants assign 2 characteristics (“competent”, “intelligent”) to the two people. The mean score of the warmth and competence items for the citizens of China will then be subtracted from the mean score of the warmth and competence items for the citizens of the US to create an ingroup bias score (Fritsche, Jonas, & Ablasser, 2012).
Ingroup Entitativity: Entitativity of the ingroup will be assessed via the extent to which participants agree with two statements (“The citizens of the US share a common nature.”, “The citizens of the US share common goals and a common fate.”, Fritsche, Jonas, & Fankhänel, 2008).
System Justification: To assess participants’ level of system justification, we adopted the items of the System Justification Scale (Kay & Jost, 2003) to the current Corona crisis.
Conspiracy Beliefs: Participants’ level of conspiracy beliefs will be assessed by asking participants about the extent to which they belief in 2 conspiratorial hypotheses about the spread of COVID-19. In detail, the 2 hypotheses are:
“COVID-19 was developed as a biological weapon by the Chinese government. Due to a laboratory accident, it was spread among China's own population.”
“The Chinese government reports false numbers regarding the COVID-19 death cases as well as the cases of recovery: Compared to the official numbers, there are more people that died and less people that recovered from COVID-19 within China.”
4) How many and which conditions will participants be assigned to? Participants will be assigned to a low-, or a high-threat group. In the high-threat group, participants will be confronted with 8 corona facts taken from the World Health Organisation’s corona mythbusters. They will be asked a question regarding each of the facts making it evident that there is no cure to the threat imposed by COVID-19.
In the low-threat groups the same pictures as for the corona mythbusters will be paired with 8 facts unrelated to the coronavirus. These facts impose no threat. Participants will also be asked a question after presentation of each of the facts.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. Simple t-test analyses will be run to test the association between Corona-threat level and the dependent variables outlined above.
Mediation analyses via Hayes’ SPSS PROCESS macro will be performed. 5000 bootstrap samples will be created to establish a ninety-five percent bias corrected confidence interval for the expected indirect positive effect of Corona-threat level via behavioral inhibition on the outlined dependent variables.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. Participants who do not complete the survey and/or show a suspicious response pattern in the questionnaires by consistently ticking the same answer/Likert scale point will be excluded. Furthermore, an attention check (“Please ignore the question and only write down the word football into the box as the answer to the question”) is implemented in the survey. Participants who fail the attention check will also be excluded.
7) How many observations will be collected or what will determine sample size? No need to justify decision, but be precise about exactly how the number will be determined. The sample size was determined via a power analysis meant to establish the amount of participants needed to find the hypothesized mediation effect with a likelihood of 80%, setting alpha error probability to .05. The power analysis was conducted with Kenny’s (2017) MedPower application. We assumed an effect size of r = .15 for the association between perceived threat through the Coronavirus and behavioral inhibition, behavioral inhibition and the DVs, and perceived threat through the Coronavirus and the DVs when controlling for its indirect association with behavioral inhibition.
Given these effect sizes, a sample size of N = 453 would be required to detect the indirect association of perceived threat through the Coronavirus and the DVs over behavioral inhibition with a likelihood of 80%. We decided to recruit 500 participants to account for possible exclusions (as described above) and to compensate for drop-outs.
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) Nothing else to pre-register.
