'ITE across Climate Beliefs using SASSY - June 2021' (AsPredicted #67,333)
Author(s) This pre-registration is currently anonymous to enable blind peer-review. It has 2 authors.
Pre-registered on 2021/05/31 20:29 (PT)
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? People rate repeated, more familiar claims as more true than claims they see for the first time, a phenomenon known as the illusory truth effect (ITE; meta-analysis: Dechene, Stahl, Hansen, & Wanke, 2010). While many studies have examined this phenomenon, to our knowledge there is a lack of studies testing the truth effect with controversial claims, though social psychology literatures have shown that underlying beliefs are an important factor in truth reasoning and judgment (e.g., Strickland, Taber, & Lodge, 2011; Oyserman, 2011). For instance, information that is inconsistent with one's own beliefs are processed with a disconfirmation bias, demonstrated through longer reading time and formation of more counterarguments (Taber et al., 2009; Erisen, Redlawsk, & Erisen, 2017).
We examine susceptibility to the truth effect in the context of belief consistency by using claims related to climate change. In particular, we use piloted claims supporting the beliefs of a climate scientist (scientist claims), supporting the belief of a climate science skeptic (skeptic claims), and neutral weather claims. Belief consistency is determined by measuring level of belief in climate science prior to participating in the ITE component of the study.
Our key research question is whether claims inconsistent with our own beliefs will be less susceptible to the effects of repetition. It is hypothesised that, relative to claims that are consistent with our own beliefs, claims inconsistent with our own beliefs will be related to a decreased truth effect, as well as a longer reaction time.
3) Describe the key dependent variable(s) specifying how they will be measured. The key dependent variable is mean truth ratings on a 6-point scale from Definitely True to Definitely False. We will also collect reaction time at test for each claim.
4) How many and which conditions will participants be assigned to? This is a 2 (claim familiarity: old or new) x 2 (claim type: skeptic or scientist) fully within-subjects design. We will use climate science endorsement as a continuous or categorical (between-subjects) variable in examining the variability in the ITE by claim and climate science beliefs/attitudes.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. We will analyse which factors influence truth ratings in a linear mixed model which considers the inputs of claim type, claim familiarity, participant, climate science endorsement, and interactions between these factors.
We will also analyse how reaction time is predicted by the above factors.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. We will exclude answers from people who have said yes to searching for answers online (for the test phase). We will also exclude submissions that fail the bot check, and submissions with identical answers in the testing phase (e.g. all true).
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. We will post 200 HITs on MTurk.
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) - We plan to use the Six Americas scale to represent the climate science endorsement factor in the main LMM analysis. Alternatively, we may use this scale in combination with the previous belief scales to represent climate science endorsement.
- We plan to run the main LMM while also including weather claims (our seemingly innocuous filler items).
- We will also include an exploratory measure of individual variation in chronic trust, and plan to run the LMM with chronic trust included.
- We may also consider an analysis considering upper and lower quartiles of the belief in climate science measure.
