Whereas actual attitudes represent peopleu2019s evaluations of specific objects as being good or bad, desired attitudes represent the attitude positions that people wish they held. In five datasets involving a variety of populations and procedural variations, this study explored how political and moral factors motivate people to form desired attitudes distinct from their actual attitudes.
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5.1.2.1. Creating indices. The Time 1 actual attitude items were highly inter-correlated in each sample, rStudy2a(115) = 0.73, p < .001, rStudy2b(512) = 0.87, p < .001, so we averaged them into Time 1 attitude indices. Time 2 ideal and ought attitudes were highly correlated in each sample, rStudy2a(115) = 0.82, p < .001, rStudy2b(512) = 0.79, p < .001, so we averaged these to represent desired attitudes. 5.2. Results
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5.2.1. Manipulation check: Desired attitudes In Table 3, we examine several factors related to the formation of desired attitudes towards the painting across the two experimental samples. In Experiment 2a, Time 1 actual attitudes were not significantly related to desired attitudes at Time 2. However, Time 2 actual attitudes were significantly and substantially related to desired attitudes at Time 2. This finding is unsurprising because people likely use their actual attitudes as an anchor for determining their desired attitude although their pre-manipulation attitudes presumably do not serve this same 5.1. Methods
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5.1.1. Participants For Experiment 2a, we recruited 119 undergraduates from a Canadian University to complete the study online for partial course credit (79.8% women, 20.2% men, 0% non-binary or prefer not to answer; Mage = 19.5 years, SDage = 5.2).6 For Experiment 2b, we recruited 514 online volunteer American participants from ResearchMatch (74.0% women, 24.0% men, 0.8% non-binary, 1.2% prefer not to answer; 86.7% Caucasian/White, 3.5% African American/Black, 3.1% mixed, 1.8% Latinx, 1.2% East Asian, 1.4% other, and 0.6% East Indian; 2.2% did not answer). The latter group was substantially older than all previous samples, Mage = 52.2 years, and with much greater heterogeneity in age, SD = 16.4. In each case, sample sizes were determined by time-based stopping rules, and they permitted us with 80% statistical power to detect effect sizes of r > 0.25 and 0.13, respectively. We reasoned that smaller samples compared to Experiment 1 were reasonable given that
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