'Moved by Racial Justice: The Role of Kama muta in Collective Action'
(AsPredicted #63768)
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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?
Main question: What is the role of the emotion kama muta in collective action toward racial equality?

Hypotheses:
The role of kama muta:
H1.a Collective efficacy appraisals are positively associated with collective action intentions toward racial equality
H1.b Kama muta toward the BLM movement is positively associated with collective action intentions toward racial equality
H1.c Kama muta toward the BLM movement mediates the relationship between collective efficacy and collective action intentions.
The role of anger:
H2.a Unfairness appraisals are positively associated with collective action intentions towards racial equality
H2.b Anger toward the system of racial inequalities has a positive effect on collective action intentions toward racial equality.
H2.c Anger toward the system of racial inequalities partly mediates the relationship between injustice appraisals and collective action intentions
The role of sadness:
H3.a Sadness toward the system of racial inequalities has a positive effect on collective action intentions toward racial equality
H3.b Sadness toward the system of racial inequalities partly mediates the relationship between unfairness appraisal and collective action intentions.

3) Describe the key dependent variable(s) specifying how they will be measured.
Emotions: Participants will be presented with descriptions of three emotions: Kama muta (labeled positive experience of being moved), anger and sadness. Descriptions contain detailed information about the valence, appraisals, physical reactions and labels that characterise each one of these emotions. Participants will indicate their emotional experiences through four items assessing frequency, intensity, salience and ease of retrieval toward two targets: The black lives matter movement and the system of racial inequalities. All 3 emotions will be assessed for both social targets in a 3 x 2 within-participant design.
Appraisals: Collective efficacy (3 items) and injustice appraisals (3 items).
Collective action tendencies: collective action intentions (7 items).
In addition, identity (5 items), attitudes toward 5 targets (5 items), contact quality (2 items), age, gender, ideology, ethnicity and level of education will be assessed. We also include two dichotomous items on whether participants support the BLM movement and the goal of racial equality at all for exploratory analyses.

The emotion measure has been tested in a pilot study and found to be internally consistent. The same applies to the collective action intention measure. The appraisal measures have been used in the literature before, but not been used in our pilot test. We will check all variables for internal consistency before proceeding with analyses. If internal consistency (Cronbach's alpha) drops below .70 will we use exploratory factor analysis and correlation matrices to determine if scales can be recomposed to improve internal consistency of measures. These determinations will be made before any model checking between the relations is run.

4) How many and which conditions will participants be assigned to?
All participants will respond to the same questionnaire.

5) Specify exactly which analyses you will conduct to examine the main question/hypothesis.
Multiple regression:
Model 1. To test H1.a and H2.a, we will run a multiple regression with the DV collective action and the two appraisals as predictors.
Model 2. To test H1.b, H2b, and H3a, we will run a multiple regression with the DV collective action and kama muta towards the movement, anger towards the system, and sadness towards the system as predictors.
Mediation analysis:
Model 3. To test H1.c, H2.c and H3.b, we will specify a path model with the two appraisals as predictors, the three emotions as mediators, and collective action as the outcome.

We will run each of these models for Black and White participants separately, and also on the combined sample with race as a main effect and moderator. The multiple regression models will therefore include a contrast-coded variable for race, centred continuous predictors, and multiplied interaction terms. The mediation model will be run on the combined sample while adding race as a grouping factor, setting paths equal between groups, and only relaxing these constraints if modification indices indicate a violation of the assumption. Our main prediction is that the hypotheses will hold on the combined sample without being moderated. The exception is that we expect anger to be a stronger predictor for Black participants. If we observe significant moderations, we will follow up with the results from the separate models. If we observe insignificant paths with insignificant moderations, we will follow up with results from separate models, but correct those (two) tests with a Bonferroni correction.

6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations.
Sampling will be done on Prolific using their function to collect data from White and Black US American participants. If self-reported race does not follow into one of these categories, the participants will be removed. Data from participants who failed 1 or more attention checks will be excluded from the analysis. The distribution of the response times will be inspected for the presence of a bimodal distribution, with some participants answering much faster. If such a cluster is found, these very fast participants will be removed. In addition, data from participants that exceed 3SD the average response time of the questionnaire will be also excluded. These deletions will be done before analysing any other data.

We will inspect the data for unusual patterns of answers that possibly indicate unserious participation. It is impossible for us to list such possible patterns here. If we find suspicious cases, we will delegate the decision on whether to include them or not to the co-supervisor of this MA thesis project.

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 attempt to collect information from 300 US American participants. We will aim to gather information from two ethnic groups: 150 black Americans and 150 white Americans. Because we do not have the estimates to run an accurate power analysis, we base the sample size on a previous research following a similar study design (Landmann & Rohmann, 2020, who argued for N=170 for a model with two parallel mediators) and Schönbrodt and Perugini's (2013) recommendation for a minimum sample size to achieve stable estimates of correlations (N=150 per sample).

8) Anything else you would like to pre-register?
(e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?)
We will run additional exploratory correlational and regression analyses to explore the associations between emotions (kama muta, anger, sadness) appraisals (collective efficacy and unfairness), collective action intentions, identity (white, black, US Americans, the BLM movement, racial justice activists and the system of racial inequalities), ideology, attitudes and contact quality toward black and white people. In specific, exploratory analysis to determine the possible role of contact and attitudes toward black people in collective action. We will also run an exploratory analysis with the exclusion of participants that do not support racial equality or the Black Lives Matter Movement. We will run and report a 3 (emotions) x 2 (targets) x 2 (race) ANOVA on the strength of emotions to describe the sample.