Author(s) This pre-registration is currently anonymous to enable blind peer-review. It has 2 authors.
Pre-registered on 09/29/2023 09:10 AM (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? In previous studies we have found consistent evidence that longtermists feel concerned for climate change/global warming. In this investigation we wish to delve deeper into potential mechanisms of this relationship. We consider three possibilities. (1) Longtermists care more about their and others future. (2) Longtermists show more altruistic tendencies. (3) Longtermists are more capable of envisioning an alternative and better future.
Thus, we hypothesize that longtermists will score higher than non-longtermists on legacy concerns, future self-continuity, expansive altruism, impartial beneficence, utopian thinking, and access to environmental cognitive alternatives (H1a-H1f). Furthermore, we hypothesize that each of the six above listed variables will correlate positively with support for pro-climate policies (H2a-H2f). These policies will focus on climate justice for minoritized people, climate justice for future generations, and general pro-climate measures. We hypothesize that longtermists will score higher on each of the three types of pro-climate policies (H3). Finally, we will explore whether the direct effect of longtermism on support for pro-climate policies is explained by any of the potential six underlying mechanisms.
3) Describe the key dependent variable(s) specifying how they will be measured. Longtermism beliefs will be captured with a 7-item measure developed by the researchers. Importantly, each item will be completed simultaneously at four different timeframes/timepoints (1,000, 10,000, 100,000, and 1,000,000 years in the future). Scores will be captured on slider scales ranging from 0 = strongly disagree – 100 = strongly agree. Participants will be classified as longtermists if they score above 75 for the closest temporal timeframe, and they have the same score, or higher for future timeframes.
Legacy concerns will be captured using three items from Zaval et al. (2015) and measured on a a 1 "strongly disagree" – 7 "strongly agree" Likert scale.
FSC will be measured with a single item using the seven overlapping circles to display FSC with oneself 25 years in the future (e.g., Hershfield et al., 2012).
Expansive altruism will be captured with the 6-item Expansive Altruism Scale (Caviola et al., 2022) and measured on a 1 "strongly disagree" – 7 "strongly agree" Likert scale.
Impartial beneficence will be captured with the 5-item IB subscale of the Oxford Utilitarianism Scale (Kahane et al., 2018) and measured on a 1 "strongly disagree" – 7 "strongly agree" Likert scale.
Utopian Thinking will be captured with 8 items from Fernando et al. (2018), on a 7-point Likert scale.
Environmental Cognitive Alternatives will be captured with 10 items from Wright et al. (2020), on a 7-point Likert scale.
All items focusing on pro-climate policies will be taken directly from or adapted by items generated by the Yale Program for Climate Change Communication (YPCCC). Nine of these items focus on general pro-climate policy support (see here: https://climatecommunication.yale.edu/visualizations-data/ycom-us/). Seven items focus on climate justice for minoritized people, also taken directly from YPCC (see here: https://climatecommunication.yale.edu/publications/climate-change-in-the-american-mind-climate-justice-spring-2023/). Finally, four items were adapted to focus on climate justice for future generations. These items are highly similar to the original climate justice items, with the only difference being that the target group is future people.
4) How many and which conditions will participants be assigned to? No random assignment will take place.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. All analyses will be conducted in SAS. Graphing of results will be conducted in Rstudio and/or Jamovi.
H1a-H1f and H3 will be evaluated via independent sample t-tests. Any significant effects will also be re-evaluated controlling for political orientation, age, and subjective socioeconomic status (SES) in linear regression models.
H2a-H2f will be evaluated via bivariate correlations.
Indirect effect tests will be evaluated using the PROCESS Macro (Hayes, 2013), Model 4 with 10,000 bootstrapped samples. To avoid running multiple tests, if all associations between potential mediators and each type of pro-climate policy and the comparisons between longtermists and the general population for the of pro-climate policies are consistent (i.e., in terms of significant, magnitude of effect size, and direction) and if the three types of pro-climate policies create a construct with reliability (Cronbach's alpha) of at least .70, then we will average them into a single construct to avoid running multiple tests. Indirect effects will be estimated by following the following process:
1) Independently for each mediator
2) Including all significant mediators as parallel mediators.
3) Including all significant mediators, and controlling for age, SES and political orientation.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. We will exclude participants who miss our attention check (selecting the correct choice in a multiple-choice question) and participants with duplicate IP addresses.
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 recruit a sample size of 800 participants from Prolific. With 0 exclusions, we will have roughly 180 longtermists and 620 general population members, allowing us to detect effect sizes as small as d = 0.24 with power of 0.80. With 700 participants (100 excluded) we will have roughly 160 longtermists and 640 general population members, allowing us to detect effect sizes as small as d = 0.25 with power of 0.80
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) We will report correlations between scores on the longtermism beliefs scale and all outcomes in the supplementary materials.
