1,401
Views
1
CrossRef citations to date
0
Altmetric
Research Article

The effect of source credibility on the evaluation of statements in a spiritual and scientific context: A registered report study

ORCID Icon, ORCID Icon, ORCID Icon, & ORCID Icon
Pages 59-84 | Received 06 Aug 2020, Accepted 16 Jan 2022, Published online: 12 Apr 2022

References

  • Aust, F., & Barth, M. (2018). papaja: Prepare reproducible apa journal articles with r markdown. (version 0.1.0.9997) https://github.com/crsh/papaja
  • Barth, M. (2020). Tinylabels: Lightweight variable labels. (version 0.1.0) https://CRAN.R-project.org/package=tinylabels
  • Bates, D., & Maechler, M. (2010). Matrix: Sparse and dense matrix classes and methods. (version 1.3.2) http://cran.r-project.org/package=Matrix
  • Bialek, M., & Pennycook, G. (2018). The cognitive reflection test is robust to multiple exposures. Behavior Research Methods, 50(5), 1953–1959. https://doi.org/10.3758/s13428-017-0963-x
  • Chaiken, S., & Maheswaran, D. (1994). Heuristic processing can bias systematic processing: Effects of source credibility, argument ambiguity, and task importance on attitude judgment. Journal of Personality and Social Psychology, 66(3), 460–473. https://doi.org/10.1037/0022-3514.66.3.460
  • Dawson, E., Gilovich, T., & Regan, D. T. (2002). Motivated reasoning and performance on the was on selection task. Personality & Social Psychology Bulletin, 28(10), 1379–1387. https://doi.org/10.1177/014616702236869
  • Eklund, A. (2016). beeswarm: The bee swarm plot, an alternative to stripchart. (version 0.2.3) h ttps.//CRAN.R-project.o rg/package=beeswarm
  • Evans, A., Sleegers, W., & Mlakar, Ž. (2020). Individual differences in receptivity to scientific bullshit. Judgment and Decision Making, 15(3), 401–412 http://journal.sjdm.org/20/200221/jdm200221.pdf
  • Evans, J. H. (2011). Epistemological and moral conflict between religion and science. Journal for the Scientific Study of Religion, 50(4), 707–727. https://doi.org/10.1111/j.1468-5906.2011.01603.x
  • Faircloth, C. (2010). ‘what science says is best’: Parenting practices, scientific authority and maternal identity. Sociological Research Online, 15(4), 85–98. https://doi.org/10.5153/sro.2175
  • Farias, M., Newheiser, A.-K., Kahane, G., & de Toledo, Z. (2013). Scientific faith: Belief in science increases in the face of stress and existential anxiety. Journal of Experimental Social Psychology, 49(6), 1210–1213. https://doi.org/10.1016/j.jesp.2013.05.008
  • Farias, M., van Mulukom, V., Kahane, G., Kreplin, U., Joyce, A., Soares, P., Oviedo, L., Hernu, M., Rokita, K., Savulescu, J., & Möttönen, R. (2017). Supernatural belief is not modulated by intuitive thinking style or cognitive inhibition. Scientific Reports, 7(1), 1–8. https://doi.org/10.1038/s41598-017-14090-9
  • Funk, C., Hefferon, M., Kennedy, B., & Johnson, C. (2019). Trust and mistrust in americans’ views of scientific experts. Pew Research Center. https://www.pewresearch.org/science/2019/08/02/trust-and-mistrust-inamericans-views-of-scientific-experts
  • Garrett, B. M., & Cutting, R. L. (2017). Magical beliefs and discriminating science from pseudoscience in undergraduate professional students. Heliyon, 3(11), e00433. https://doi.org/10.1016/j.heliyon.2017.e00433
  • Gervais, W. M., van Elk, M., Xygalatas, D., McKay, R. T., Aveyard, M., and Buchtel, E. E., Dar-Nimrod, I., Klocová, E. K., Ramsey, J. E., Riekki, T., Svedholm-Häkkinen, A. M., & Bulbulia, J. A. (2018). Analytic atheism: A cross-culturally weak and fickle phenomenon? Judgment and Decision Making, 13(3), 268-274. http://journal.sjdm.org/18/18228/jdm18228.pdf.
  • Gheorghiu, A. I., Callan, M. J., & Skylark, W. J. (2017). Facial appearance affects science communication. Proceedings of the National Academy of Sciences, 114(23), 5970–5975. https://doi.org/10.1073/pnas.1620542114
  • Ginn, J., & Silge, J. (2021). Qualtrics: Download ‘qualtrics’ survey data. (version 3.1.4) https://CRAN.R-project.org/package=qualtRics
  • Haaf, J. M., & Rouder, J. N. (2017). Developing constraint in Bayesian mixed models. Psychological Methods, 22(4), 779–798. https://doi.org/10.31234/osf.io/ktjnq
  • Hoogeveen, S., Haaf, J. M., Bulbulia, J. A., Ross, R. M., McKay, R., Altay, S., and van Elk, M. (2022). The Einstein effect provides global evidence for scientific source credibility effects and the influence of religiosity. Nature Human Behaviour. https://doi.org/10.1038/s41562-021-01273-8
  • Kahan, D. M., Jenkins-Smith, H., & Braman, D. (2011). Cultural cognition of scientific consensus. Journal of Risk Research, 14(2), 147–174. https://doi.org/10.1080/13669877.2010.511246
  • Kahan, D. M., Peters, E., Wittlin, M., Slovic, P., Ouellette, L. L., Braman, D., & Mandel, G. (2012). The polarizing impact of science literacy and numeracy on perceived climate change risks. Nature Climate Change, 2(10), 732–735. https://doi.org/10.1038/nclimate1547
  • Kobayashi, K. (2018). The impact of perceived scientific and social consensus on scientific beliefs. Science Communication, 40(1), 63–88. https://doi.org/10.1177/1075547017748948
  • Lachapelle, E., Montpetit, É., & Gauvin, J.-P. (2014). Public perceptions of expert credibility on policy issues: The role of expert framing and political worldviews. Policy Studies Journal, 42(4), 674–697. https://doi.org/10.1111/psj.12073
  • Legare, C. H., Evans, E. M., Rosengren, K. S., & Harris, P. L. (2012). The coexistence of natural and supernatural explanations across cultures and development. Child Development, 83(3), 779–793. https://doi.org/10.1111/j.1467-8624.2012.01743.x
  • Lindeman, M., & Lipsanen, J. (2016). Diverse cognitive profiles of religious believers and nonbelievers. The International Journal for the Psychology of Religion, 26(3), 185–192. https://doi.org/10.1080/10508619.2015.1091695
  • Lindeman, M., & Svedholm, A. M. (2012). What’s in a term? Paranormal, superstitious, magical and supernatural beliefs by any other name would mean the same. Review of General Psychology, 16(3), 241–255. https://doi.org/10.1037/a0027158
  • Maij, D. L., van Harreveld, F., Gervais, W., Schrag, Y., Mohr, C., & van Elk, M. (2017). Mentalizing skills do not differentiate believers from non-believers, but credibility enhancing displays do. PloS one, 12(8), e0182764. https://doi.org/10.1371/journal.pone.0182764
  • Makowski, D., Ben-Shachar, M. S., Patil, I., & Lüdecke, D. (2021). Automated results reporting as a practical tool to improve reproducibility and methodological best practices adoption. (version 0.3.0).https://github.com/easystats/report
  • Mayo, R. (2019). The skeptical (ungullible) mindset. In J. P. Forgas & R. F. Baumeister (Eds.), The Social Psychology of Gullibility: Conspiracy Theories, Fake News and Irrational Beliefs (pp.140-158). Routledge, New York. https://doi.org/10.4324/2F9780429203787-8
  • McPhetres, J., Jong, J., & Zuckerman, M. (2020). Religious americans have less positive attitudes toward science, but this does not extend to other cultures. Social Psychological and Personality Science, 12(4), 528-536. https://doi.org/10.1177/1948550620923239.
  • McPhetres, J., & Nguyen, T.-V. T. (2018). Using findings from the cognitive science of religion to understand current conflicts between religious and scientific ideologies. Religion, Brain & Behavior, 8(4), 394–405. https://doi.org/10.1080/2153599X.2017.1326399
  • McPhetres, J., & Zuckerman, M. (2017). Religious people endorse different standards of evidence when evaluating religious versus scientific claims. Social Psychological and Behavior Personality Science, 8(7), 836–842. https://doi.org/10.1177/1948550617691098
  • McPhetres, J., & Zuckerman, M. (2018). Religiosity predicts negative attitudes towards science and lower levels of science literacy. PloS one, 13(11), e0207125. https://doi.org/10.1371/journal.pone.0207125
  • Morey, R. D., & Rouder, J. N. (2018). Bayesfactor: Computation of Bayes factors for common designs. (version 0.9.12.4.2) https://CRAN.R-project.org/package=BayesFactor
  • Myers, T. A., Maibach, E. W., Roser-Renouf, C., Akerlof, K., & Leiserowitz, A. A. (2013). The relationship between personal experience and belief in the reality of global warming. Nature Climate Change, 3(4), 343–347. https://doi.org/10.1038/nclimate1754
  • O’Brien, T. C., Palmer, R., & Albarracin, D. (2021). Misplaced trust: When trust in science fosters belief in pseudoscience and the benefits of critical evaluation. Journal of Experimental Social Psychology, 96, 104184. https://doi.org/10.1016/j.jesp.2021.104184
  • Patel, N. (2017). The cognitive reflection test: A measure of intuition/reflection, numeracy, and insight problem solving, and the implications for understanding real-world judgments and beliefs. University of Missouri-Columbia.
  • Patzer, G. L. (1983). Source credibility as a function of communicator physical attractiveness. Journal of Business Research, 11(2), 229–241. https://doi.org/10.1016/0148-2963(83)90030-9
  • Pennycook, G., Cheyne, J. A., Barr, N., Koehler, D. J., & Fugelsang, J. A. (2015). On the reception and detection of pseudo-profound bullshit. Judgment and Decision Making, 10(6), 549–563. http://journal.sjdm.org/15/15923a/jdm15923a.pdf
  • Pennycook, G., Cheyne, J. A., Koehler, D. J., & Fugelsang, J. A. (2016). Is the cognitive reflection test a measure of both reflection and intuition? Behavior Research Methods, 48(1), 341–348. https://doi.org/10.3758/s13428-015-0576-1
  • Pennycook, G., Cheyne, J. A., Seli, P., Koehler, D. J., & Fugelsang, J. A. (2012). Analytic cognitive style predicts religious and paranormal belief. Cognition, 123(3), 335–346. https://doi.org/10.1016/j.cognition.2012.03.003
  • Pennycook, G., Fugelsang, J. A., & Koehler, D. J. (2015). Everyday consequences of analytic thinking. Current Directions in Psychological Science, 24(6), 425–432. https://doi.org/10.1177/0963721415604610
  • Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting covid-19 misinformation on social media: Experimental evidence for a scalable accuracy-nudge intervention. Psychological Science, 31(7), 770–780. https://doi.org/10.1177/0956797620939054
  • Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In R. E. Petty & J. T. Cacioppo (Eds.), Communication and persuasion (pp. 1–24). Springer, New York.
  • Pfadt, J. M., van den Bergh, D., & Goosen, J. (2021). Bayesrel: Bayesian reliability estimation. (version0.7.0.3) https://CRAN.R-project.org/package=Bayesrel
  • Plummer, M., Best, N., Cowles, K., & Vines, K. (2006). Coda: Convergence diagnosis893and output analysis for mcmc. (version0.19.4) https://journal.r-project.org/archive/
  • Poldrack, R. A. (2011). Inferring mental states from neuroimaging data: From reverse inference to large-scale decoding. Neuron, 72(5), 692–697. https://doi.org/10.1016/j.neuron.2011.11.001
  • Pornpitakpan, C. (2004). The persuasiveness of source credibility: A critical review of five decades’ evidence. Journal of Applied Social Psychology, 34(2), 243–281. https://doi.org/10.1111/j.1559-1816.2004.tb02547.x
  • R Core Team (2013). R: A language and environment for statistical computing. (version 4.0.2) https://www.R-project.org/
  • Ram, K., & Wickham, H. (2018). Wesanderson: A wes anderson palette generator. (version 0.3.6) https://journal.r-project.org/archive/
  • Randall, T. M., & Desrosiers, M. (1980). Measurement of supernatural belief: Sex differences and locus of control. Journal of Personality Assessment, 44(5), 493–498. https://doi.org/10.1207/s15327752jpa4405_9
  • Roberts, C. (2010). Correlations among variables in message and messenger credibility scales. American Behavioral Scientist, 54(1), 43–56. https://doi.org/10.1177/0002764210376310
  • Rouder, J. N. (2014). Optional stopping: No problem for Bayesians. Psychonomic Bulletin & Review, 21(2), 301–308. https://doi.org/10.3758/s13423-014-0595-4
  • Rouder, J. N., Haaf, J. M., Davis-Stober, C. P., & Hilgard, J. (2019). Beyond overall effects: A Bayesian approach to finding constraints in meta-analysis. Psychological Methods, 24(5), 606–621. https://doi.org/10.1037/met0000216
  • Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012). Default Bayes factors for ANOVA designs. Journal of Mathematical Psychology, 56(5), 356–374. https://doi.org/10.1016/J.JMP.2012.08.001
  • Rutjens, B. T., Sutton, R. M., & van der Lee, R. (2018). Not all skepticism is equal: Exploring the ideological antecedents of science acceptance and rejection. Personality & Social Psychology Bulletin, 44(3), 384–405. https://doi.org/10.1177/0146167217741314
  • Rutjens, B. T., & van der Lee, R. (2020). Spiritual skepticism? Heterogeneous science skepticism in the Netherlands. Public Understanding of Science, 29(3), 335–352. https://doi.org/10.1177/0963662520908534
  • Sambrook, K., Konstantinidis, E., Russell, S., & Okan, Y. (2021). The role of personal experience and prior beliefs in shaping climate change perceptions: A narrative review. Frontiers in Psychology, 12, 2679. https://doi.org/10.3389/fpsyg.2021.669911
  • Schjoedt, U., Sørensen, J., Nielbo, K. L., Xygalatas, D., Mitkidis, P., & Bulbulia, J. (2013). Cognitive resource depletion in religious interactions. Religion, Brain & Behavior, 3(1), 39–55. https://doi.org/10.1080/2153599X.2012.736714
  • Schjoedt, U., Stødkilde-Jørgensen, H., Geertz, A. W., Lund, T. E., & Roepstorff, A. (2011). The power of charisma—perceived charisma inhibits the frontal executive network of believers in intercessory prayer. Social Cognitive and Affective Neuroscience, 6(1), 119–127. https://doi.org/10.1093/scan/nsq023
  • Schönbrodt, F. D., Wagenmakers, E.-J., Zehetleitner, M., & Perugini, M. (2017). Sequential hypothesis testing with Bayes factors: Efficiently testing mean differences. Psychological Methods, 22(2), 322–339. https://doi.org/10.1037/met0000061
  • Stern, S. E., Mullennix, J. W., & Yaroslavsky, I. (2006). Persuasion and social perception of human vs. synthetic voice across person as source and computer as source conditions. International Journal of Human-Computer Studies, 64(1), 43–52. https://doi.org/10.1016/j.ijhcs.2005.07.002
  • Taves, A., Asprem, E., & Ihm, E. (2018). Psychology, meaning making, and the study of worldviews: Beyond religion and non-religion. Psychology of Religion and Spirituality, 10(3), 207. https://doi.org/10.1037/rel0000201
  • Thomson, K. S., & Oppenheimer, D. M. (2016). Investigating an alternate form of the cognitive reflection test. Judgment and Decision Making, 11(1), 99. http://journal.sjdm.org/15/151029/jdm151029.pdf
  • Umeogu, B. (2012). Source credibility: A philosophical analysis. Open Journal of Philosophy, 2(2), 112. https://doi.org/10.4236/ojpp.2012.22017
  • van Elk, M., & Snoek, L. (2020). The relationship between individual differences in gray matter volume and religiosity and mystical experiences: A preregistered voxel-based morphometry study. European Journal of Neuroscience, 51(3), 850–865. https://doi.org/10.1111/ejn.14563
  • Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Rouder, J. N., & Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35–57. https://doi.org/10.3758/s13423-017-1343-3
  • Weisberg, D. S., Keil, F. C., Goodstein, J., Rawson, E., & Gray, J. R. (2008). The seductive allure of neuroscience explanations. Journal of Cognitive Neuroscience, 20(3), 470–477. https://doi.org/10.1162/jocn.2008.20040
  • Weisberg, D. S., Taylor, J. C., & Hopkins, E. J. (2015). Deconstructing the seductive allure of neuroscience explanations. Judgment and Decision Making, 10(5), 429. http://journal.sjdm.org/15/15731a/jdm15731a.pdf
  • Wickham, H., François, R., Henry, L., & Müller, K. (2021). Dplyr: A grammar of data manipulation. (version 1.0.5) https://CRAN.R-project.org/package=dplyr
  • Wickham, H., & Seidel, D. (2020). Scales: Scale functions for visualization. (version 1.1.1) https://CRAN.R-project.org/package=scales