Research Proposal / Dissertation Proposal Example

Do British Conspiracy-Theorists perceive illusory patterns more frequently than Non-Conspiracy-Theorists?

Conspiracy Theories (CTs) have left their mark on the cultural landscape of the world over the past 5 years. In America, widespread conspiracy belief has spurred some of the greatest political upsets of the age (Hellinger, 2018) and smaller CTs, such as Flat Earth, have seen an uptick in online presence (Landrum, 2019). This surge in conspiracy mindedness led to little recent research being focused on countries outside of the USA, until the 2019 global coronavirus pandemic, wherein conspiracy theories became a cause for concern internationally (Johnson et-al, 2021). Approximately 50% of the British population display some degree of conspiracy endorsement regarding COVID-19, with greater levels of endorsement being negatively associated with likelihood to engage with government guidelines (Freeman et-al, 2021).

Currently there are two prevailing theories regarding why people believe CTs: Evolved Adaptation Theory and By-Product Theory (Prooijen Vugt, 2018). Evolved Adaptation Theory posits that the ability to perceive CTs is an adaptation that we have evolved as a way of detecting coalitional dangers (Prooijen Vugt, 2018). By-Product Theory postulates that conspiracy detection comes as a result of psychological processes with alternate functions that accidentally detect false threats that we recognise as CTs (Prooijen Vugt, 2018). Many of these psychological mechanisms have been found to be heavily associated with conspiratorial beliefs. Such mechanisms include Agency Detection (Douglas et al, 2016), Threat Management (Mashuri Zaduqisti, 2015), Alliance Detection, and Pattern Perception (Brotherton French, 2014). Some individuals perceive patterns where there are none due to an overactive pattern recognition ability these are called Illusory Patterns, and are positively correlated with conspiratorial belief (Prooijen et-al, 2017).

Studies within the field of Illusory Pattern Recognition work in a generally similar fashion. Participants are shown random stimuli, and asked if they perceive a pattern within the stimuli. Examples of studied stimuli include the snowy image task (Whitson Galinsky, 2008 Banning, 2014), stock-market information (Whitson Galinsky, 2008), or coin flips and modern art (Prooijen et-al, 2017). This lattermost study also used a novel method of sampling participants. Prooijen et-al s sampling method was a self-report 9-item questionnaire consisting of the most popular conspiracy theories of the day, as designated by Douglas and Sutton (2011) and Prooijen et-al (2015). Participants would answer a 5-point Likert Scale denoting their belief that the conspiracies were true. This method was adapted from Swami et-al s (2010) 14-item Belief In Conspiracy Theories Inventory (BICTI).

Like research aforementioned, recent studies in the field of Illusory Pattern Perception have been focused on American populations, leaving little evidence regarding the globality of this theory. As such, a consolidation of methodologies within this field, conducted upon a British participant sample, could yield some much-needed insight into how the British population construct CTs or at least aid in confirming or falsifying the Pattern Perception element of the By-Product Theory. This presents a research question. Do British Conspiracy-Theorists perceive illusory patterns more frequently than Non-Conspiracy-Theorists?

i. Design

The study will operate under an Independent Groups Design, comprised of two groups. An experiment group of Conspiracy Minded Participants, a control group of Non-Conspiracy Minded Participants. The Independent Variable between the two groups will be their score on Prooijen s (2017) Belief In Conspiracy Theories Inventory (BICTI). The measured Dependant Variable of the study will be a participant s score on a Banning (2014) modified Snowy Image Task.

ii. Participants

Like Prooijen et-al (2017), there will be approximately 100 participants per group. These participants will be opportunity sampled online via social media and allocated to either group based on their BICTI score. These participants must be British, and will be asked their nationality and gender in a participant information questionnaire prior to the BICTI.

iii. Materials

Researchers will use Prooijen et-al s (2017) modified 9-item BICTI to sample participants. This inventory will be slightly edited for a British audience, removing specific mention of the US government where possible, and updating references of the most recent pandemic to COVID-19 rather than Ebola (See Appendix A1 Appendix A2). A single factor score ( General Conspiracist Beliefs or GCB) is calculated by taking an average of responses across all items. Cronbach s for Prooijen s scale was a high 0.87.

A Banning (2014) modified Snowy Image Task will be used to assess Illusory Pattern Perception in participants (See Appendix B). This task consists of 10 pictures of scattered dots, 8 of which are totally random, and 2 of which are control items that contain actual images to increase test credibility. Results for these 2 images are discarded during analysis. Participants fill out a 0-10 Likert scale denoting how clearly they see a pattern or image, and a score for each participant is calculated by averaging their results for the 8 test images (SIT score). The control items and Likert-scale system make the Banning modified test more reliable and precise than the original binary Whitson (2008) test.

iv. Procedure

Firstly, participants will complete computerised ethical consent forms and an information sheet where they will be asked their nationality, gender, age, etc. Next, they will answer the adapted Prooijen et al (2017) BICTI, which should take approximately 3 minutes. Group divisions based upon these results will take place during data analysis. Following this, participants will take the Banning (2014) modified Snowy Image Task. Each image will be onscreen for as long as the participant requires, moving on only once they have input their Likert response. Once 10 results are recorded, the experiment is complete.

v. Analytic Strategy

Firstly, participant GCB scores from the BICTI, 1.0 to 5.0, will be used to allocate participants to either group with the score 2.5 being the threshold between groups. Following this, SIT scores will be calculated for every participant by averaging the scores they got for the 8 test items on the Snowy Image Task. Descri ptive and inferential statistical tests will be conducted upon the SIT scores for each group in SPSS. Mean scores, standard deviation, and confidence intervals will be compiled into graphs. Tests for homogeneity of variance should be passed, after which an Independent Samples T-Test will be conducted. The hypothesis that Conspiracy-Mindedness is positively correlated with score on an Illusory Pattern Recognition Task will be tested to a level of significance of P=0.05.

References

Banning, L. (2014). Lacking control, Pattern Perception, and Symptom Overendorsement. Maastricht Student Journal of Psychology and Neuroscience, 3.

Brotherton, R. French, C. C. (2014). Belief in conspiracy theories and susceptibility to the conjunction fallacy. Applied Cognitive Psychology, 28(2), 238-248.

Douglas, K. M. Sutton, R. M. (2011). Does it take one to know one? Endorsement of conspiracy theories is influenced by personal willingness to conspire. British Journal of Social Psychology, 50(3), 544-552.

Douglas, K. M. Sutton, R. M. Callan, M. J. Dawtry, R. J. Harvey, A. J. (2016). Someone is pulling the strings: Hypersensitive agency detection and belief in conspiracy theories. Thinking Reasoning, 22(1), 57-77.

Freeman, D. Waite, F. Rosebrock, L. Petit, A. Causier, C. East, A. Jenner, L. Teale, A. L. Carr, L. Mulhall, S. Bold, E. Lambe, S. (2020). Coronavirus conspiracy beliefs, mistrust, and compliance with government guidelines in England. Psychological Medicine, 1-13.

Hellinger, D. (2018). Conspiracies and Conspiracy Theories in the Age of Trump. Springer. ISBN: 3319981587

Johnson, N. F. Velasquez, N. Restrepo, N. J. Leahy, R. Sear, R. Gabriel, N. Larson, H. Lupu, Y. (2021). Mainstreaming of conspiracy theories and misinformation. Cornell University. Arxiv preprint.

Landrum, A. R. Olshansky, A. Richards, O. (2021). Differential susceptibility to misleading flat earth arguments on youtube. Media Psychology, 24(1), 136-165.

Mashuri, A. Zaduqisti, E. (2015). The effect of intergroup threat and social identity salience on the belief in conspiracy theories over terrorism in Indonesia: Collective angst as a mediator. International Journal of Psychological Research, 8(1), 24-35.

Prooijen, J. W. Douglas, K. M. De Inocencio, C. (2018). Connecting the dots: Illusory pattern perception predicts belief in conspiracies and the supernatural. European journal of social psychology, 48(3), 320-335.

Prooijen, J. W. Vugt, M. (2018). Conspiracy theories: Evolved functions and psychological mechanisms. Perspectives on psychological science, 13(6), 770-788.

Prooijen, J. W. Krouwel, A. P. Pollet, T. V. (2015). Political extremism predicts belief in conspiracy theories. Social Psychological and Personality Science, 6(5), 570-578.

Whitson, J. A. Galinsky, A. D. (2008). Lacking control increases illusory pattern perception. science, 322(5898), 115-117.