Your Understanding Is My Understanding

Sloman, Steven A.; Rabb, Nathaniel

doi:10.1177/0956797616662271

Cited by 73 publications

(50 citation statements)

References 38 publications

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“…Our findings additionally expand our knowledge of how the IOED influences people's reasoning and decision-making in several ways. First, our findings add to the growing observations of the IOED in phenomena besides everyday devices (Alter et al, 2010;Fernbach et al, 2013;Fisher & Keil, 2014;Sloman & Rabb, 2016;Zeveney & Marsh, 2016), further demonstrating the robustness of people's overconfidence in their perceived causal understanding of the world. Second, our results provide one of the first demonstrations of how the IOED can affect other kinds of beliefs (Fernbach et al, 2013), enriching our understanding of the consequences explanation can have in other areas of reasoning.…”

Section: Discussionsupporting

confidence: 71%

The illusion of explanatory depth and endorsement of conspiracy beliefs

Vitriol

Marsh

2018

Euro J Social Psych

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The average person possesses superficial understanding of complex causal relations and, consequently, tends to overestimate the quality and depth of their explanatory knowledge. In this study, we examined the role of this illusion of explanatory depth (IOED) in politics—inflated confidence in one's causal understanding of political phenomena—for endorsement of conspiracy beliefs. Utilizing a pre‐/post‐election panel design and a large sample of U.S. Citizens (N = 394) recruited in the context of the 2016 presidential election, we provide evidence that political IOED, but not a non‐political IOED, was associated with increased support for general and election‐specific conspiracy beliefs, particularly among political novices and supporters of the losing candidate. We find this pattern of results net the influence of a broad range of variables known to covary with conspiracy beliefs. Implications for theory and the need for future research are discussed.

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Section: Discussionsupporting

confidence: 71%

The illusion of explanatory depth and endorsement of conspiracy beliefs

Vitriol

Marsh

2018

Euro J Social Psych

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“…Prior research suggests that laypeople's understanding of disease symptomology can shape their perception of effective treatment (Marsh and Zeveney, 2015;Marsh and Romano, 2016). Further, selfperceived causal understanding is closely tied to perceptions of causal understanding among scientists or experts (Sloman and Rabb, 2016;Rabb et al, 2019), the latter of which has been directly implicated in COVID-19 mitigation behaviors (Marsh et al, 2021). These findings suggest that perceived understanding, by both the self and scientists, of how COVID-19 spreads could translate to increased belief in and compliance with behavioral mitigation.…”

Section: Current Researchmentioning

confidence: 99%

A Pandemic of Misbelief: How Beliefs Promote or Undermine COVID-19 Mitigation

Vitriol

Marsh

2021

Front. Polit. Sci.

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Sustained and coordinated social action is needed to combat the spread of the novel coronavirus disease 2019 (COVID-19). Health practitioners and governments around the world have issued recommendations and mandates designed to reduce the transmission of COVID-19 by influencing the social behaviors of the general public. Why and when are some people unwilling to take action to protect themselves and others from the effects of this public health crisis? We find that belief in COVID-19 consensus information (by the self or perceptions of scientists’ beliefs), are consequential predictors of COVID-19 mitigation behaviors. Importantly, support for COVID-19 conspiracy theories predicted decreased, whereas perceived understanding of COVID-19 predicted increased, belief in COVID-19 consensus information. We also implemented an Illusion of Explanatory depth paradigm, an approach to examining knowledge overestimation shown to reduce confidence in one’s understanding of complex phenomena. By requiring participants to elaborate upon COVID-19 conspiracies, we experimentally increased understanding of these theories, which led, in turn, to ironic increases in support for the conspiracy theories and undermined perceived understanding of COVID-19 information for a notable portion of our participants. Together, our results suggest that attention given to COVID-19 conspiracies may be misguided; describing or explaining the existence of COVID-19 conspiracies may ironically increase support for these accounts and undermine knowledge about and willingness to engage in COVID-19 mitigation.

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“…However, our results suggest that such efforts may actually cause a certain population of readers to be misled about the strength of the scientific evidence. The misinterpretation may be exacerbated by the phenomenon that readers are swayed to believe a statement when they are told scientists understand it ( Sloman & Rabb, 2016 ). Because interpretation, and thus explanation, is an essential aspect of science communication, we should not aim to avoid explanation but to understand how certain characteristics of explanation help or hinder perception.…”

Section: Discussionmentioning

confidence: 99%

Explanation of observational data engenders a causal belief about smoking and cancer

Myint

Leek

Jager

2018

PeerJ

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Most researchers do not deliberately claim causal results in an observational study. But do we lead our readers to draw a causal conclusion unintentionally by explaining why significant correlations and relationships may exist? Here we perform a randomized controlled experiment in a massive open online course run in 2013 that teaches data analysis concepts to test the hypothesis that explaining an analysis will lead readers to interpret an inferential analysis as causal. We test this hypothesis with a single example of an observational study on the relationship between smoking and cancer. We show that adding an explanation to the description of an inferential analysis leads to a 15.2% increase in readers interpreting the analysis as causal (95% confidence interval for difference in two proportions: 12.8%–17.5%). We then replicate this finding in a second large scale massive open online course. Nearly every scientific study, regardless of the study design, includes an explanation for observed effects. Our results suggest that these explanations may be misleading to the audience of these data analyses and that qualification of explanations could be a useful avenue of exploration in future research to counteract the problem. Our results invite many opportunities for further research to broaden the scope of these findings beyond the single smoking-cancer example examined here.

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Your Understanding Is My Understanding

Cited by 73 publications

References 38 publications

The illusion of explanatory depth and endorsement of conspiracy beliefs

The illusion of explanatory depth and endorsement of conspiracy beliefs

A Pandemic of Misbelief: How Beliefs Promote or Undermine COVID-19 Mitigation

Explanation of observational data engenders a causal belief about smoking and cancer

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