Pilgrims sailing the Titanic: Plausibility effects on memory for misinformation

Abstract

People rely on information they read even when it is inaccurate (Marsh, Meade, & Roediger, Journal of Memory and Language 49:519–536, 2003), but how ubiquitous is this phenomenon? In two experiments, we investigated whether this tendency to encode and rely on inaccuracies from text might be influenced by the plausibility of misinformation. In Experiment 1, we presented stories containing inaccurate plausible statements (e.g., “The Pilgrims’ ship was the Godspeed”), inaccurate implausible statements (e.g., . . . the Titanic), or accurate statements (e.g., . . . the Mayflower). On a subsequent test of general knowledge, participants relied significantly less on implausible than on plausible inaccuracies from the texts but continued to rely on accurate information. In Experiment 2, we replicated these results with the addition of a think-aloud procedure to elicit information about readers’ noticing and evaluative processes for plausible and implausible misinformation. Participants indicated more skepticism and less acceptance of implausible than of plausible inaccuracies. In contrast, they often failed to notice, completely ignored, and at times even explicitly accepted the misinformation provided by plausible lures. These results offer insight into the conditions under which reliance on inaccurate information occurs and suggest potential mechanisms that may underlie reported misinformation effects.

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Notes

  1. 1.

    We also analyzed participants’ confidence ratings and obtained results similar to the accuracy rates, including main effects of difficulty, F(1, 354) = 1,080.79, η p 2 = .75, and plausibility, F(1, 354) = 364.52, η p 2 = .51. Participants were less confident with hard (M = 4.02, SD = 0.79) than with easy (M = 5.07, SD = .61) items and less confident with plausible (M = 4.20, SD = 0.73) than with implausible (M = 4.89, SD = .72) lures. There was also a significant, but small, interaction between plausibility and difficulty, F(1, 354) = 6.55, η p 2 = .02.

  2. 2.

    Another option for this analysis would involve calculating mean conditional probabilities aggregated for each participant for different categories of think-aloud responses. However, several participants did not offer think-aloud responses in all categories. Specifically, 7 participants provided no skeptical responses, and 2 participants provided no acceptance responses. Additionally, 6 participants gave only one skeptical or acceptance response. Given the small number of observations for each type of response for particular participants, calculating conditional probabilities for each participant was problematic. We therefore conducted our analysis on the frequencies of think-aloud responses across participants.

  3. 3.

    It is possible that participants actually detected the inaccuracies during reading but avoided discussing them in their think-aloud responses. Any such cases would mean that the think-aloud methodology might underestimate the number of detections. Measurement of reading times to inaccurate information could help account for these subthreshold detections. However, we note that even explicit detection tasks have obtained relatively low detection rates for plausible lures (Marsh & Fazio, 2006), consistent with the think-aloud findings reported here.

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Author Note

Scott R. Hinze, Daniel G. Slaten, William S. Horton, Ryan Jenkins, and David N. Rapp, Northwestern University.

Scott R. Hinze is now in the Psychology Department at Virginia Wesleyan College.

Direct all correspondence to Scott Hinze, Department of Psychology, 1584 Wesleyan Dr., Virginia Wesleyan College, Norfolk, VA, 23502. E-mail: shinze@vwc.edu. Phone: 757-455-3288.

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Appendices

Appendix 1

Table 8 Questions, correct responses, and lures used in Experiments 1 and 2

Appendix 2

Table 9 Definitions and examples of think-aloud codes

Appendix 3

Table 10 Distribution of think-aloud responses for misleading frames
Table 11 Distribution of think-aloud responses for correct frames
Table 12 Distribution of think-aloud responses for neutral frames

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Hinze, S.R., Slaten, D.G., Horton, W.S. et al. Pilgrims sailing the Titanic: Plausibility effects on memory for misinformation. Mem Cogn 42, 305–324 (2014). https://doi.org/10.3758/s13421-013-0359-9

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Keywords

  • Memory
  • False memory
  • Text processing