Nils Kobis

Nils Kobis
Max Planck Institute for Human Development | MPIB · Center for Humans and Machines

PhD

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Question (1)
Question
Hi all,
We are conducting a meta-analysis on the role of intuition vs deliberation in dishonesty. Specifically, we are interested in experiments using two types of tasks, measuring the decision to lie (see 1a below) or the cognitive cost of lying (see 1b below), and manipulating cognitive processing (see 2 below). We would love to include any studies (published or unpublished) you might have run that meet the following criteria:
1a) Participants engage in one or more (incentivized or hypothetical) tasks allowing them to boost self (and/or other’s) profit by lying (e.g., tasks like Gneezy’s deception game, privately predicting coin tosses, reporting outcome of die rolls, solving numerical matrices, identifying where more dots appear, and more). We are interested both in studies including a control condition in which lying is not possible, and in studies in which lying is assessed by comparing behavior to the expected performance if participants are honest.
OR
1b) Participants engage in a computerized task recording reaction times for lie and for truth trials, at least 20 trials each, within the same subject (e.g., using the Differentiation of Deception paradigm, Autobiographical Implicit Association Test, Sheffield Lie test, TARA, Concealed Information Test / Guilty Knowledge Test).
AND
2) Cognitive processing capacity was experimentally manipulated, using for example: cognitive load, time pressure/delay, (ego) depletion, intuition/deliberation inductions (e.g. instructing participants to decide intuitively vs deliberatively, or having them recall a time in their life where intuition vs deliberation worked out well), sleep deprivation, alcohol, time of day effects, stress / anxiety, 2nd language, or any other manipulation of theoretical relevance.
To illustrate, some exemplar studies that meet these criteria:
1a) The decision to lie:
van ’t Veer, A. E., Stel, M., & van Beest, I. (2014). Limited capacity to lie: Cognitive load interferes with being dishonest. Judgment and Decision Making, 9, 199-206
Zhong, C. B. (2011). The ethical dangers of deliberative decision making. Administrative Science Quarterly, 56, 1–25
Shalvi, S., Eldar, O., & Bereby-Meyer, Y. (2012). Honesty requires time (and lack of justifications). Psychological Science, 23, 1264–1270
Gunia, B.C., Wang, L., Huang, L., Wang, J. & Murnighan, J.K. (2012). Contemplation and conversation: subtle Influences on moral decision making. Academy of Management Journal, 55,13–33.
1b) Cognitive costs of lying:  
Visu-Petra, G., Varga, M., Miclea, M., & Visu-Petra, L. (2013). When interference helps:
increasing executive load to facilitate deception detection in the concealed information
test. Frontiers in Psychology, 4, 146. doi:10.3389/fpsyg.2013.00146
Debey, E., Verschuere, B., & Crombez, G. (2012). Lying and executive control: An experimental investigation using ego depletion and goal neglect. Acta Psychologica, 140, 133-141.
Suchotzki, K., Crombez, G., Debey, E., Van Oorsouw, K., & Verschuere, B. (2014). In Vino Veritas? – Alcohol, Response Inhibition and Lying. Alcohol and Alcoholism, 50, 74-81.
If you have any studies you'd like to be included, please send them to us (n.c.kobis@uva.nl):
i) the raw data (in spss, excel, csv format), ideally including any subjects who might have been excluded from your main analyses (in particular, those excluded for failing manipulation checks for the cognitive process manipulation); or, if you would rather not share raw data but are willing to run tests on the data for us, let us know and we will follow up with details.
ii) a key explaining what each data column corresponds to
iii) details of the experimental setup - i.e. what the exact game/payoff structure was (1a) or what the exact RT paradigm was (1b), and how exactly the cognitive processing manipulation was implemented
iv) the subject pool and location in which the experiment was conducted (e.g. Yale undergrads in the Yale School of Management laboratory, or US residents on Amazon Mechanical Turk)
iv) how you would like us to cite your work (e.g., Rand (2016) title, Unpublished data.)
Thanks very much!
Nils Köbis, Shaul Shalvi, Bruno Verschuere, David Rand, & Yoella Bereby-Meyer

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