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Sizing up information distortion: Quantifying its effect on the subjective values of choice options

Overview of attention for article published in Psychonomic Bulletin & Review, December 2011
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Title
Sizing up information distortion: Quantifying its effect on the subjective values of choice options
Published in
Psychonomic Bulletin & Review, December 2011
DOI 10.3758/s13423-011-0184-8
Pubmed ID
Authors

Michael L. DeKay, Eric R. Stone, Clare M. Sorenson

Abstract

When choosing between options, people often distort new information in a direction that favors their developing preference. Such information distortion is widespread and robust, but less is known about the magnitude of its effects. In particular, research has not quantified the effects of distortion relative to the values of the choice options. In two experiments, we manipulated participants' initial preferences in choices between risky three-outcome monetary gambles (win, lose, or neither) by varying the order of five information items (e.g., amount to win, chance of losing). In Experiment 1 (N = 397), the effect of initial information on gambles' certainty equivalents (subjective values) was mediated by the distortion of later information. The indirect effect on the difference between gambles' certainty equivalents averaged 27% of the gambles' mean expected value. In Experiment 2 (N = 791), we increased the difference between gambles on a later information item to overcome the effect of initial information on participants' choices. The required change averaged 31% of the gambles' mean expected value. We conclude that the effects of information distortion can be substantial.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 3%
Unknown 32 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 15%
Student > Master 4 12%
Student > Doctoral Student 3 9%
Lecturer 2 6%
Professor 2 6%
Other 4 12%
Unknown 13 39%
Readers by discipline Count As %
Psychology 10 30%
Social Sciences 4 12%
Computer Science 2 6%
Medicine and Dentistry 2 6%
Business, Management and Accounting 1 3%
Other 0 0%
Unknown 14 42%