Symmetrical choices and biased confidence during uncertain personality trait judgments

While great methodological strides have been made in the area of decision making research, decisions that rely on subjective stimuli, such as personality traits, still pose a challenge for researchers, partly because it is difficult to define a standard of accuracy for such choices-they lack a "ground truth". In studies on value-based decisions, this same problem has been circumvented by comparing uncertain subjective decisions against a separately assessed judgment of value-a "standard". Here we apply this method in a task of verbal personality trait judgment, and show how a separately assessed standard judgment can be used to precisely control stimulus presentation and analyze subjective personality choices via the method of reverse correlation. Per trial, a series of quasi-randomly sampled adjectives was shown, which participants categorized as more descriptive of either themselves of another person well known to them. Participants also indicated their confidence in the response. Each trial's difficulty was controlled based on the previously assessed standard judgment. Analysis of the behavioral data shows several decision-general properties during these personality judgments, such as symmetrical choices, steeper choice functions for confident trials, and a positive evidence bias during confidence judgment. We discuss how these findings can shed light on the cognitive processes involved in personality perception. The task and results together may help bridge the gap between research on complex, social forms of judgment and findings on more basic decision processes.

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PLoS ONE
Published
2024-10-31
DOI
https://doi.org/10.1371/journal.pone.0312858
Primary Topic
Evolutionary Psychology and Human Behavior
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article
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article

Symmetrical choices and biased confidence during uncertain personality trait judgments

Lorenz Weise, Verena Mainz, Siegfried Gauggel, Barbara Drüke
PLoS ONE
Evolutionary Psychology and Human Behavior
article

Symmetrical choices and biased confidence during uncertain personality trait judgments

Lorenz Weise, Verena Mainz, Siegfried Gauggel, Barbara Drüke
article en

Abstract

While great methodological strides have been made in the area of decision making research, decisions that rely on subjective stimuli, such as personality traits, still pose a challenge for researchers, partly because it is difficult to define a standard of accuracy for such choices-they lack a "ground truth". In studies on value-based decisions, this same problem has been circumvented by comparing uncertain subjective decisions against a separately assessed judgment of value-a "standard". Here we apply this method in a task of verbal personality trait judgment, and show how a separately assessed standard judgment can be used to precisely control stimulus presentation and analyze subjective personality choices via the method of reverse correlation. Per trial, a series of quasi-randomly sampled adjectives was shown, which participants categorized as more descriptive of either themselves of another person well known to them. Participants also indicated their confidence in the response. Each trial's difficulty was controlled based on the previously assessed standard judgment. Analysis of the behavioral data shows several decision-general properties during these personality judgments, such as symmetrical choices, steeper choice functions for confident trials, and a positive evidence bias during confidence judgment. We discuss how these findings can shed light on the cognitive processes involved in personality perception. The task and results together may help bridge the gap between research on complex, social forms of judgment and findings on more basic decision processes.

PLoS ONEVol. 19(10)
RWTH Aachen University (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 76%
Evolutionary Psychology and Human Behavior
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Symmetrical choices and biased confidence during uncertain personality trait judgments — Lorenz Weise, Verena Mainz, et al. · PLoS ONE (2024) | TGRS Research Map | TGRS