The effects of non-diagnostic information on confidence and decision making

Kohl, Amelia T.; Sauer, James D.; Palmer, Matthew A.; Brooks, Jasmin R.; Heathcote, Andrew · 2024 · Memory & Cognition

DOI: 10.3758/s13421-024-01535-6

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Summary

This study investigates the impact of non-diagnostic information—data irrelevant to a specific choice—on decision confidence, accuracy, and response time (RT). While standard models like Signal Detection Theory and the Diffusion Decision Model largely ignore non-diagnostic inputs, Baranski and Petrusic’s (1998) doubt-scaling model predicts that such information actively reduces confidence and accuracy by triggering "guessing" processes. The authors aimed to empirically test these predictions, addressing a gap in literature where non-diagnostic information is often treated merely as noise rather than a central driver of decision dynamics. The researchers conducted two experiments using perceptual-choice tasks. In Experiment 1, participants viewed dynamic grids of flashing blue, orange, and white pixels, indicating whether the stimulus was predominantly blue or orange while rating their confidence. White pixels served as non-diagnostic information. The design manipulated the proportion of white pixels (0%, 17%, 33%, 50%) and task difficulty (easy vs. hard), using two grid types: "additive" (increasing total grid size) and "stable" (constant grid size, decreasing diagnostic pixels). Experiment 2 replicated the task without confidence ratings to isolate effects on accuracy and RT, using only the stable grid condition. Data were analyzed using linear mixed-effects models for RT and discrimination ($d'$), and Conditional Accuracy Functions (CAFs) to assess the relationship between speed and accuracy. Results from both experiments supported the doubt-scaling model. Increasing non-diagnostic information significantly reduced confidence and discrimination accuracy while generally slowing response times. Crucially, CAFs revealed a "flattening" effect: as non-diagnostic information increased, the accuracy of fast responses decreased relative to slow responses, indicating an increase in rapid guessing errors. Experiment 1 found that the stable condition produced slightly larger effects on confidence than the additive condition, suggesting absolute diagnostic amounts may play a minor role. Experiment 2 confirmed that these effects on accuracy and RT persist even when confidence judgments are removed, demonstrating that non-diagnostic information directly impairs decision quality and speed. The findings validate the doubt-scaling model’s claim that non-diagnostic information is not merely noise but a distinct factor that degrades decision performance by promoting guessing. This has significant implications for applied fields such as eyewitness identification and security screening, where stimuli often contain irrelevant features. Understanding that non-diagnostic information systematically lowers confidence and accuracy can improve the interpretation of decision reliability in real-world contexts where perfect diagnostic information is unavailable.

Key finding

Increasing the proportion of non-diagnostic information in a decision task reduces confidence and accuracy while slowing overall response times and increasing the speed of errors.

Methodology

lab_experiment

Sample size: 104

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• decision making risk perception