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Participants prefer decision support (DS) when information is uncertain and integrate it effectively when visual cues are combined. Binary cues are better than likelihood cues when integration is not possible.

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Area of Science:

  • Human-Computer Interaction
  • Cognitive Psychology
  • Decision Science

Background:

  • Decision support (DS) systems can influence decision accuracy, performance time, and workload.
  • Selective access to DS based on informational needs may enhance its effectiveness.

Purpose of the Study:

  • To investigate how event uncertainty, DS display format, and DS sensitivity impact user behavior, performance, and perception.
  • To analyze user interaction with DS in a classification task under varying conditions.

Main Methods:

  • Participants performed a sensory classification task with trial-by-trial DS access.
  • DS was presented in separated-binary (SB), separated-likelihood (SL), or integrated-likelihood (IL) formats.
  • Recorded data included access preferences, task performance, time, workload, and perceived DS usefulness/performance.

Main Results:

  • DS was accessed more frequently with higher sensitivity, greater stimulus uncertainty, or perceptual integration of DS cues and stimulus information.
  • The integrated likelihood (IL) DS format yielded the highest effective sensitivity.
  • Separated likelihood (SL) DS was accessed less often than binary likelihood DS, resulting in lower sensitivity despite providing more information.

Conclusions:

  • Users are more likely to access DS when raw stimulus information is highly uncertain.
  • Effective use of likelihood DS is dependent on perceptual integration with raw stimulus information.
  • When integration is not feasible, binary DS cues are more effective than likelihood cues.