Mental effort in binary categorization aided by binary cues

Assaf Botzer, Joachim Meyer, Yisrael Parmet

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Binary cueing systems assist in many tasks, often alerting people about potential hazards (such as alarms and alerts). We investigate whether cues, besides possibly improving decision accuracy, also affect the effort users invest in tasks and whether the required effort in tasks affects the responses to cues. We developed a novel experimental tool to study binary categorization performance. In two experiments, participants decided whether items on a screen were intact or faulty, based on the configuration of lighter and darker areas in items. Cues were available in half of the experimental blocks, and participants could use them in their decisions. Experimental conditions differed in the effort required to perform the task, manipulated through the contrast between lighter and darker areas (higher contrast vs. lower contrast), and in the validity of cues (medium vs. high validity). In the NASA-TLX, participants reported that with highly valid cues, they invested less effort in the task, whereas with medium validity cues, they invested similar effort as without cues. Responses to the high-validity cues were stronger than responses to the medium-validity cues. The required effort in the task did not affect the strength of responses to cues. We conclude that the invested effort may decrease when cues are available, but users will not rely more strongly on cues in more demanding situations to reduce the invested effort. We therefore recommend integrating cues into work environments, as they reduce users' effort without necessarily leading to overdependence on the cues to reduce invested effort. copy; 2013 American Psychological Association.

Original languageEnglish
Pages (from-to)39-54
Number of pages16
JournalJournal of Experimental Psychology: Applied
Volume19
Issue number1
DOIs
StatePublished - 1 Mar 2013

Keywords

  • Alerts
  • Binary categorization
  • Binary cues
  • Detection
  • Mental effort

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