Demand characteristics in human–computer experiments

Olga Iarygina*, Kasper Hornbæk, Aske Mottelson

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Demand characteristics refer to cues that can inform participants in experiments about the hypothesis and influence their behavior. They lead researchers to erroneously infer non-existing effects, undermining the experimental integrity of empirical studies. Despite a widespread acknowledgment of their confounding influence in experimental psychology, experiments involving humans and computers to a lesser extent consider effects of demand characteristics, as computerized protocols are thought to be immune to some experimenter biases. Furthermore, demand characteristics are considered to mainly effect subjective measures. As a result, demand characteristics often remain uncontrolled in studies involving computers, and in particular for objective measures such as performance. In this paper, we present two experiments that underline the importance of demand characteristics in human–computer interaction experiments. In a text-entry study, we made participants believe they were evaluating a research-based keyboard. This belief led to increased performance and self-reported user experience. In a second study, we conducted a thought experiment on the illusion of body ownership in virtual reality, where the experimental design indicated the study hypothesis. We found hypothesis-compliant responses from participants, even when they did not experience the illusion. We conclude that demand characteristics pose a significant challenge to the interpretation and validity of human–computer experiments, even when they are fully automated. We discuss the implications and offer guidelines to mitigate effects of demand characteristics.

Original languageEnglish
Article number103379
JournalInternational Journal of Human Computer Studies
Volume193
Number of pages14
ISSN1071-5819
DOIs
Publication statusPublished - Jan 2025

Bibliographical note

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Keywords

  • Bias
  • Confounds
  • Demand characteristics
  • Experiments
  • Human–computer interaction
  • Validity

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