Decision dynamics and human-computer interaction in consumer online health information seeking: A behavioral information research (BIR) exploration
Abstract
According to the dual-processing theory, humans deviate from rational decision-making due to the intuitive cognitive heuristics. Online health information seeking (OHIS) entails critical implications for health. This study aims to understand the dynamics of cognitive biases and achieve debiasing through human-computer interaction (HCI) designs to enable better decision-making in OHIS. Preliminary findings identified 40 empirical research articles containing 56 studies on cognitive biases in consumer OHIS from 1995 to 2019 with 75% of the articles published in the last decade. Optimistic bias and confirmation bias are the most studied cognitive biases out of the 16 biases identified. Behavioral economist Daniel Kahneman has the most theoretical presence, while more recent behavioral economic insights such as nudge are not present. In terms of health topics, 35% of studies addressed specific diseases and illness, while 17.5% addressed consumer health issues such as food and nutrition.
Recommended Citation
Chen, T. (2020). Decision dynamics and human-computer interaction in consumer online health information seeking: A behavioral information research (BIR) exploration. ALISE 2020 Annual Conference ALISE 2020 Annual Conference.
Department(s)
Business and Information Technology
Keywords and Phrases
health information seeking; cognitive bias; decision-making; behavioral information research; online experiment
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 The Author, All rights reserved.
Publication Date
2020-10-21