Information Avoidance: a Systematic Review

The aim of this study is to understand the concept of information avoidance in terms of origin, effective factors, behaviors, areas of the previous studies, and research gaps. This research was conducted by systematic review method using Kitchenham and Charters (2007) framework. By reviewing internal and external databases and studying the abstracts of retrieved articles with related keywords, 65 related articles were identified and after refinement, 49 related articles were reviewed without time limitation. After studying the articles related to information avoidance, and using the content analysis approach, the contents were categorized into several thematic categories and the questions were answered according to the aims of the research. The findings suggest that the origins of information avoidance could be traced back to theories such as cognitive dissonance theory of Festinger (1957), uncertainty reduction theory of Gudykunst (1985), and models such as Johnson’s (1997) and Wilson’s (1999). The most important factors influencing information avoidance could be classified into two categories of Hedonic and Strategic factors. The factors of hedonic category are preferences for resolution of compound lotteries, risk, loss, and disappointment aversion, anxiety, attention, regret aversion, optimism maintenance, dissonance avoidance, and belief investments. Strategic factors also fall into two categories: intrapersonal strategic avoidance (avoiding dynamic inconsistency, resisting temptation, motivation maintenance, avoiding projection biases, abdicating responsibility and saving it for later) and interpersonal strategic avoidance (avoiding spoiling information about themselves or receiving information about others, which causes a change in their attitudes toward them). Information avoidance behaviors are then introduced which include physical avoidance, inattention, biased interpretation of information, forgetting, and self-handicapping. Also, the contexts in which information avoidance has been discussed so far include health, risk information, social and news media, emotional relationships, and smoking, using common information avoidance assessment tools such as questionnaires, interviews, modeling, laboratory observation, and task defining are investigated. Finally, two of the important research gaps in this field are the lack of a comprehensive model for information avoidance that is responsive to any society and any problem, and the need to pay more attention to information avoidance in the field of knowledge and information science.