Manipulating google's knowledge graph box to counter biased information processing during an online search on vaccination: Application of a technological debiasing strategy

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Abstract

Background: One of people fs major motives for going online is the search for health-related information. Most consumers start their search with a general search engine but are unaware of the fact that its sorting and ranking criteria do not mirror information quality. This misconception can lead to distorted search outcomes, especially when the information processing is characterized by heuristic principles and resulting cognitive biases instead of a systematic elaboration. As vaccination opponents are vocal on the Web, the chance of encountering their non.evidence-based views on immunization is high. Therefore, biased information processing in this context can cause subsequent impaired judgment and decision making. A technological debiasing strategy could counter this by changing people fs search environment. Objective: This study aims at testing a technological debiasing strategy to reduce the negative effects of biased information processing when using a general search engine on people fs vaccination-related knowledge and attitudes. This strategy is to manipulate the content of Google fs knowledge graph box, which is integrated in the search interface and provides basic information about the search topic. Methods: A full 3x2 factorial, posttest-only design was employed with availability of basic factual information (comprehensible vs hardly comprehensible vs not present) as the first factor and a warning message as the second factor of experimental manipulation. Outcome variables were the evaluation of the knowledge graph box, vaccination-related knowledge, as well as beliefs and attitudes toward vaccination, as represented by three latent variables emerged from an exploratory factor analysis. Results: Two-way analysis of variance revealed a significant main effect of availability of basic information in the knowledge graph box on participants fvaccination knowledge scores (F2,273=4.86, P=.01), skepticism/fear of vaccination side effects (F2,273=3.5, P=.03), and perceived information quality (F2,273=3.73, P=.02). More specifically, respondents receiving comprehensible information appeared to be more knowledgeable, less skeptical of vaccination, and more critical of information quality compared to participants exposed to hardly comprehensible information. Although, there was no significant interaction effect between the availability of information and the presence of the warning, there was a dominant pattern in which the presence of the warning appeared to have a positive influence on the group receiving comprehensible information while the opposite was true for the groups exposed to hardly comprehensible information and no information at all. Participants evaluated the knowledge graph box as moderately to highly useful, with no significant differences among the experimental groups. Conclusion: Overall, the results suggest that comprehensible information in the knowledge graph box positively affects participants f vaccination-related knowledge and attitudes. A small change in the content retrieval procedure currently used by Google could already make a valuable difference in the pursuit of an unbiased online information search. Further research is needed to gain insights into the knowledge graph box's entire potential.

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APA

Ludolph, R., Allam, A., & Schulz, P. J. (2016). Manipulating google’s knowledge graph box to counter biased information processing during an online search on vaccination: Application of a technological debiasing strategy. Journal of Medical Internet Research, 18(6). https://doi.org/10.2196/jmir.5430

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