Master’s Thesis Presentation • Data Systems • Evaluating the Ability of Commercial Search Engines to Help People Answer Health QuestionsExport this event to calendar

Wednesday, December 13, 2023 — 12:30 PM to 1:30 PM EST

Please note: This master’s thesis presentation will take place in DC 3102.

Kamyar Ghajar, Master’s candidate
David R. Cheriton School of Computer Science

Supervisors: Professors Mark Smucker, Charles Clarke

The act of seeking information pertaining to medical treatments and self-diagnosis is one of the applications of search engines. However online documents and websites offer convenience and efficiency in accessing information, it is important to acknowledge that they may contain incorrect and also unreliable information, which can potentially lead to adverse consequences such as making harmful medical decisions. This is particularly concerning when search engine users rely solely on the information they encounter through search results, without conducting additional research or seeking guidance from qualified medical professionals. Therefore, it is essential to assess the impact of search engines on users’ behaviour and decision-making processes, especially when it comes to health-related decisions. Previous research has been conducted to evaluate the extent to which people may be affected by search engine results when they are responding to health-related questions, upon which our study is based (Pogacar et al., 2017; Ghenai et al., 2020). Their findings indicated that individuals tend to make correct decisions when supplied with a series of correct information as search results, and conversely, they tend to make wrong decisions when presented with a group of search results with incorrect information. The prior research studies used a methodology whereby study participants were presented with static search results, without the ability to actively query a search engine.

In our study, we designed and conducted a controlled laboratory study which followed a within-subject design that consisted of presenting a group of participants with 12 topics from TREC 2021 Health Misinformation track each comprising a particular health issue and its corresponding suggested medical treatment. These treatments were categorized as either helpful or unhelpful for each health issue, but the participants were not aware of the true effectiveness of each treatment. The participants were then asked to evaluate the effectiveness of the treatments both with and without utilizing the search engine experience provided to them. The search engine environment was established using modern commercial search engine APIs such as Google and Bing as its underlying infrastructure. This approach, unlike previous studies, allowed participants to directly engage with the search engine and submit their own queries to get their desired search results.

Our research revealed that search engine results have a substantial impact on individuals, both in terms of positive and negative effects. Significantly, the study participants exhibited a higher frequency of incorrect decision-making when they engaged with topics in which the treatment was not helpful towards the health issue. Furthermore, it was discovered that there existed a positive correlation between the participants’ level of prior knowledge of health issues and treatments, and their performance in making decisions. We also found that even though the participants used a fully interactive search engine, interaction alone was not sufficient for participants to avoid being negatively influenced by the search engine on some search topics.

Location 
DC - William G. Davis Computer Research Centre
DC 3102
200 University Avenue West

Waterloo, ON N2L 3G1
Canada
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