比較大眾意見與專家意見對於降低健康資訊之確認偏誤的效果

Abstract

確認偏誤是一種資訊尋求者在找資訊時傾向找尋符合自己原先立場資訊之行為，它可能會阻礙消費者健康資訊尋求行為並導致錯誤的決策。前人研究顯示，透過系統推薦對立立場的資訊給使用者，可以降低他們的確認偏誤。本實驗探討專家推薦系統與大眾推薦系統降低確認偏誤的效果，並在選擇階段、評估階段和最終決策階段分別測量確認偏誤的大小。本實驗招募了 78 位 40 到 70 歲的受測者。受測者只被告知他們參加的是針對兩個癌症篩檢議題的健康資訊實驗。實驗設計讓受測者在兩個不同篩檢議題下會使用到兩個不同的推薦系統。實驗結果發現和選擇偏誤相比，評估偏誤和最終決策偏誤較難被抵銷。在降低選擇偏誤上，專家推薦系統比大眾推薦系統效果更好。此外，專家推薦系統對高涉入感的議題影響力也較佳。本實驗亦發現面對健康資訊議題，樣本存在性別差異。未來研究降低確認偏誤的研究者應視性別為一項干擾變項並選擇大眾認知程度相近的健康議題作為實驗材料，方能達到更準確的研究成果。

Confirmation bias, the preferential seeking of confirmatory information, can become an obstacle for the disseminate of valid health information online and lead to biased decision. Following previous findings, preference-inconsistent recommendation can be used to overcome this bias. We conducted an experiment to study the impact of expert system and popularity system on mitigating confirmation bias, the confirmation bias was measured in the selection phase, the evaluation phase and the final decision phases. 78 participants aged 40-70 were recruited. Participants were informed that they would participate in a health information experiment involving two cancer screening debates. Participants were assigned in such a way that each participant would see two fairly different interfaces for the two tasks. We found that the evaluation bias and the final decision were more persistent than the selection bias. The comparison between the two systems revealed that expert system has a better mitigation effect than the popularity system in the selection bias. Furthermore, it was observed that expert system would have better mitigation effect on high-involvement issue. We also found strong gender difference in our experiment. Future study which aims to investigate the mitigation effect of different techniques should take gender as a confounding variable and choose health issues which are more comparable.