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Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information and Social Tags on Information Search and Evaluation

机译:基于Web的搜索中的确认偏差:专家信息和社会标签对信息搜索和评估影响的随机在线研究

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Background: The public typically believes psychotherapy to be more effective than pharmacotherapy for depression treatments. This is not consistent with current scientific evidence, which shows that both types of treatment are about equally effective.Objective: The study investigates whether this bias towards psychotherapy guides online information search and whether the bias can be reduced by explicitly providing expert information (in a blog entry) and by providing tag clouds that implicitly reveal experts’ evaluations.Methods: A total of 174 participants completed a fully automated Web-based study after we invited them via mailing lists. First, participants read two blog posts by experts that either challenged or supported the bias towards psychotherapy. Subsequently, participants searched for information about depression treatment in an online environment that provided more experts’ blog posts about the effectiveness of treatments based on alleged research findings. These blogs were organized in a tag cloud; both psychotherapy tags and pharmacotherapy tags were popular. We measured tag and blog post selection, efficacy ratings of the presented treatments, and participants’ treatment recommendation after information search.Results: Participants demonstrated a clear bias towards psychotherapy (mean 4.53, SD 1.99) compared to pharmacotherapy (mean 2.73, SD 2.41; t173=7.67, P<.001, d=0.81) when rating treatment efficacy prior to the experiment. Accordingly, participants exhibited biased information search and evaluation. This bias was significantly reduced, however, when participants were exposed to tag clouds with challenging popular tags. Participants facing popular tags challenging their bias (n=61) showed significantly less biased tag selection (F2,168=10.61, P<.001, partial eta squared=0.112), blog post selection (F2,168=6.55, P=.002, partial eta squared=0.072), and treatment efficacy ratings (F2,168=8.48, P<.001, partial eta squared=0.092), compared to bias-supporting tag clouds (n=56) and balanced tag clouds (n=57). Challenging (n=93) explicit expert information as presented in blog posts, compared to supporting expert information (n=81), decreased the bias in information search with regard to blog post selection (F1,168=4.32, P=.04, partial eta squared=0.025). No significant effects were found for treatment recommendation (Ps>.33).Conclusions: We conclude that the psychotherapy bias is most effectively attenuated—and even eliminated—when popular tags implicitly point to blog posts that challenge the widespread view. Explicit expert information (in a blog entry) was less successful in reducing biased information search and evaluation. Since tag clouds have the potential to counter biased information processing, we recommend their insertion.
机译:背景:公众通常认为心理疗法比药物疗法对抑郁症治疗更为有效。这与当前的科学证据不一致,后者表明两种治疗方法都差不多有效。目的:本研究调查这种对心理疗法的偏见是否可以指导在线信息搜索,以及是否可以通过明确提供专家信息来减少偏见(在方法:在我们通过邮件列表邀请他们之后,共有174名参与者完成了基于Web的全自动研究,从而隐瞒了专家的评价。首先,参与者阅读了专家的两篇博客文章,这些文章挑战或支持心理疗法的偏见。随后,参与者在网上环境中搜索有关抑郁症治疗的信息,该网络基于所谓的研究发现提供了更多专家关于治疗效果的博客文章。这些博客是在标签云中组织的;心理治疗标签和药物治疗标签均很受欢迎。在信息搜索后,我们测量了标签和博客文章的选择,所提出治疗的功效等级以及参与者的治疗建议。结果:与药物治疗(平均2.73,SD 2.41)相比,参与者表现出明显的心理疗法偏倚(平均4.53,SD 1.99)。在实验前对治疗效果进行评估时,t173 = 7.67,P <.001,d = 0.81)。因此,参与者表现出有偏见的信息搜索和评估。但是,当参与者暴露于具有挑战性的流行标签的标签云时,这种偏见被大大降低。面对颇具挑战性的标签挑战其偏见(n = 61)的参与者显示出偏见的标签选择(F2,168 = 10.61,P <.001,部分eta平方= 0.112),博客帖子选择(F2,168 = 6.55,P =)明显更少。与偏倚支持标签云(n = 56)和平衡标签云(n = 56)相比,002,部分eta平方= 0.072)和治疗功效等级(F2,168 = 8.48,P <.001,部分eta平方= 0.092) = 57)。与支持专家信息(n = 81)相比,挑战(n = 93)博客帖子中呈现的显式专家信息,可以减少信息搜索中有关博客帖子选择的偏见(F1,168 = 4.32,P = .04,部分eta平方= 0.025)。没有推荐治疗的显着效果(Ps> .33)。结论:我们得出结论,当流行标签隐含指向挑战普遍观点的博客帖子时,心理疗法偏见可以最有效地减轻甚至消除。显式的专家信息(在博客文章中)在减少有偏见的信息搜索和评估方面不太成功。由于标签云有可能抵消有偏见的信息处理,因此我们建议插入它们。

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