Trial reportJournal of medical Internet research2014
Confirmation bias in web-based search: a randomized online study on the effects of expert information and social tags on information search and evaluation.
Trial report in Journal of medical Internet research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 32 citations in OpenAlex.
- How Confidence in Prior Attitudes, Social Tag Popularity, and Source Credibility Shape Confirmation Bias Toward Antidepressants and Psychotherapy in a Representative German Sample: Randomized Controlled Web-Based Study.Journal of medical Internet research · 2019Trial
- Generative artificial intelligence-mediated confirmation bias in health information seeking.Annals of the New York Academy of Sciences · 2025Review
- Coconut oil: an overview of cardiometabolic effects and the public health burden of misinformation.Archives of endocrinology and metabolism · 2023Review
- When freedom of choice leads to bias: How threat fosters selective exposure to health information.Frontiers in psychology · 2022Article
- Characterizing the Influence of Confirmation Bias on Web Search Behavior.Frontiers in psychology · 2021Article
- When Similarity Beats Expertise-Differential Effects of Patient and Expert Ratings on Physician Choice: Field and Experimental Study.Journal of medical Internet research · 2019Article
- Article
- Web-based textual analysis of free-text patient experience comments from a survey in primary care.JMIR medical informatics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
objectiveThe 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.
methodsA 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.
resultsParticipants 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).
conclusionsWe 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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.