Evidence map›Paper›PMID 40795090›Full record

SynthesisAnnals of behavioral medicine : a publication of the Society of Behavioral Medicine2025

Prevalence and predictors of medical information avoidance: a systematic review and meta-analysis.

Konstantin Offer, Natalia Oglanova, Lisa Oswald, Ralph Hertwig

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Annals of behavioral medicine : a publication of the Society of Behavioral Medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Konstantin OfferCenter for Adaptive Rationality (ARC), Max Planck Institute for Human Development, 14195 Berlin, Germany.ORCID 0000-0002-5488-1312
Natalia OglanovaDepartment of Psychology, The University of Potsdam, 14476 Potsdam, Germany.
Lisa OswaldCenter for Adaptive Rationality (ARC), Max Planck Institute for Human Development, 14195 Berlin, Germany.ORCID 0000-0002-8418-282X
Ralph HertwigCenter for Adaptive Rationality (ARC), Max Planck Institute for Human Development, 14195 Berlin, Germany.ORCID 0000-0002-9908-9556

Funding

BMBF and the Max Planck Society
6 · The paper itself

Abstract

backgroundMedical information avoidance-the prevention or delay of acquiring health-related information-is a growing concern for physicians, healthcare professionals, and policymakers. Yet, its prevalence and predictors have remained poorly understood. PURPOSE: We conducted a systematic review and meta-analysis to clarify the prevalence and predictors of medical information avoidance, offering key insights into the worldwide empirical evidence.

methodsWe performed a systematic search, preregistered on the OSF and in accordance with PRISMA and MOOSE reporting guidelines. Additional individual participant datasets were obtained from the National Institutes of Health (NIH). Data analysis was performed using random--effects and mixed-effects models.

resultsA total of 92 studies and 6 individual participant datasets (564 497 unique participants, 25 countries) were analyzed. We found that almost 1 in 3 participants avoided or were likely to avoid information. Specifically, we estimated prevalence rates of 24% for diabetes, 29% for cancer, 32% for HIV, 40% for Huntington's disease, and 41% for Alzheimer's disease. We did not find any reliable association with gender or with race and ethnicity. Instead, we identified 16 significant predictors across cognitive, health-related, and sociodemographic domains. The strongest predictors were all cognitive: information overload (r = 0.26), perceived stigma (r = 0.36), self-efficacy (r = -0.28), and trust in the medical system (r = -0.25).

conclusionsNearly 1 in 3 participants avoided or were likely to avoid medical information. The highest prevalence rates were found for Huntington's disease and Alzheimer's disease, 2 incurable neurodegenerative diseases. Key cognitive predictors suggest entry points for policy interventions and future research. LAY SUMMARY: Medical information is more accessible than ever, but many people choose to avoid it. How common is this behavior, and what predicts it? To find out, we analyzed data from over 90 studies involving more than half a million people across 25 countries. We found that nearly 1 in 3 people avoided or were likely to avoid medical information. Avoidance was highest for incurable neurodegenerative diseases (Alzheimer's disease: 41%, Huntington's disease: 40%), moderate for severe but treatable conditions (HIV: 32%, cancer: 29%), and lowest for a chronic, manageable illness (diabetes: 24%). We identified 16 key predictors of medical information avoidance. Surprisingly, gender, race, and ethnicity were not among them. Instead, the strongest predictors were cognitive and emotional: mistrust in the medical system, feeling overwhelmed, low confidence in managing one's health, and fear of being judged. Patterns of avoidance varied across world regions, suggesting that differences in healthcare systems may influence behavior. In this study, we do not judge whether medical information avoidance is good or bad. Instead, we offer the first comprehensive review of how common it is and what predicts it. More research is needed to understand the psychological and medical consequences of avoiding medical information.

Indexed as

Information Seeking BehaviorHumansPrevalencehealth behaviormedical information avoidancemeta-analysispredictorsprevalencesystematic review

Identifiers

PMID40795090
PMCPMC12342947

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Registered trials

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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.