{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T22:10:47Z","timestamp":1792793447581,"version":"4.5.0"},"reference-count":138,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,8,10]],"date-time":"2025-08-10T00:00:00Z","timestamp":1754784000000},"content-version":"vor","delay-in-days":221,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"BMBF and the Max Planck Society","id":[{"id":"https:\/\/ror.org\/01hhn8329","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,1,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Medical information avoidance\u2014the prevention or delay of acquiring health-related information\u2014is a growing concern for physicians, healthcare professionals, and policymakers. Yet, its prevalence and predictors have remained poorly understood.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We 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-\u00adeffects and mixed-effects models.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A 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\u2019s disease, and 41% for Alzheimer\u2019s 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\u2009=\u20090.26), perceived stigma (r\u2009=\u20090.36), self-efficacy (r\u2009=\u2009\u22120.28), and trust in the medical system (r\u2009=\u2009\u22120.25).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Nearly 1 in 3 participants avoided or were likely to avoid medical information. The highest prevalence rates were found for Huntington\u2019s disease and Alzheimer\u2019s disease, 2 incurable neurodegenerative diseases. Key cognitive predictors suggest entry points for policy interventions and future research.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Lay Summary<\/jats:title>\n                    <jats:p>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\u2019s disease: 41%, Huntington\u2019s 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\u2019s 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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/abm\/kaaf058","type":"journal-article","created":{"date-parts":[[2025,6,16]],"date-time":"2025-06-16T07:25:55Z","timestamp":1750058755000},"source":"Crossref","is-referenced-by-count":10,"title":["Prevalence and predictors of medical information avoidance: a systematic review and meta-analysis"],"prefix":"10.1093","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5488-1312","authenticated-orcid":false,"given":"Konstantin","family":"Offer","sequence":"first","affiliation":[{"name":"Center for Adaptive Rationality (ARC), Max Planck Institute for Human Development , 14195 Berlin,","place":["Germany"]},{"name":"Max Planck School of Cognition , 04103 Leipzig,","place":["Germany"]},{"name":"Department of Psychology, Humboldt-Universit\u00e4t zu Berlin , 10099 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