{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T21:13:05Z","timestamp":1788642785304,"version":"build-2803163510"},"reference-count":33,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Infodemiology"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The COVID-19 pandemic highlighted the importance of effective health communication and reliable information for crisis management, particularly following the introduction of vaccinations. Varied attitudes toward COVID-19 vaccination and an overwhelming amount of online information complicated communication and pandemic management. Previous studies have often focused on general vaccination behavior and its correlation with vaccination attitudes, establishing a link between information-seeking and vaccination decisions. However, there is insufficient analysis distinguishing specific user groups based on their actual online information behavior regarding COVID-19 vaccination and examining its correlation with vaccination behavior.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to fill this research gap by identifying user groups based on their information behavior and investigating its influence on vaccination uptake.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>As part of the \u201cInternetnutzung zur COVID-19-Impfung\u201d (INCOVI) study, 1000 individuals in Germany were surveyed online (November 26 to December 8, 2021) regarding their internet usage related to COVID-19 vaccination. A hierarchical cluster analysis was conducted to identify user groups. Logistic regression analyses were then used to explore correlations among the user groups and their demographic characteristics, readiness to vaccinate, knowledge of vaccination, and health literacy. Additionally, a logistic regression analysis was performed to identify the influence of user groups and other factors on vaccination behavior.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 3 user groups were identified: frequent and critical information evaluators (454\/778, 58.4%), who primarily relied on official information sources, exhibited a higher level of health literacy, and were older than the other groups; infrequent and passive recipients (222\/778, 28.5%), who rarely sought information actively and were younger than the other groups; and frequent and multichannel, interaction-focused users (102\/778, 13.1%), who actively searched across multiple channels and engaged in information exchange. Notably, the user groups did not significantly differ in knowledge or willingness to vaccinate. User group affiliation, knowledge, and health literacy did not significantly influence vaccination behavior. The strongest predictor of vaccination was preexisting willingness to vaccinate. Additionally, women were more likely to be vaccinated than men, and individuals with medium or higher education levels were 6-11 times more likely to be vaccinated compared to those with only a basic level of education.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Segmenting the population into different user groups allows for more targeted communication tailored to the specific needs and beliefs of each group. Because these groups stem from observable usage patterns, they constitute a transferable framework for other health topics. For frequent and critical information evaluators, providing well-founded and detailed information on public channels is important. Infrequent and passive recipients benefit from straightforward formats, such as short explanatory videos, while frequent and multichannel, interaction-focused users are better reached through interactive offerings on social media. By specifically targeting these groups, informed decision-making about vaccinations can be supported.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/82221","type":"journal-article","created":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:30:08Z","timestamp":1773415808000},"page":"e82221","source":"Crossref","is-referenced-by-count":1,"title":["Online Information Behavior Regarding COVID-19 Vaccination and Its Association With Vaccination Behavior Based on Cluster Analysis of User Groups: Cross-Sectional Study"],"prefix":"10.2196","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-4606-4223","authenticated-orcid":false,"given":"Lea","family":"Liebner","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8722-3332","authenticated-orcid":false,"given":"Birgit","family":"Babitsch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6063-3983","authenticated-orcid":false,"given":"Lisa","family":"Schmidt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,5,29]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s10389-023-01827-2"},{"key":"ref2","unstructured":"Federal Ministry of HealthVaccinations2025https:\/\/www.bundesgesundheitsministerium.de\/en\/topics\/vaccinations.html"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3238\/arztebl.m2022.0174"},{"key":"ref4","unstructured":"Robert Koch-InstitutBundeszentrale f\u00fcr gesundheitliche Aufkl\u00e4rungLeibniz-Zentrum f\u00fcr Psychologische Information und DokumentationScience Media CenterBernhard Nocht Institute for Tropical MedicineYale Institute for Global HealthCOSMO explorer: impfbereitschaft (mit Geimpften)COSMOhttps:\/\/projekte.uni-erfurt.de\/cosmo2020\/web\/explorer\/"},{"key":"ref5","unstructured":"Robert Koch InstitutCOVID-19-impfungen in Deutschlandhttps:\/\/robert-koch-institut.github.io\/COVID-19-Impfungen_in_Deutschland\/"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1038\/s43856-022-00176-7"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1027\/1015-5759\/a000663"},{"key":"ref8","first-page":"117","author":"Baumann, E","year":"2006","journal-title":"Gesundheitsmonitor 2006. 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