{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,9]],"date-time":"2026-10-09T21:49:24Z","timestamp":1791582564130,"version":"4.3.4"},"reference-count":107,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Online J Public Health Inform"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Public reporting websites have become increasingly important for improving health care transparency and supporting informed decision-making. However, little empirical evidence exists regarding whether the readability of these websites adequately meets users\u2019 information needs, particularly in the context of digital health and Finland\u2019s ongoing social welfare and health care reform.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aimed to evaluate the readability of health information on the City of Helsinki public reporting website.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cross-sectional website evaluation was conducted using the English-language health care section of the City of Helsinki public reporting website. A total of 429 web pages were collected, among which 246 unique textual descriptions were identified for readability analysis. Website text was automatically extracted using Python and evaluated using 7 established readability indexes: Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Gunning fog index (GFI), Simple Measure of Gobbledygook (SMOG), Coleman-Liau index (CLI), automated readability index (ARI), and Dale-Chall readability score (DCRS). Descriptive statistics were used to summarize textual characteristics and readability outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>All readability indexes consistently demonstrated that the website content exceeded the readability levels recommended for patient education materials. The mean FRES was 42.33 (SD 11.12), indicating difficult-to-read content. The mean FKGL score was 12.03 (SD 2.15), corresponding to a 12th-grade reading level, whereas the mean GFI score of 14.43 (SD 2.43) indicated undergraduate-level reading ability. Similar levels of linguistic complexity were observed across the SMOG (mean 13.69, SD 1.70), CLI (mean 13.61, SD 1.87), ARI (mean 13.67, SD 2.56), and DCRS (mean 11.49, SD 1.02). Considerable variability in readability across web pages suggested inconsistent linguistic accessibility within the website.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The City of Helsinki public reporting website could be improved by enhancing readability and user-centered communication. These improvements may facilitate users\u2019 understanding of health care information and support informed health care decision-making. The findings provide practical implications for the design and evaluation of future digital health care public reporting systems.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/93241","type":"journal-article","created":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T19:11:56Z","timestamp":1791486716000},"page":"e93241-e93241","source":"Crossref","is-referenced-by-count":0,"title":["The Readability of Patient-Facing Information in Public Reporting System: Cross-Sectional Evaluation of the City of Helsinki Website"],"prefix":"10.2196","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2574-6247","authenticated-orcid":false,"given":"Lanmei","family":"Du","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2169-7997","authenticated-orcid":false,"given":"Reima","family":"Suomi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,10,8]]},"reference":[{"issue":"2","key":"R1","doi-asserted-by":"publisher","first-page":"161","DOI":"10.30476\/ijcbnm.2025.106424.2761","article-title":"Digitalization in healthcare and health data reporting: opportunities to reduce error and inequality of healthcare delivery","volume":"13","author":"Cordova-Pozo","journal-title":"Int J Community Based Nurs Midwifery"},{"key":"R2","unstructured":"Cacace M Geraedts M Berger E . 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