{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T01:44:39Z","timestamp":1792806279436,"version":"4.5.0"},"reference-count":31,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T00:00:00Z","timestamp":1792713600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T00:00:00Z","timestamp":1792713600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["ANZ Journal of Surgery"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Consent forms often exceed the reading ability of populations they serve. Large language models may improve accessibility of patient\u2010facing information, but existing research has predominantly assessed de novo generation, with limited benefit. AI\u2010assisted simplification of existing, clinically validated material represents a distinct workflow that remains underexplored. This study compared the readability of all 64 consent forms published by NHS England's Getting it right first time (GIRFT) with matched de novo AI\u2010generated and AI\u2010simplified versions across six surgical specialties.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>For each procedure, two AI counterparts were produced using Claude Opus 4.8 with standardised prompts: a de novo AI\u2010generated form and an AI\u2010simplified version derived from the original (192 documents across three paired arms). Readability was assessed using five validated metrics, Flesch reading ease (FRE) and word count. Primary outcomes were average reading age (RA) and grade level (GL). Achievement of the nationally recommended RA (\u2264\u200911\u2009years) was also assessed.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Original GIRFT forms required a mean RA of 16.39\u2009\u00b1\u20090.85\u2009years. AI\u2010generated forms were harder to read (17.65\u2009\u00b1\u20090.73\u2009years,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), whereas AI\u2010simplified forms were easier (13.27\u2009\u00b1\u20090.67\u2009years,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). No form achieved a RA\u2009\u2264\u200911\u2009years. FRE\u2009\u2265\u200950 was achieved by 100% of AI\u2010simplified, 45.3% of originals and 15.6% of AI\u2010generated forms.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>De novo AI\u2010generation reduced readability relative to nationally standardised consent forms, whereas AI\u2010simplification improved readability. Neither approach achieved the recommended reading age. AI may therefore have a role in improving the accessibility of existing consent forms, but outputs require objective readability assessment and clinical validation before implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/ans.71030","type":"journal-article","created":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T01:14:52Z","timestamp":1792804492000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Readability of National Surgical Consent Forms: Artificial Intelligence Generation Versus Simplification"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7936-2715","authenticated-orcid":false,"given":"Nasir","family":"Kharma","sequence":"first","affiliation":[{"name":"King's College Hospital NHS Foundation Trust  London UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,23]]},"reference":[{"key":"e_1_2_11_2_1","volume-title":"Informed Consent","author":"Royal Australasian College of Surgeons","year":"2019"},{"key":"e_1_2_11_3_1","volume-title":"Informed Consent: Helping Patients Make Informed Decision About Their Care","author":"Medical Council of New Zealand","year":"2021"},{"key":"e_1_2_11_4_1","volume-title":"Montgomery v Lanarkshire Health Board","year":"2015"},{"key":"e_1_2_11_5_1","volume-title":"Decision Making and Consent","author":"General Medical Council","year":"2020"},{"issue":"635","key":"e_1_2_11_6_1","doi-asserted-by":"crossref","first-page":"e379","DOI":"10.3399\/bjgp15X685285","article-title":"A Mismatch Between Population Health Literacy and the Complexity of Health Information: An Observational Study","volume":"65","author":"Rowlands G.","year":"2015","journal-title":"British Journal of General Practice"},{"key":"e_1_2_11_7_1","volume-title":"How We Write\u2014NHS Digital Service Manual","author":"NHS England","year":"2019"},{"issue":"7","key":"e_1_2_11_8_1","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1093\/ced\/llad461","article-title":"Artificial Intelligence\u2010Generated Patient Information Leaflets: A Comparison of Contents According to British Association of Dermatologists Standards","volume":"49","author":"Verran C.","year":"2024","journal-title":"Clinical and Experimental Dermatology"},{"issue":"12","key":"e_1_2_11_9_1","article-title":"A Study of Orthopedic Patient Leaflets and Readability of AI\u2010Generated Text in Foot and Ankle Surgery (SOLE\u2010AI)","volume":"16","author":"Jaques A.","year":"2024","journal-title":"Cureus"},{"issue":"4","key":"e_1_2_11_10_1","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1055\/a-2413-3675","article-title":"Assessing the Quality and Readability of Online Patient Information: ENT UK Patient Information e\u2010Leaflets Versus Responses by a Generative Artificial Intelligence","volume":"41","author":"Shamil E.","year":"2025","journal-title":"Facial Plastic Surgery"},{"issue":"12","key":"e_1_2_11_11_1","doi-asserted-by":"crossref","first-page":"2549","DOI":"10.1111\/ans.16362","article-title":"Readability of Foot and Ankle Consent Forms in Queensland","volume":"90","author":"Pastore G.","year":"2020","journal-title":"ANZ Journal of Surgery"},{"issue":"7","key":"e_1_2_11_12_1","doi-asserted-by":"crossref","first-page":"1831","DOI":"10.1111\/ans.17781","article-title":"Poor Compliance Documenting Informed Consent in Trauma Patients With Distal Radius Fractures Compared to Elective Total Knee Arthroplasty","volume":"92","author":"Bolam S. M.","year":"2022","journal-title":"ANZ Journal of Surgery"},{"key":"e_1_2_11_13_1","volume-title":"Getting It Right First Time\u2014What We Do: Getting It Right First Time (GIRFT)","author":"NHS England","year":"2026"},{"key":"e_1_2_11_14_1","volume-title":"Standardised Consent Forms for High Volume, Low Complexity Procedures: Getting It Right First Time (GIRFT)","author":"NHS England","year":"2026"},{"key":"e_1_2_11_15_1","volume-title":"Introducing Claude Opus 4.8","author":"Anthropic","year":"2026"},{"key":"e_1_2_11_16_1","volume-title":"Readability Studio","year":"2024"},{"issue":"3","key":"e_1_2_11_17_1","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1037\/h0057532","article-title":"A New Readability Yardstick","volume":"32","author":"Flesch R.","year":"1948","journal-title":"Journal of Applied Psychology"},{"issue":"2","key":"e_1_2_11_18_1","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","article-title":"A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research","volume":"15","author":"Koo T. 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