2026-10-10T23:45:04Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33966923 2026-09-22T17:25:27Z category_21 category_46 category_931 category_64 category_106 category_122 portal_5 item_type_3 month_year_09_2026

<p>Risk of bias of quantitative descriptive studies (mixed methods appraisal tool category 4).</p> Rocco Sheldon (24549748) Morya Wadodkar (24549751) Andrew Gan (24549754) Rachael Yip (25091168) Yimeng Zhang (283704) Jyoti Baharani (3584696) Biotechnology Immunology Information Systems not elsewhere classified Cancer Science Policy Mental Health small sample sizes primary outcomes due one study reported large language models information fidelity ranging grade appraisal tool effectiveness remains fragmented drafting time compared 1 november 2025 findings regarding readability tactless patient descriptions authored control group outpatient clinic letters five using synthetic concerns regarding accuracy world clinic data providing insufficient evidence assessed quality using limiting patient comprehension studies evaluating ai world patient authored letters evidence regarding certainty using measured patient five databases extracted data clinical accuracy simplified letters two studies studies relied seven studies widespread adoption systematic review subjective measures scalable tools prospero registration overall certainty mmat ), methodological limitations low across improvement settings hypothetical scenarios generalisability remain fold reduction clinical communication centred research artificial intelligence <p>Risk of bias of quantitative descriptive studies (mixed methods appraisal tool category 4).</p> 2026-09-22T17:25:16Z Dataset Dataset 10.1371/journal.pdig.0001745.t003 https://figshare.com/articles/dataset/_p_Risk_of_bias_of_quantitative_descriptive_studies_mixed_methods_appraisal_tool_category_4_p_/33966923 CC BY 4.0