{"paper_id":"dfcee830-55f8-4804-b861-3acfe9280eb5","body_text":"Previously submitted to: Journal of Medical Internet Research (no longer under consideration since Aug 22, 2024)\nDate Submitted: May 16, 2023\nOpen Peer Review Period: May 16, 2023 - Jul 11, 2023\n(closed for review but you can still tweet)\nNOTE: This is an unreviewed Preprint\nWarning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note \"no longer under consideration\" will appear above).\nPeer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a \"Peer Review Me\" button to sign up as reviewer is displayed above). 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Preprints - unless they show as \"accepted\" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.\nThe use of infodemiology in the development of targeted public health actions on endometriosis in France: a mixed & patient-centric methodology\nABSTRACT\nBackground:\nEndometriosis is a chronic gynaecological disease of women of reproductive age linked to menstruation and the hormones that trigger it. The symptoms of endometriosis have a major impact on women’s quality of life, either on a psychological level or on a societal one. Today, as many other female-specific topics, endometriosis is under-researched and under-diagnosed and many causes remain unknown. Although literature suggests that endometriosis patients are prone to use social network as a self-management tool and discuss various topics related to their disease, very few papers applied infodemiological (epidemiology based on internet health-related content) methods to endometriosis.\nObjective:\nThe main objective of this study is to understand whether infodemiology could be useful for public health decision makers in the management of patients with endometriosis and to prove it to be a reliable study methodology.\nMethods:\nFirstly, social media post were collected between January 2020 and 2022 from France geolocalized sites using keyword for endometriosis. Automatic natural language processing methods were used to identify relevant patients with endometriosis posts expressing difficulties and unmet needs. Then, semi-structured interviews were conducted during July 2022 with 9 women with endometriosis and healthcare professionals. Discussions were recorded and transcribed verbatims were analysed through a thematic analysis allowing to generate general statistics on the most discussed topics.\nResults:\nA total of 2,396 written by 1,742 patients with endometriosis were included. 2,317 (96.70%) were identified as containing at least one difficulty. The top 3 unmet needs and difficulties were difficulties present throughout the care pathway (71.1%; n = 1701), pathology-related (57.2%; n = 1,356) and treatments and medical procedures (20.6 %; n = 492). Semi-structured interviews show that the top 3 main difficulties for patients with endometriosis were difficulties related to treatments (30% of the detected medical concepts), impact of the disease on the patient's environment (29% of the concepts) and transversal difficulties (16% of the concepts).\nConclusions:\nThe bi-patient-centric approach with limited manual work allows to identify difficulties encountered by patients with endometriosis in France. The mixed-methodology of this study appears ideal to demonstrate their complementarity and to justify the use of AI algorithms for public health decision-making. Furthermore, endometriosis is a disease affecting a wide range of women, each with their own specific difficulties. They now expect societal and medical recognition of their illness and care pathways adapted to their individual symptoms.\nCitation\nRequest queued. Please wait while the file is being generated. It may take some time.\nCopyright\n© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.","source_license":"CC0","license_restricted":false}