Published on in Vol 7, No 3 (2020): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19713, first published .
Patients’ Utilization and Perception of an Artificial Intelligence–Based Symptom Assessment and Advice Technology in a British Primary Care Waiting Room: Exploratory Pilot Study

Patients’ Utilization and Perception of an Artificial Intelligence–Based Symptom Assessment and Advice Technology in a British Primary Care Waiting Room: Exploratory Pilot Study

Patients’ Utilization and Perception of an Artificial Intelligence–Based Symptom Assessment and Advice Technology in a British Primary Care Waiting Room: Exploratory Pilot Study

Journals

  1. Aboueid S, Meyer S, Wallace J, Mahajan S, Chaurasia A. Young Adults’ Perspectives on the Use of Symptom Checkers for Self-Triage and Self-Diagnosis: Qualitative Study. JMIR Public Health and Surveillance 2021;7(1):e22637 View
  2. Kühnle L, Mücke U, Lechner W, Klawonn F, Grigull L. Development of a Social Network for People Without a Diagnosis (RarePairs): Evaluation Study. Journal of Medical Internet Research 2020;22(9):e21849 View
  3. Faqar-Uz-Zaman S, Filmann N, Mahkovic D, von Wagner M, Detemble C, Kippke U, Marschall U, Anantharajah L, Baumartz P, Sobotta P, Bechstein W, Schnitzbauer A. Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial. BMJ Open 2021;11(1):e041396 View
  4. Knitza J, Mohn J, Bergmann C, Kampylafka E, Hagen M, Bohr D, Morf H, Araujo E, Englbrecht M, Simon D, Kleyer A, Meinderink T, Vorbrüggen W, von der Decken C, Kleinert S, Ramming A, Distler J, Vuillerme N, Fricker A, Bartz-Bazzanella P, Schett G, Hueber A, Welcker M. Accuracy, patient-perceived usability, and acceptance of two symptom checkers (Ada and Rheport) in rheumatology: interim results from a randomized controlled crossover trial. Arthritis Research & Therapy 2021;23(1) View
  5. Montazeri M, Multmeier J, Novorol C, Upadhyay S, Wicks P, Gilbert S. Optimization of Patient Flow in Urgent Care Centers Using a Digital Tool for Recording Patient Symptoms and History: Simulation Study. JMIR Formative Research 2021;5(5):e26402 View
  6. Gilbert S, Fenech M, Idris A, Türk E. Periodic Manual Algorithm Updates and Generalizability: A Developer’s Response. Comment on “Evaluation of Four Artificial Intelligence–Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study”. Journal of Medical Internet Research 2021;23(6):e26514 View
  7. Martinengo L, Lo N, Goh W, Tudor Car L. Choice of Behavioral Change Techniques in Health Care Conversational Agents: Protocol for a Scoping Review. JMIR Research Protocols 2021;10(7):e30166 View
  8. Asan O, Choudhury A. Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review. JMIR Human Factors 2021;8(2):e28236 View
  9. Schmude M, Salim N, Azadzoy H, Bane M, Millen E, O’Donnell L, Bode P, Türk E, Vaidya R, Gilbert S. Investigating the Potential for Clinical Decision Support in Sub-Saharan Africa With AFYA (Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania): Protocol for a Prospective, Observational Pilot Study. JMIR Research Protocols 2022;11(6):e34298 View
  10. Frommeyer T, Fursmidt R, Gilbert M, Bett E. The Desire of Medical Students to Integrate Artificial Intelligence Into Medical Education: An Opinion Article. Frontiers in Digital Health 2022;4 View
  11. Khanijahani A, Iezadi S, Dudley S, Goettler M, Kroetsch P, Wise J. Organizational, professional, and patient characteristics associated with artificial intelligence adoption in healthcare: A systematic review. Health Policy and Technology 2022;11(1):100602 View
  12. Kopka M, Schmieding M, Rieger T, Roesler E, Balzer F, Feufel M. Determinants of Laypersons’ Trust in Medical Decision Aids: Randomized Controlled Trial. JMIR Human Factors 2022;9(2):e35219 View
  13. Gilbert S, Fenech M, Upadhyay S, Wicks P, Novorol C. Quality of condition suggestions and urgency advice provided by the Ada symptom assessment app evaluated with vignettes optimised for Australia. Australian Journal of Primary Health 2021;27(5):377 View
  14. Cotte F, Mueller T, Gilbert S, Blümke B, Multmeier J, Hirsch M, Wicks P, Wolanski J, Tutschkow D, Schade Brittinger C, Timmermann L, Jerrentrup A. Safety of Triage Self-assessment Using a Symptom Assessment App for Walk-in Patients in the Emergency Care Setting: Observational Prospective Cross-sectional Study. JMIR mHealth and uHealth 2022;10(3):e32340 View
  15. Benoit J, Hartling L, Chan M, Scott S. Characteristics of Acute Childhood Illness Apps for Parents: Environmental Scan. Journal of Medical Internet Research 2021;23(10):e29441 View
  16. d'Elia A, Gabbay M, Rodgers S, Kierans C, Jones E, Durrani I, Thomas A, Frith L. Artificial intelligence and health inequities in primary care: a systematic scoping review and framework. Family Medicine and Community Health 2022;10(Suppl 1):e001670 View
  17. Faqar-Uz-Zaman S, Anantharajah L, Baumartz P, Sobotta P, Filmann N, Zmuc D, von Wagner M, Detemble C, Sliwinski S, Marschall U, Bechstein W, Schnitzbauer A. The Diagnostic Efficacy of an App-based Diagnostic Health Care Application in the Emergency Room: eRadaR-Trial. A prospective, Double-blinded, Observational Study. Annals of Surgery 2022;276(5):935 View
  18. Hillis J, Bizzo B. Use of Artificial Intelligence in Clinical Neurology. Seminars in Neurology 2022;42(01):039 View
  19. Hennemann S, Kuhn S, Witthöft M, Jungmann S. Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients. JMIR Mental Health 2022;9(1):e32832 View
  20. Ramgopal S, Sanchez-Pinto L, Horvat C, Carroll M, Luo Y, Florin T. Artificial intelligence-based clinical decision support in pediatrics. Pediatric Research 2023;93(2):334 View
  21. Yi-No Kang E, Chen D, Chen Y. Associations between literacy and attitudes toward artificial intelligence–assisted medical consultations: The mediating role of perceived distrust and efficiency of artificial intelligence. Computers in Human Behavior 2023;139:107529 View
  22. Albrink K, Joos C, Schröder D, Müller F, Hummers E, Noack E. Obtaining patients’ medical history using a digital device prior to consultation in primary care: study protocol for a usability and validity study. BMC Medical Informatics and Decision Making 2022;22(1) View
  23. Ramgopal S, Heffernan M, Bendelow A, Davis M, Carroll M, Florin T, Alpern E, Macy M. Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care. Academic Pediatrics 2023;23(1):140 View
  24. Kujala S, Hörhammer I. Health Care Professionals’ Experiences of Web-Based Symptom Checkers for Triage: Cross-sectional Survey Study. Journal of Medical Internet Research 2022;24(5):e33505 View
  25. Scheder-Bieschin J, Blümke B, de Buijzer E, Cotte F, Echterdiek F, Nacsa J, Ondresik M, Ott M, Paul G, Schilling T, Schmitt A, Wicks P, Gilbert S. Improving Emergency Department Patient-Physician Conversation Through an Artificial Intelligence Symptom-Taking Tool: Mixed Methods Pilot Observational Study. JMIR Formative Research 2022;6(2):e28199 View
  26. Wozney L, Curran J, Archambault P, Cassidy C, Jabbour M, Mackay R, Newton A, Plint A, Somerville M. Electronic Discharge Communication Tools Used in Pediatric Emergency Departments: Systematic Review. JMIR Pediatrics and Parenting 2022;5(2):e36878 View
  27. Martinengo L, Jabir A, Goh W, Lo N, Ho M, Kowatsch T, Atun R, Michie S, Tudor Car L. Conversational Agents in Health Care: Scoping Review of Their Behavior Change Techniques and Underpinning Theory. Journal of Medical Internet Research 2022;24(10):e39243 View
  28. Fraser H, Cohan G, Koehler C, Anderson J, Lawrence A, Pateña J, Bacher I, Ranney M. Evaluation of Diagnostic and Triage Accuracy and Usability of a Symptom Checker in an Emergency Department: Observational Study. JMIR mHealth and uHealth 2022;10(9):e38364 View
  29. Olickal J, Chinnakali P, Suryanarayana B, Rajanarayanan S, Vivekanandhan T, Saya G, Ganapathy K, Subrahmanyam D. Down referral and assessing comprehensive diabetes care in primary care settings: An operational research from India. Diabetes & Metabolic Syndrome: Clinical Research & Reviews 2023;17(1):102694 View
  30. Knitza J, Muehlensiepen F, Ignatyev Y, Fuchs F, Mohn J, Simon D, Kleyer A, Fagni F, Boeltz S, Morf H, Bergmann C, Labinsky H, Vorbrüggen W, Ramming A, Distler J, Bartz-Bazzanella P, Vuillerme N, Schett G, Welcker M, Hueber A. Patient's Perception of Digital Symptom Assessment Technologies in Rheumatology: Results From a Multicentre Study. Frontiers in Public Health 2022;10 View
  31. Laukka E, Kujala S, Gluschkoff K, Kanste O, Hörhammer I, Heponiemi T. Leaders’ support for using online symptom checkers in Finnish primary care: Survey study. Health Informatics Journal 2021;27(4):146045822110522 View
  32. Millen E, Salim N, Azadzoy H, Bane M, O'Donnell L, Schmude M, Bode P, Tuerk E, Vaidya R, Gilbert S. Study protocol for a pilot prospective, observational study investigating the condition suggestion and urgency advice accuracy of a symptom assessment app in sub-Saharan Africa: the AFYA-‘Health’ Study. BMJ Open 2022;12(4):e055915 View
  33. Müller R, Klemmt M, Ehni H, Henking T, Kuhnmünch A, Preiser C, Koch R, Ranisch R. Ethical, legal, and social aspects of symptom checker applications: a scoping review. Medicine, Health Care and Philosophy 2022;25(4):737 View
  34. Painter A, Hayhoe B, Riboli-Sasco E, El-Osta A. Online Symptom Checkers: Recommendations for a Vignette-Based Clinical Evaluation Standard. Journal of Medical Internet Research 2022;24(10):e37408 View
  35. Young A, Amara D, Bhattacharya A, Wei M. Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review. The Lancet Digital Health 2021;3(9):e599 View
  36. Ilicki J, Kakulapati V. Challenges in evaluating the accuracy of AI-containing digital triage systems: A systematic review. PLOS ONE 2022;17(12):e0279636 View
  37. Irvin L, Madden L, Marshall P, Vince R. Digital Health Solutions for Weight Loss and Obesity: A Narrative Review. Nutrients 2023;15(8):1858 View
  38. Mielke A, Ghanem M, Back D, Fröhlich S, Herbstreit S, Seemann R. Medical studies in times of a pandemic – concepts of digital teaching for Orthopaedics and Trauma at german universities. BMC Medical Education 2023;23(1) View
  39. Lundberg K, Qin L, Aulin C, van Spil W, Maurits M, Knevel R. Population-based user-perceived experience ofRheumatic?: a novel digital symptom-checker in rheumatology. RMD Open 2023;9(2):e002974 View
  40. Kopka M, Scatturin L, Napierala H, Fürstenau D, Feufel M, Balzer F, Schmieding M. Characteristics of Users and Nonusers of Symptom Checkers in Germany: Cross-Sectional Survey Study. Journal of Medical Internet Research 2023;25:e46231 View
  41. Chenais G, Lagarde E, Gil-Jardiné C. Artificial Intelligence in Emergency Medicine: Viewpoint of Current Applications and Foreseeable Opportunities and Challenges. Journal of Medical Internet Research 2023;25:e40031 View
  42. Liu V, Koskela T, Kaila M. User-Initiated Symptom Assessment With an Electronic Symptom Checker: Protocol for a Mixed Methods Validation Study. JMIR Research Protocols 2023;12:e41423 View
  43. Eckstein J. Künstliche Intelligenz in der internistischen Versorgung. Die Innere Medizin 2023;64(11):1017 View
  44. Deng Z, Tian Z, Xue J, Gupta S. What predicts patients’ satisfaction and continuous use of intelligent medical guidance? the moderating effect of consulting experience. Behaviour & Information Technology 2023:1 View
  45. Riboli-Sasco E, El-Osta A, Alaa A, Webber I, Karki M, El Asmar M, Purohit K, Painter A, Hayhoe B. Triage and Diagnostic Accuracy of Online Symptom Checkers: Systematic Review. Journal of Medical Internet Research 2023;25:e43803 View
  46. You Y, Tsai C, Li Y, Ma F, Heron C, Gui X. Beyond Self-diagnosis: How a Chatbot-based Symptom Checker Should Respond. ACM Transactions on Computer-Human Interaction 2023;30(4):1 View
  47. Kerstan S, Bienefeld N, Grote G. Choosing human over AI doctors? How comparative trust associations and knowledge relate to risk and benefit perceptions of AI in healthcare. Risk Analysis 2024;44(4):939 View
  48. Mahlknecht A, Engl A, Piccoliori G, Wiedermann C. Supporting primary care through symptom checking artificial intelligence: a study of patient and physician attitudes in Italian general practice. BMC Primary Care 2023;24(1) View
  49. Asan O, Choi E, Wang X. Artificial Intelligence–Based Consumer Health Informatics Application: Scoping Review. Journal of Medical Internet Research 2023;25:e47260 View
  50. Kafke S, Kuhlmey A, Schuster J, Blüher S, Czimmeck C, Zoellick J, Grosse P. Can clinical decision support systems be an asset in medical education? An experimental approach. BMC Medical Education 2023;23(1) View
  51. Ramgopal S, Kapes J, Alpern E, Carroll M, Heffernan M, Simon N, Florin T, Macy M. Perceptions of Artificial Intelligence-Assisted Care for Children With a Respiratory Complaint. Hospital Pediatrics 2023;13(9):802 View
  52. Spoladore D, Mondellini M, Mahroo A, Chicchi-Giglioli I, De Gaspari S, Di Lernia D, Riva G, Bellini E, Setola N, Sacco M. Smart Waiting Room: A Systematic Literature Review and a Proposal. Electronics 2024;13(2):388 View
  53. Müller R, Klemmt M, Koch R, Ehni H, Henking T, Langmann E, Wiesing U, Ranisch R. “That’s just Future Medicine” - a qualitative study on users’ experiences of symptom checker apps. BMC Medical Ethics 2024;25(1) View
  54. Wetzel A, Koch R, Koch N, Klemmt M, Müller R, Preiser C, Rieger M, Rösel I, Ranisch R, Ehni H, Joos S. ‘Better see a doctor?’ Status quo of symptom checker apps in Germany: A cross-sectional survey with a mixed-methods design (CHECK.APP). DIGITAL HEALTH 2024;10 View
  55. Hammoud M, Douglas S, Darmach M, Alawneh S, Sanyal S, Kanbour Y. Evaluating the Diagnostic Performance of Symptom Checkers: Clinical Vignette Study. JMIR AI 2024;3:e46875 View
  56. Frost E, Bosward R, Aquino Y, Braunack-Mayer A, Carter S. Facilitating public involvement in research about healthcare AI: A scoping review of empirical methods. International Journal of Medical Informatics 2024;186:105417 View
  57. Hagemann J, Becker S, Klimek L. Die Zukunft der Allergologie mitgestalten: das Potenzial digitaler Lösungen, open source und KI bei Patientenversorgung und Registerstudien. Allergo Journal 2024;33(3):53 View
  58. Andreadis K, Newman D, Twan C, Shunk A, Mann D, Stevens E. Mixed methods assessment of the influence of demographics on medical advice of ChatGPT. Journal of the American Medical Informatics Association 2024 View
  59. Huang X, Yang H, Qiao Y. Symptom experiences and influencing factors in patients undergoing chemotherapy for gastrointestinal cancers: a qualitative study. Frontiers in Psychology 2024;15 View

Books/Policy Documents

  1. Eckstein J. The Future Circle of Healthcare. View
  2. Gilbert S. Digital Respiratory Healthcare. View