This paper is in the following e-collection/theme issue:

Diagnostic Tools in Mental Health (326) Symptom Checkers (42) mHealth in a Clinical Setting (743) Methods and New Tools in Mental Health Research (558) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2109) Innovations in Mental Health Systems (484) Mobile Health in Psychiatry (527) Transdiagnostic Mental Health Interventions (207) Usability of Apps and User Perceptions of mHealth (1188)

Published on in Vol 9, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32832, first published .
Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients

Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients

Diagnostic Performance of an App-Based Symptom Checker in Mental Disorders: Comparative Study in Psychotherapy Outpatients

Authors of this article:

Severin Hennemann1 Author Orcid Image ;   Sebastian Kuhn2 Author Orcid Image ;   Michael Witthöft1 Author Orcid Image ;   Stefanie M Jungmann1 Author Orcid Image
Article Authors Cited by (20) Tweetations (11) Metrics

Journals

  1. Schmieding M, Kopka M, Schmidt K, Schulz-Niethammer S, Balzer F, Feufel M. Triage Accuracy of Symptom Checker Apps: 5-Year Follow-up Evaluation. Journal of Medical Internet Research 2022;24(5):e31810 View
  2. 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
  3. 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
  4. Zielasek J, Reinhardt I, Schmidt L, Gouzoulis-Mayfrank E. Adapting and Implementing Apps for Mental Healthcare. Current Psychiatry Reports 2022;24(9):407 View
  5. Achtyes E, Glenn T, Monteith S, Geddes J, Whybrow P, Martini J, Bauer M. Telepsychiatry in an Era of Digital Mental Health Startups. Current Psychiatry Reports 2023;25(6):263 View
  6. Määttä J, Lindell R, Hayward N, Martikainen S, Honkanen K, Inkala M, Hirvonen P, Martikainen T. Diagnostic Performance, Triage Safety, and Usability of a Clinical Decision Support System Within a University Hospital Emergency Department: Algorithm Performance and Usability Study. JMIR Medical Informatics 2023;11:e46760 View
  7. Terhorst Y, Weilbacher N, Suda C, Simon L, Messner E, Sander L, Baumeister H. Acceptance of smart sensing: a barrier to implementation—results from a randomized controlled trial. Frontiers in Digital Health 2023;5 View
  8. Sarkar S, Gaur M, Chen L, Garg M, Srivastava B. A review of the explainability and safety of conversational agents for mental health to identify avenues for improvement. Frontiers in Artificial Intelligence 2023;6 View
  9. Abilkaiyrkyzy A, Laamarti F, Hamdi M, Saddik A. Dialogue System for Early Mental Illness Detection: Toward a Digital Twin Solution. IEEE Access 2024;12:2007 View
  10. 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
  11. Miller N, North F, Curry E, Thompson M, Pecina J. Recommendation endpoints and safety of an online self-triage for depression symptoms. Journal of Telemedicine and Telecare 2025;31(8):1186 View
  12. Knauer J, Baumeister H, Schmitt A, Terhorst Y. Acceptance of smart sensing, its determinants, and the efficacy of an acceptance-facilitating intervention in people with diabetes: results from a randomized controlled trial. Frontiers in Digital Health 2024;6 View
  13. Chamorro-Delmo J, Lopez-Fernandez O, Villasante-Soriano P, Antonio P, Álvarez-García R, Porras-Segovia A, Baca-García E. A feasibility study of a Smart screening tool for people at risk of mental health issues: Response rate, and sociodemographic and clinical factors. Journal of Affective Disorders 2024;362:755 View
  14. Szumilas D, Ochmann A, Zięba K, Bartoszewicz B, Kubrak A, Makuch S, Agrawal S, Mazur G, Chudek J. Evaluation of AI-Driven LabTest Checker for Diagnostic Accuracy and Safety: Prospective Cohort Study. JMIR Medical Informatics 2024;12:e57162 View
  15. Hindelang M, Sitaru S, Zink A. Transforming Health Care Through Chatbots for Medical History-Taking and Future Directions: Comprehensive Systematic Review. JMIR Medical Informatics 2024;12:e56628 View
  16. Preiser C, Radionova N, Ög E, Koch R, Klemmt M, Müller R, Ranisch R, Joos S, Rieger M. The Doctors, Their Patients, and the Symptom Checker App: Qualitative Interview Study With General Practitioners in Germany. JMIR Human Factors 2024;11:e57360 View
  17. Kleine A, Kokje E, Hummelsberger P, Lermer E, Schaffernak I, Gaube S. AI-enabled clinical decision support tools for mental healthcare: A product review. Artificial Intelligence in Medicine 2025;160:103052 View
  18. Kopka M, von Kalckreuth N, Feufel M. Accuracy of online symptom assessment applications, large language models, and laypeople for self–triage decisions. npj Digital Medicine 2025;8(1) View
  19. Schmieding M, Kopka M, Bolanaki M, Napierala H, Altendorf M, Kuschick D, Piper S, Scatturin L, Schmidt K, Schorr C, Thissen A, Wäscher C, Heintze C, Möckel M, Balzer F, Slagman A. Impact of a Symptom Checker App on Patient-Physician Interaction Among Self-Referred Walk-In Patients in the Emergency Department: Multicenter, Parallel-Group, Randomized, Controlled Trial. Journal of Medical Internet Research 2025;27:e64028 View

Conference Proceedings

  1. Won H, Kang M, Kim M, Lee D, Choi H, Kim Y, Choi D, Ko M, Han J. Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. "Show Your Mind": Unveiling User Experience on an AI-based Mental Health Assessment System with Symptom-based Evidences View