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

Usability of Apps and User Perceptions of mHealth (884) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (777) mHealth for Data Collection and Research (899)

Published on in Vol 6, No 5 (2018): May

Designing a Tablet-Based Software App for Mapping Bodily Symptoms: Usability Evaluation and Reproducibility Analysis

Designing a Tablet-Based Software App for Mapping Bodily Symptoms: Usability Evaluation and Reproducibility Analysis

Designing a Tablet-Based Software App for Mapping Bodily Symptoms: Usability Evaluation and Reproducibility Analysis

Authors of this article:

Till-Ansgar Neubert1 Author Orcid Image ;   Martin Dusch2 Author Orcid Image ;   Matthias Karst2 Author Orcid Image ;   Florian Beissner1 Author Orcid Image
Article Authors Cited by (22) Tweetations (3) Metrics

Journals

  1. Shaballout N, Aloumar A, Neubert T, Dusch M, Beissner F. Digital Pain Drawings Can Improve Doctors’ Understanding of Acute Pain Patients: Survey and Pain Drawing Analysis. JMIR mHealth and uHealth 2019;7(1):e11412 View
  2. Almeida A, Rocha N, Silva A. Methodological Quality of Manuscripts Reporting on the Usability of Mobile Applications for Pain Assessment and Management: A Systematic Review. International Journal of Environmental Research and Public Health 2020;17(3):785 View
  3. Sigle S, Barriga P, Correa Fernández F, Juhra C, Härtel S, Fegeler C. Evaluating Online Consumer Medication Information Systems: Comparative Online Usability Study. JMIR mHealth and uHealth 2020;8(6):e16648 View
  4. Tobore I, Li J, Yuhang L, Al-Handarish Y, Kandwal A, Nie Z, Wang L. Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations. JMIR mHealth and uHealth 2019;7(8):e11966 View
  5. Ziemssen T, Kern R, Voigt I, Haase R. Data Collection in Multiple Sclerosis: The MSDS Approach. Frontiers in Neurology 2020;11 View
  6. Shaballout N, Neubert T, Boudreau S, Beissner F. From Paper to Digital Applications of the Pain Drawing: Systematic Review of Methodological Milestones. JMIR mHealth and uHealth 2019;7(9):e14569 View
  7. Schiller J, Kellner T, Briest J, Hoepner K, Woyciechowski A, Ostermann A, Korallus C, Sturm C, Weiberlenn T, Jiang L, Egen C, Beissner F, Stiesch M, Karst M, Gutenbrunner C, Fink M. The best from East and West? Acupuncture and medical training therapy as monotherapies or in combination for adult patients with episodic and chronic tension-type headache: study protocol for a randomized controlled trial. Trials 2019;20(1) View
  8. Corrêa L, Bittencourt J, Ferreira A, Reis F, de Almeida R, Nogueira L. The Reliability and Concurrent Validity of PainMAP Software for Automated Quantification of Pain Drawings on Body Charts of Patients With Low Back Pain. Pain Practice 2020;20(5):462 View
  9. Ali S, Lau W, McBeth J, Dixon W, van der Veer S. Digital manikins to self‐report pain on a smartphone: A systematic review of mobile apps. European Journal of Pain 2021;25(2):327 View
  10. Ellingsen D, Beissner F, Moher Alsady T, Lazaridou A, Paschali M, Berry M, Isaro L, Grahl A, Lee J, Wasan A, Edwards R, Napadow V. A picture is worth a thousand words: linking fibromyalgia pain widespreadness from digital pain drawings with pain catastrophizing and brain cross-network connectivity. Pain 2021;162(5):1352 View
  11. Loose L, Manuel J, Karst M, Schmidt L, Beissner F. Flotation Restricted Environmental Stimulation Therapy for Chronic Pain. JAMA Network Open 2021;4(5):e219627 View
  12. Shaballout N, Aloumar A, Manuel J, May M, Beissner F. Lateralization and Bodily Patterns of Segmental Signs and Spontaneous Pain in Acute Visceral Disease: Observational Study. Journal of Medical Internet Research 2021;23(8):e27247 View
  13. Boudreau S. Visualizing and quantifying spatial and qualitative pain sensations. Scandinavian Journal of Pain 2022;22(4):681 View
  14. Dixit A, Lee M. Quantification of Digital Body Maps for Pain: Development and Application of an Algorithm for Generating Pain Frequency Maps. JMIR Formative Research 2022;6(6):e36687 View
  15. Pike C, Kim M, Schnitzer K, Mercaldo N, Edwards R, Napadow V, Zhang Y, Morrissey E, Alshelh Z, Evins A, Loggia M, Gilman J. Study protocol for a phase II, double-blind, randomised controlled trial of cannabidiol (CBD) compared with placebo for reduction of brain neuroinflammation in adults with chronic low back pain. BMJ Open 2022;12(9):e063613 View
  16. Manuel J, Rudolph L, Beissner F, Neubert T, Dusch M, Karst M. Traumatic Events, Posttraumatic Stress Disorder, and Central Sensitization in Chronic Pain Patients of a German University Outpatient Pain Clinic. Psychosomatic Medicine 2023;85(4):351 View
  17. Tragoudas M, Dimitriadis Z, Koufogianni A, Kanellopoulos A, Vassis K, Gkrilias P, Spanos S, Poulis I. Test-retest reliability of pain extent and pain location using a novel pain drawing analysis software application, on patients with shoulder pain. Expert Review of Medical Devices 2023;20(12):1219 View
  18. Mamakou X, Zaharias P, Milesi M. Measuring customer satisfaction in electronic commerce: the impact of e-service quality and user experience. International Journal of Quality & Reliability Management 2024;41(3):915 View
  19. Boudreau S, Jakobsen T, Haraldsson B, Clausen M. Digital mapping of shoulder pain in patients with shoulder disorders: a reliability study. Physiotherapy Theory and Practice 2024:1 View
  20. van der Veer S, Ali S, Yu Z, McBeth J, Chiarotto A, James B, Dixon W. Reliability, validity, and responsiveness of a smartphone-based manikin to support pain self-reporting. PAIN Reports 2024;9(2):e1131 View
  21. Cescon C, Landolfi G, Bonomi N, Derboni M, Giuffrida V, Rizzoli A, Maino P, Koetsier E, Barbero M. Automated pain spots recognition algorithm provided by a web service-based platform (Preprint). JMIR mHealth and uHealth 2023 View

Books/Policy Documents

  1. Baharum A, Abdul Aziz S, Mat Zain N. Intelligent Computing. View