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

Research Instruments, Questionnaires, and Tools (576) Participatory Medicine & E-Patients (773) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (573) Electronic Health Records (1053) Crowdsourcing and Mechanical Turks (98) Linguistics, Comprehension, and Learning (52)

Published on in Vol 20, No 4 (2018): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9380, first published .
ComprehENotes, an Instrument to Assess Patient Reading Comprehension of Electronic Health Record Notes: Development and Validation

ComprehENotes, an Instrument to Assess Patient Reading Comprehension of Electronic Health Record Notes: Development and Validation

ComprehENotes, an Instrument to Assess Patient Reading Comprehension of Electronic Health Record Notes: Development and Validation

Authors of this article:

John P Lalor1 Author Orcid Image ;   Hao Wu2 Author Orcid Image ;   Li Chen2 Author Orcid Image ;   Kathleen M Mazor3 Author Orcid Image ;   Hong Yu1, 4, 5, 6 Author Orcid Image
Article Authors Cited by (12) Tweetations (12) Metrics

Journals

  1. Kulzer B. Ist die elektronische Patientenakte bei Diabetes Fluch oder Segen?. Info Diabetologie 2020;14(2):29 View
  2. Zheng J, Yu H. QuikLitE, a Framework for Quick Literacy Evaluation in Medicine: Development and Validation. Journal of Medical Internet Research 2019;21(2):e12525 View
  3. Antonio M, Petrovskaya O, Lau F. Is research on patient portals attuned to health equity? A scoping review. Journal of the American Medical Informatics Association 2019;26(8-9):871 View
  4. Lalor J, Woolf B, Yu H. Improving Electronic Health Record Note Comprehension With NoteAid: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Crowdsourced Workers. Journal of Medical Internet Research 2019;21(1):e10793 View
  5. Sousa D, Lamurias A, Couto F. A hybrid approach toward biomedical relation extraction training corpora: combining distant supervision with crowdsourcing. Database 2020;2020 View
  6. He X, Zhang R, Alpert J, Zhou S, Adam T, Raisa A, Peng Y, Zhang H, Guo Y, Bian J. When text simplification is not enough: could a graph-based visualization facilitate consumers’ comprehension of dietary supplement information?. JAMIA Open 2021;4(1) View
  7. Lalor J, Hu W, Tran M, Wu H, Mazor K, Yu H. Evaluating the Effectiveness of NoteAid in a Community Hospital Setting: Randomized Trial of Electronic Health Record Note Comprehension Interventions With Patients. Journal of Medical Internet Research 2021;23(5):e26354 View
  8. Hendawi R, Alian S, Li J. A Smart Mobile App to Simplify Medical Documents and Improve Health Literacy: System Design and Feasibility Validation. JMIR Formative Research 2022;6(4):e35069 View
  9. Lalor J, Wu H, Mazor K, Yu H. Evaluating the efficacy of NoteAid on EHR note comprehension among US Veterans through Amazon Mechanical Turk. International Journal of Medical Informatics 2023;172:105006 View
  10. Dijkman E, ter Brake W, Drossaert C, Doggen C. Assessment Tools for Measuring Health Literacy and Digital Health Literacy in a Hospital Setting: A Scoping Review. Healthcare 2023;12(1):11 View
  11. Levy D, Jordan H, Lalor J, Smirnova J, Hu W, Liu W, Yu H. Individual Factors That Affect Laypeople's Understanding of Definitions of Medical Jargon. Health Policy and Technology 2024:100932 View