1
|
Kor PPK, Leung AYM, Parial LL, Wong EML, Dadaczynski K, Okan O, Amoah PA, Wang SS, Deng R, Cheung TCC, Molassiotis A. Are People With Chronic Diseases Satisfied With the Online Health Information Related to COVID‐19 During the Pandemic? J Nurs Scholarsh 2020; 53:75-86. [DOI: 10.1111/jnu.12616] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2020] [Indexed: 12/11/2022]
Affiliation(s)
- Patrick Pui Kin Kor
- Assistant Professor Centre for Gerontological Nursing School of Nursing Hong Kong Polytechnic University Hong Kong SAR China
| | - Angela Yee Man Leung
- Associate Professor and Director Centre for Gerontological Nursing School of Nursing Hong Kong Polytechnic University Hong Kong SAR China
| | - Laurence Lloyd Parial
- PhD Student Centre for Gerontological Nursing School of Nursing Hong Kong Polytechnic University Hong Kong SAR China
| | - Eliza Mi Ling Wong
- Principal Research Fellow Centre for Gerontological Nursing School of Nursing Hong Kong Polytechnic University Hong Kong SAR China
| | - Kevin Dadaczynski
- Professor Fulda University of Applied SciencesPublic Health Centre Fulda Fulda Germany
| | - Orkan Okan
- Research Associate Bielefeld UniversityFaculty of Educational ScienceInterdisciplinary Centre for Health Literacy Research Bielefeld Germany
| | - Padmore Adusei Amoah
- Research Assistant Professor School of Graduate Studies Asia Pacific Institute of Ageing StudiesCentre for Social Policy and Social ChangeLingnan University Hong Kong SAR China
| | - Shan Shan Wang
- Post doctoral fellow Centre for Gerontological Nursing School of Nursing Hong Kong Polytechnic University Hong Kong SAR China
| | - Renli Deng
- Director Department of Nursing The 5th Affiliated Hospital of Zhuyi Medical University Zhuhai China
| | - Teris Cheuk Chi Cheung
- Research Assistant Professor School of Nursing Hong Kong Polytechnic University Hong Kong SAR China
| | - Alex Molassiotis
- Chair Professor WHO Collaborating Centre for Community Health Services School of Nursing Hong Kong Polytechnic University Hong Kong China
| |
Collapse
|
2
|
Marco-Ruiz L, Bønes E, de la Asunción E, Gabarron E, Aviles-Solis JC, Lee E, Traver V, Sato K, Bellika JG. Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers. J Biomed Inform 2017; 74:104-122. [PMID: 28893671 DOI: 10.1016/j.jbi.2017.09.002] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2017] [Revised: 08/28/2017] [Accepted: 09/04/2017] [Indexed: 10/18/2022]
Abstract
Symptom checkers are software tools that allow users to submit a set of symptoms and receive advice related to them in the form of a diagnosis list, health information or triage. The heterogeneity of their potential users and the number of different components in their user interfaces can make testing with end-users unaffordable. We designed and executed a two-phase method to test the respiratory diseases module of the symptom checker Erdusyk. Phase I consisted of an online test with a large sample of users (n=53). In Phase I, users evaluated the system remotely and completed a questionnaire based on the Technology Acceptance Model. Principal Component Analysis was used to correlate each section of the interface with the questionnaire responses, thus identifying which areas of the user interface presented significant contributions to the technology acceptance. In the second phase, the think-aloud procedure was executed with a small number of samples (n=15), focusing on the areas with significant contributions to analyze the reasons for such contributions. Our method was used effectively to optimize the testing of symptom checker user interfaces. The method allowed kept the cost of testing at reasonable levels by restricting the use of the think-aloud procedure while still assuring a high amount of coverage. The main barriers detected in Erdusyk were related to problems understanding time repetition patterns, the selection of levels in scales to record intensities, navigation, the quantification of some symptom attributes, and the characteristics of the symptoms.
Collapse
Affiliation(s)
- Luis Marco-Ruiz
- Norwegian Centre for E-health Research, University Hospital of North Norway, P.O. Box 35, N-9038 Tromsø, Norway; Department of Clinical Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, 9037 Tromsø, Norway.
| | - Erlend Bønes
- Norwegian Centre for E-health Research, University Hospital of North Norway, P.O. Box 35, N-9038 Tromsø, Norway
| | - Estela de la Asunción
- Norwegian Centre for E-health Research, University Hospital of North Norway, P.O. Box 35, N-9038 Tromsø, Norway
| | - Elia Gabarron
- Norwegian Centre for E-health Research, University Hospital of North Norway, P.O. Box 35, N-9038 Tromsø, Norway; Department of Clinical Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, 9037 Tromsø, Norway
| | - Juan Carlos Aviles-Solis
- Department of Community Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, 9037 Tromsø, Norway
| | - Eunji Lee
- SINTEF, Forskningsveien 1, 0373 Oslo, Norway
| | - Vicente Traver
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Keiichi Sato
- Institute of Design, Illinois Institute of Technology, 565 West Adams Street, Chicago, IL 60661, United States; Department of Computer Science, UIT The Arctic University of Norway, 9037 Tromsø, Norway
| | - Johan G Bellika
- Norwegian Centre for E-health Research, University Hospital of North Norway, P.O. Box 35, N-9038 Tromsø, Norway; Department of Clinical Medicine, Faculty of Health Sciences, UIT The Arctic University of Norway, 9037 Tromsø, Norway
| |
Collapse
|