Establishing a usability cut-point for the health information technology usability evaluation scale (Health-ITUES)

被引:10
作者
Loh, Kah Poh [1 ]
Liu, Jianfang [2 ]
Ganzhorn, Sarah [2 ]
Sanabria, Gabriella [3 ]
Schnall, Rebecca [2 ]
机构
[1] Univ Rochester, James P Wilmot Canc Inst, Dept Med, Div Hematol Oncol,Med Ctr, Rochester, NY USA
[2] Columbia Univ, Sch Nursing, New York, NY USA
[3] Univ S Florida, Coll Publ Hlth, Tampa, FL USA
基金
美国医疗保健研究与质量局;
关键词
Mobile health; Usability; Information technology; Health-ITUES; SELF-MANAGEMENT; THINK-ALOUD; MOBILE; APP; LITERACY; ADULTS;
D O I
10.1016/j.ijmedinf.2022.104713
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Objective: The Health Information Technology Usability Evaluation Scale (Health-ITUES) is a validated and reliable instrument to evaluate usability of information technology (IT) tools. In this study, we aimed to establish the optimal cut-point of the Health-ITUES to identify usability of IT tools. Methods: Adult participants were recruited to a trial evaluating a mobile app for self-managing HIV. Participants completed the Health-ITUES at the 3- and 6-month follow-up. Health-ITUES is a 20-item questionnaire that assesses four subscales: impact, perceived usefulness, perceived ease of use, and user control. The total score ranged from 1 to 5 and a higher score indicates greater usability. App use was defined as the proportion of activities completed by participants in both study arms. The selection of an optimal cut-point involved a series of multiple linear regression models with 500 bootstrap replications to examine the relationship between the Health-ITUES total score and app use, controlling for potential covariates. Results: We included 158 participants; mean age was 49.7 years (SD 10.3), 71% were African American/Black, and 72% were non-Hispanic. Mean Health-ITUES total scores at 3 and 6 months were 4.39 (SD 0.75) and 4.43 (SD 0.75), respectively. App use completed by participants from baseline to the 3-month follow-up visits was 0.61 (SD 0.36, range 0-1.72) and from 3-month to the 6-month follow-up visits was 0.51 (SD 0.37). Participants who reported greater Health-ITUES total score completed more activities [beta = 0.18, 95% Confidence Interval (CI) 0.10-0.27]. The optimal cut-point of 4.32 (95% CI: 4.25-4.56) yielded the lowest p-value to identify usability of IT tools. Conclusions: In this study of adults with HIV, we identified an optimal cut-point of 4.32 on the Health-ITUES total score to define usability. Further studies are needed to validate this cut-point.
引用
收藏
页数:7
相关论文
共 43 条
[1]   Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik [J].
Akdur, Gorkem ;
Aydin, Mehmet Nafiz ;
Akdur, Gizdem .
JMIR MHEALTH AND UHEALTH, 2020, 8 (10)
[2]  
[Anonymous], 2021, Op.cit., fact sheet
[3]  
Bailey R., 2009, Performance-Based Usability Testing: Metrics That Have the Greatest Impact for Improving a System's Usability. Human Centered Design
[4]   A Multi-step Usability Evaluation of a Self-Management App to Support Medication Adherence in Persons Living with HIV [J].
Beauchemin, Melissa ;
Gradilla, Melissa ;
Baik, Dawon ;
Cho, Hwayoung ;
Schnall, Rebecca .
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2019, 122 :37-44
[5]  
Brooke John., 1996, Usability evaluation in industry, V189, P4
[6]   Eye-tracking retrospective think-aloud as a novel approach for a usability evaluation [J].
Cho, Hwayoung ;
Powell, Dakota ;
Pichon, Adrienne ;
Kuhns, Lisa M. ;
Garofalo, Robert ;
Schnall, Rebecca .
INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2019, 129 :366-373
[7]   A multi-level usability evaluation of mobile health applications: A case study [J].
Cho, Hwayoung ;
Yen, Po-Yin ;
Dowding, Dawn ;
Merrill, Jacqueline A. ;
Schnall, Rebecca .
JOURNAL OF BIOMEDICAL INFORMATICS, 2018, 86 :79-89
[8]   Factors Influencing Usability of a Smartphone App to Reduce Excessive Alcohol Consumption: Think Aloud and Interview Studies [J].
Crane, David ;
Garnett, Claire ;
Brown, Jamie ;
West, Robert ;
Michie, Susan .
FRONTIERS IN PUBLIC HEALTH, 2017, 5
[10]   A Review of Usability Evaluation Methods and Their Use for Testing eHealth HIV Interventions [J].
Davis, Rindcy ;
Gardner, Jessica ;
Schnall, Rebecca .
CURRENT HIV/AIDS REPORTS, 2020, 17 (03) :203-218