Literature DB >> 35144102

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

Kah Poh Loh1, Jianfang Liu2, Sarah Ganzhorn3, Gabriella Sanabria4, Rebecca Schnall5.   

Abstract

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 completedby 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 [β = 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.
Copyright © 2022 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Health-ITUES; Information technology; Mobile health; Usability

Mesh:

Year:  2022        PMID: 35144102      PMCID: PMC8903058          DOI: 10.1016/j.ijmedinf.2022.104713

Source DB:  PubMed          Journal:  Int J Med Inform        ISSN: 1386-5056            Impact factor:   4.046


  26 in total

1.  A Multi-step Usability Evaluation of a Self-Management App to Support Medication Adherence in Persons Living with HIV.

Authors:  Melissa Beauchemin; Melissa Gradilla; Dawon Baik; Hwayoung Cho; Rebecca Schnall
Journal:  Int J Med Inform       Date:  2018-12-03       Impact factor: 4.046

2.  A simulation study of cross-validation for selecting an optimal cutpoint in univariate survival analysis.

Authors:  D Faraggi; R Simon
Journal:  Stat Med       Date:  1996-10-30       Impact factor: 2.373

3.  Do High-Risk Young Adults Use the HIV Self-Test Appropriately? Observations from a Think-Aloud Study.

Authors:  Rebecca Schnall; Rita Marie John; Alex Carballo-Dieguez
Journal:  AIDS Behav       Date:  2016-04

4.  Examining construct and predictive validity of the Health-IT Usability Evaluation Scale: confirmatory factor analysis and structural equation modeling results.

Authors:  Po-Yin Yen; Karen H Sousa; Suzanne Bakken
Journal:  J Am Med Inform Assoc       Date:  2014-02-24       Impact factor: 4.497

5.  Quick assessment of literacy in primary care: the newest vital sign.

Authors:  Barry D Weiss; Mary Z Mays; William Martz; Kelley Merriam Castro; Darren A DeWalt; Michael P Pignone; Joy Mockbee; Frank A Hale
Journal:  Ann Fam Med       Date:  2005 Nov-Dec       Impact factor: 5.166

6.  Comparative study of heuristic evaluation and usability testing methods.

Authors:  Thankam Paul Thyvalikakath; Valerie Monaco; Himabindu Thambuganipalle; Titus Schleyer
Journal:  Stud Health Technol Inform       Date:  2009

Review 7.  A Review of Usability Evaluation Methods and Their Use for Testing eHealth HIV Interventions.

Authors:  Rindcy Davis; Jessica Gardner; Rebecca Schnall
Journal:  Curr HIV/AIDS Rep       Date:  2020-06       Impact factor: 5.071

8.  Developing and adapting a mobile health exercise intervention for older patients with myeloid neoplasms: A qualitative study.

Authors:  Kah Poh Loh; Chandrika Sanapala; Grace Di Giovanni; Heidi D Klepin; Michelle Janelsins; Rebecca Schnall; Eva Culakova; Paula Vertino; Martha Susiarjo; Jason H Mendler; Jane L Liesveld; Po-Ju Lin; Richard F Dunne; Ian Kleckner; Karen Mustian; Supriya G Mohile
Journal:  J Geriatr Oncol       Date:  2021-03-04       Impact factor: 3.929

9.  Usability Testing of a mHealth App to Support Self-Management of HIV-Associated Non-AIDS Related Symptoms.

Authors:  Samantha Stonbraker; Hwayoung Cho; Gabriella Hermosi; Adrienne Pichon; Rebecca Schnall
Journal:  Stud Health Technol Inform       Date:  2018

10.  Novel mHealth App to Deliver Geriatric Assessment-Driven Interventions for Older Adults With Cancer: Pilot Feasibility and Usability Study.

Authors:  Kah Poh Loh; Erika Ramsdale; Eva Culakova; Jason H Mendler; Jane L Liesveld; Kristen M O'Dwyer; Colin McHugh; Maxence Gilles; Terri Lloyd; Molly Goodman; Heidi D Klepin; Karen M Mustian; Rebecca Schnall; Supriya G Mohile
Journal:  JMIR Cancer       Date:  2018-10-29
View more
  1 in total

1.  Combining human and machine intelligence for clinical trial eligibility querying.

Authors:  Yilu Fang; Betina Idnay; Yingcheng Sun; Hao Liu; Zhehuan Chen; Karen Marder; Hua Xu; Rebecca Schnall; Chunhua Weng
Journal:  J Am Med Inform Assoc       Date:  2022-06-14       Impact factor: 7.942

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.