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


Journal

Current HIV/AIDS reports
ISSN: 1548-3576
Titre abrégé: Curr HIV/AIDS Rep
Pays: United States
ID NLM: 101235661

Informations de publication

Date de publication:
06 2020
Historique:
pubmed: 12 5 2020
medline: 21 10 2020
entrez: 12 5 2020
Statut: ppublish

Résumé

To provide a comprehensive review of usability testing of eHealth interventions for HIV. We identified 28 articles that assessed the usability of eHealth interventions for HIV, most of which were published within the past 3 years. The majority of the eHealth interventions for HIV was developed on a mobile platform and focused on HIV prevention as the intended health outcome. Usability evaluation methods included eye-tracking, questionnaires, semi-structured interviews, contextual interviews, think-aloud protocols, cognitive walkthroughs, heuristic evaluations and expert reviews, focus groups, and scenarios. A wide variety of methods is available to evaluate the usability of eHealth interventions. Employing multiple methods may provide a more comprehensive assessment of the usability of eHealth interventions as compared with inclusion of only a single evaluation method.

Identifiants

pubmed: 32390078
doi: 10.1007/s11904-020-00493-3
pii: 10.1007/s11904-020-00493-3
pmc: PMC7367140
mid: NIHMS1592937
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

203-218

Subventions

Organisme : NINR NIH HHS
ID : K24 NR018621
Pays : United States

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Auteurs

Rindcy Davis (R)

Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University Medical Center, 630 W 168th Street, New York, NY, 10032, USA.

Jessica Gardner (J)

Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, 630 W 168th Street, New York, NY, 10032, USA.

Rebecca Schnall (R)

School of Nursing, Columbia University, New York, NY, 10032, USA. rb897@columbia.edu.

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Classifications MeSH