Evidence map›Paper›PMID 38368698›Full record

ArticleInternational journal of medical informatics2024

Comparison of evaluation methods for improving the usability of a Spanish mHealth tool.

Alexandria L Hahn, Claudia L Michaels, Gabriella Khawly, Tyler K Nichols, Pamela Baez, Sergio Ozoria Ramirez, Janeth Juarez Padilla, Samantha Stonbraker, Susan Olender, Rebecca Schnall

Open access · greenAbstract read
In one paragraph

Article in International journal of medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.5field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Alexandria L HahnColumbia University School of Nursing, New York, NY, United States. Electronic address: alh2232@columbia.edu.
Claudia L MichaelsColumbia University School of Nursing, New York, NY, United States; Mailman School of Public Health, Columbia University, New York, NY, United States.
Gabriella KhawlyColumbia University School of Nursing, New York, NY, United States; Mailman School of Public Health, Columbia University, New York, NY, United States.
Tyler K NicholsColumbia University School of Nursing, New York, NY, United States.
Pamela BaezClínica de Familia La Romana, La Romana, Dominican Republic.
Sergio Ozoria RamirezColumbia University School of Nursing, New York, NY, United States.
Janeth Juarez PadillaNew York University School of Medicine, New York, NY, United States.
Samantha StonbrakerUniversity of Colorado College of Nursing, Anschutz Medical Campus, Aurora CO, United States.
Susan OlenderDivision of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, NY, United States.
Rebecca SchnallColumbia University School of Nursing, New York, NY, United States; Mailman School of Public Health, Columbia University, New York, NY, United States.
Columbia University · USColumbia University Irving Medical Center · USNew York University · US

Funding

Reducing Health Disparities Through Informatics - Genomics SupplementT32NR007969 · NINR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SUZANNE BAKKEN, Rebecca Schnall · 2002 to 2026
$7.9M
Reaching Communities through the Design of Information Visualizations (ReDIVis) Toolbox to Address COVID-19 Vaccine Hesitancy and Uptake.P30NR016587 · NINR · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BAKKEN, SUZANNE, SMALDONE, ARLENE M · 2016 to 2022
$4.3M
Dissemination of the WiseApp for Improving Health Outcomes Across SettingsR18HS028523 · AHRQ · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SCHNALL, REBECCA · 2021 to 2024
$1.6M
Information visualizations to facilitate clinician-patient communication in HIV care (Info Viz: HIV)R00NR017829 · NINR · UNIVERSITY OF COLORADO DENVER · PI STONBRAKER, SAMANTHA · 2020 to 2022
$717k
AHRQ HHS R18 HS028523NINR NIH HHS P30 NR016587NINR NIH HHS R00 NR017829NINR NIH HHS T32 NR007969
6 · The paper itself

Abstract

objectiveMobile health (mHealth) technology is now widely used across health conditions and populations. The rigorous development of these tools has yielded improved health outcomes, yet the ideal approach for developing mHealth tools continues to evolve, indicating the need for rigorous usability evaluation methods. This study compares two usability evaluation methods - cognitive interviews and usability assessments employing a think-aloud approach - for adapting an evidence-based mHealth tool from English into Spanish.

methodsWe conducted cognitive interviews and usability assessments using a think-aloud protocol to evaluate the usability of an HIV mHealth application among 40 Spanish-speaking adults with HIV in New York City, NY, and La Romana, Dominican Republic. The Health IT Usability Evaluation Model (Health-ITUEM) was used to guide the analysis of qualitative data collected from each method.

resultsParticipants (N = 40) averaged 43 years old (SD = 12.26; range 20-79), identified primarily Hispanic/Latino (92.5 %), and resided in La Romana (50 %) or New York City (50 %). Both usability evaluation methods yielded similar findings, highlighting learnability and information needs as crucial components of participant feedback for the mHealth application. Cognitive interviews captured participants' perspectives on the app's interface and design. On the other hand, results from usability assessments offered insights into participants' competency while interacting with the mHealth tool.

conclusionFindings from this study highlight the contributions and limitations of including cognitive interviews and task-based usability assessments using a think-aloud approach in mHealth usability testing. Future research should employ a multi-method approach, incorporating complementary usability evaluation methods and engaging participants in multiple assessments. Using complementary usability evaluation methods may provide a more comprehensive understanding of the usability and participant experience aspects of a mHealth tool compared to using a single usability evaluation method.

Indexed as

HIV InfectionsMobile ApplicationsTelemedicineAdultAgedData AccuracyHumansMiddle AgedYoung AdultCognitive InterviewsmHealthThink aloudUsabilityUsability evaluation methods

Identifiers

PMID38368698
PMCPMC10923187
OpenAlexW4391744168

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.