Evidence map›Paper›PMID 36873830›Full record

ArticleInformatics (MDPI)2022

Assessing Usability of Smartwatch Digital Health Devices for Home Blood Pressure Monitoring among Glaucoma Patients.

Sonali B Bhanvadia, Manreet S Brar, Arash Delavar, Kiana Tavakoli, Bharanidharan Radha Saseendrakumar, Robert N Weinreb, Linda M Zangwill, Sally L Baxter

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Informatics (MDPI), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. 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

8 authors at 1 institution in 1 country.

Sonali B BhanvadiaHamilton Glaucoma Center, Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, CA 92093, USA.ORCID 0000-0001-6585-5649
Manreet S BrarHamilton Glaucoma Center, Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, CA 92093, USA.ORCID 0000-0002-2123-125X
Arash DelavarHamilton Glaucoma Center, Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, CA 92093, USA.
Kiana TavakoliHamilton Glaucoma Center, Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, CA 92093, USA.
Bharanidharan Radha SaseendrakumarHamilton Glaucoma Center, Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, CA 92093, USA.
Robert N WeinrebHamilton Glaucoma Center, Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, CA 92093, USA.ORCID 0000-0001-9553-3202
Linda M ZangwillHamilton Glaucoma Center, Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, CA 92093, USA.ORCID 0000-0002-1143-5224
Sally L BaxterHamilton Glaucoma Center, Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, CA 92093, USA.ORCID 0000-0002-5271-7690
University of California San Diego · US

Funding

Vision BiostatisticsP30EY022589 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Derek Stuart Welsbie · 2012 to 2026
$10.3M
Multi-modal Health Information Technology Innovations for Precision Management of GlaucomaDP5OD029610 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAXTER, SALLY LIU · 2020 to 2024
$2.1M
Multimodal Artificial Intelligence to Predict Glaucomatous Progression and Surgical InterventionR01EY034146 · NEI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BAXTER, SALLY LIU, CHRISTOPHER, MARK · 2022 to 2025
$1.8M
NEI NIH HHS P30 EY022589NEI NIH HHS R01 EY034146NIH HHS DP5 OD029610
6 · The paper itself

Abstract

Glaucoma is a leading cause of blindness worldwide. Blood pressure (BP) dysregulation is a known risk factor, and home-based BP monitoring is increasingly used, but the usability of digital health devices to measure BP among glaucoma patients is not well studied. There may be particular usability challenges among this group, given that glaucoma disproportionately affects the elderly and can cause visual impairment. Therefore, the goal of this mixed-methods study was to assess the usability of a smart watch digital health device for home BP monitoring among glaucoma patients. Adult participants were recruited and given a smartwatch blood pressure monitor for at-home use. The eHEALS questionnaire was used to determine baseline digital health literacy. After a week of use, participants assessed the usability of the BP monitor and related mobile app using the Post-study System Usability Questionnaire (PSSUQ) and the System Usability Scale (SUS), standardized instruments to measure usability in health information technology interventions. Variations in scores were evaluated using ANOVA and open-ended responses about participants' experience were analyzed thematically. Overall, usability scores corresponded to the 80th-84th percentile, although older patients endorsed significantly worse usability based on quantitative scores and additionally provided qualitative feedback describing some difficulty using the device. Usability for older patients should be considered in the design of digital health devices for glaucoma given their disproportionate burden of disease and challenges in navigating digital health technologies, although the overall high usability scores for the device demonstrates promise for future clinical applications in glaucoma risk stratification.

Indexed as

blood pressuredigital healthgerontechnologyglaucomainclusive designmonitoringpatient-generated datausabilityuser interface

Identifiers

PMID36873830
PMCPMC9980658
OpenAlexW4303709999

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.