Evidence map›Paper›PMID 37607881›Full record

ArticleJMIR formative research2023

The Vinyasa Tool for mHealth Solutions: Supporting Human-Centered Design in Nascent Digital Health Ecosystems.

Verghese Thomas, Bharat Kalidindi, Abijeet Waghmare, Abhishek Bhatia, Tony Raj, Satchit Balsari

Abstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
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

6 authors.

Verghese ThomasDivision of Medical Informatics, St John's Research Institute, Bangalore, India.ORCID https://orcid.org/0000-0003-4153-2903
Bharat KalidindiDivision of Medical Informatics, St John's Research Institute, Bangalore, India.ORCID https://orcid.org/0000-0002-7613-1336
Abijeet WaghmareDivision of Medical Informatics, St John's Research Institute, Bangalore, India.ORCID https://orcid.org/0000-0003-4333-0010
Abhishek BhatiaCarolina Health Informatics Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID https://orcid.org/0000-0002-0063-368X
Tony Raj *Division of Medical Informatics, St John's Research Institute, Bangalore, India.ORCID https://orcid.org/0000-0003-3959-4718
Satchit Balsari *Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.ORCID https://orcid.org/0000-0002-5492-1900

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundmHealth (mobile health) systems have been deployed widely in low- and middle-income countries (LMICs) for health system strengthening, requiring considerable resource allocation. However, most solutions have not achieved scale or sustainability. Poor usability and failure to address perceived needs are among the principal reasons mHealth systems fail to achieve acceptance and adoption by health care workers. A human-centered design approach to improving mHealth system use requires an exploration of users' perceptions of mHealth systems, including the environmental, user-related, and technological aspects of a system. At present, there is a dearth of contextually intelligent tools available to mHealth developers that can guide such exploration before full-scale development and deployment.

objectiveTo develop a tool to aid optimization of mHealth solutions in LMICs to facilitate human-centered design and, consequently, successful adoption.

methodsWe collated findings and themes from key qualitative studies on mHealth deployment in LMICs. We then used the Informatics Stack framework by Lehmann to label, sort, and collate findings and themes into a list of questions that explore the environment, users, artifacts, information governance, and interoperability of mHealth systems deployed in LMICs.

resultsWe developed the Vinyasa Tool to aid qualitative research about the need and usability of mHealth solutions in LMICs. The tool is a guide for focus group discussions and key informant interviews with community-based health care workers and primary care medical personnel who use or are expected to use proposed mHealth solutions. The tool consists of 71 questions organized in 11 sections that unpack and explore multiple aspects of mHealth systems from the perspectives of their users. These include the wider world and organization in which an mHealth solution is deployed; the roles, functions, workflow, and adoption behavior of a system's users; the security, privacy, and interoperability afforded by a system; and the artifacts of an information system-the data, information, knowledge, algorithms, and technology that constitute the system. The tool can be deployed in whole or in part, depending on the context of the study.

conclusionsThe Vinyasa Tool is the first such comprehensive qualitative research instrument incorporating questions contextualized to the LMIC setting. We expect it to find wide application among mHealth developers, health system administrators, and researchers developing and deploying mHealth tools for use by patients, providers, and administrators. The tool is expected to guide users toward human-centered design with the goal of improving relevance, usability, and, therefore, adoption.

Indexed as

community health workersdigital healthfocus group discussionshealth care workershuman centered designkey informant interviewsLMICslow- and middle-income countriesmHealthmobile healthqualitative research

Identifiers

PMID37607881
PMCPMC10580130

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.