Evidence map›Paper›PMID 36040186›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2023

A tale of two applications: lessons learned from national LMIC COVID applications.

Mitchell J Winkie, Vinod E Nambudiri

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Global Health Informatics: the state of research and lessons learned.Journal of the American Medical Informatics Association : JAMIA · 2023
    Article
  5. 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

2 authors.

Mitchell J WinkieDepartment of Dermatology, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Vinod E NambudiriDepartment of Dermatology, Brigham and Women's Hospital, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mobile health (mHealth) technologies in low- and middle-income countries (LMICs) have received increased attention for the significant potential benefits they can bring to underserved populations. As smartphones are becoming increasingly accessible, many stakeholders in the mHealth space have begun exploring smartphone applications as a means to impact individuals living within LMICs. With the COVID-19 pandemic straining healthcare systems around the world, many governments in LMICs turned to use smartphone applications to help support and manage their pandemic responses. By analyzing national COVID-19 applications created and launched by the Indian and Vietnamese governments, we highlight effective application functions and strategies, summarizing best practices for future LMIC application development.

Indexed as

COVID-19Mobile ApplicationsTelemedicineDelivery of Health CareDeveloping CountriesHumansPandemicsSmartphonecomparative analysisCOVID-19 applicationsIndiaLMICsmHealthmobile healthtechnologyVietnam

Identifiers

PMID36040186
PMCPMC9452142

What OpenQuestion holds

Textmetadata
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.