Evidence map›Paper›PMID 39850857›Full record

ArticleFrontiers in public health2024

A health security-based framework for prioritizing regions for digital learning in complex health emergencies.

Shawn M D'Andrea, Nada Fadul, Bruce Struminger

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Shawn M D'AndreaBrigham and Women's Hospital, Boston, MA, United States.
Nada FadulDepartment of Internal Medicine, University of Nebraska Medical Center College of Medicine, Omaha, NE, United States.
Bruce StrumingerECHO Institute and Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital health and learning have expanded significantly in recent decades though their use in settings of acute health emergencies has only recently begun. Growing experience among organizations working in the digital health and learning space suggest that virtual communities of practice in these areas may have value in response to health emergencies. Evaluation of recent virtual programs applied in acute health emergencies suggest that a pre-established digital learning network can serve as a valuable resource when an acute health emergency strikes. This paper introduces the concept, and explores the potential value of developing a prioritization framework, informed by health security assessments, to identify countries most vulnerable to future health crises. By using an anticipatory approach and framework to identify high risk regions, digital learning programs can be developed proactively, building networks that can be activated during emergencies. Creating and prioritizing virtual learning networks in regions at high risk of health emergencies can improve response capacities. Developing a framework to identify countries and regions of greatest risk can help policy makers, educators, and donors, focus limited resources on high need areas.

Indexed as

Disaster PlanningEmergenciesHumansdigital learninghealth emergencieshealth securityhealth security indexhumanitarian responseregional prioritization

Identifiers

PMID39850857
PMCPMC11754180

What OpenQuestion holds

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LicenceCC BY
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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.