Evidence map›Paper›PMID 42381900›Full record

ArticleFrontiers in public health2026

Democratizing computational skills: evaluating an asynchronous microlearning framework for cloud-based data analytics in health services research.

Yulia A Levites Strekalova, Rachel Liu-Galvin, Mishal Khan, Eva Lee, Ernest Alema-Mensah, Elizabeth Ofili

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. 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

6 authors.

Yulia A Levites StrekalovaDepartment of Health Services Research, Management, and Policy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States.
Rachel Liu-GalvinDepartment of Health Services Research, Management, and Policy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States.
Mishal KhanDepartment of Health Services Research, Management, and Policy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States.
Eva LeeData and Analytics Innovation Institute, Atlanta, GA, United States.
Ernest Alema-MensahMorehouse School of Medicine, Atlanta, GA, United States.
Elizabeth OfiliMorehouse School of Medicine, Atlanta, GA, United States.

Funding

Urgent Competitive Revision to Existing NIH Grants and Cooperative Agreements (Urgent Supplement - Clinical Trial Optional)U24MD015970 · NIMHD · MOREHOUSE SCHOOL OF MEDICINE · PI Sandra Perreira Chang, Elizabeth O. Ofili · 2020 to 2026
$20.6M
NIMHD NIH HHS U24 MD015970
6 · The paper itself

Abstract

Background: Public health is undergoing a digital transformation, with increasing reliance on data-driven decision-making that requires proficiency in computational tools. However, traditional curricula often emphasize theoretical knowledge over applied technical skills, contributing to gaps in workforce readiness. This study evaluated a pilot remote, asynchronous microlearning course designed to expand access to digital skills-specifically R and Google Colab-among students from historically underrepresented backgrounds within the Research Centers in Minority Institutions (RCMI) network. Methods: A three-week course, " Results: Mean objective knowledge scores increased significantly from 3.58 to 4.37 ( Conclusion: Brief, asynchronous microlearning experiences can effectively build foundational computational skills and expand access to training for students in low-resourced settings. While technical competencies can be developed within short, flexible formats, more complex skills such as scientific communication may require additional instructional time and support.

Indexed as

Cloud ComputingData AnalyticsHealth Services ResearchCurriculumHumansPilot Projectsasynchronous learningcomputational skillsdata analyticshealth service researchworkforce development

Identifiers

PMID42381900
PMCPMC13314753

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.