Evidence map›Paper›PMID 39530052›Full record

ArticleJAMIA open2024

Indications of digital literacy during Latino-focused, community-based COVID-19 testing implementation.

Patric V Prado, Carina Arechiga, Kara Marson, Yolanda Oviedo, Tatiana Vizcaíno, Monica Gomez, Arandu Alvarez, Laura Jimenez-Diecks, Sindy Guevara, Alexandra Nava and 5 more

Abstract read
In one paragraph

Article in JAMIA open, 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

15 authors.

Patric V PradoDepartment of Medicine, University of California, San Francisco, San Francisco, CA 94110, United States.ORCID https://orcid.org/0000-0002-9097-6802
Carina ArechigaDepartment of Medicine, University of California, San Francisco, San Francisco, CA 94110, United States.
Kara MarsonDepartment of Medicine, University of California, San Francisco, San Francisco, CA 94110, United States.
Yolanda OviedoCanal Alliance, San Rafael, CA 94901, United States.
Tatiana VizcaínoUnited Way of Merced, Merced, CA 95340, United States.
Monica GomezUnited Way of Merced, Merced, CA 95340, United States.
Arandu AlvarezCanal Alliance, San Rafael, CA 94901, United States.
Laura Jimenez-DiecksCanal Alliance, San Rafael, CA 94901, United States.
Sindy GuevaraCanal Alliance, San Rafael, CA 94901, United States.
Alexandra NavaCanal Alliance, San Rafael, CA 94901, United States.
Zully LopezCanal Alliance, San Rafael, CA 94901, United States.
Omar CarreraCanal Alliance, San Rafael, CA 94901, United States.
Robert HypesUnited Way of Merced, Merced, CA 95340, United States.
Carina MarquezDepartment of Medicine, University of California, San Francisco, San Francisco, CA 94110, United States.ORCID https://orcid.org/0000-0002-7622-6562
Gabriel ChamieDepartment of Medicine, University of California, San Francisco, San Francisco, CA 94110, United States.ORCID https://orcid.org/0000-0002-5860-8081

Funding

Virology CoreP30AI027763 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI STEVEN Grant DEEKS · 1988 to 2026
$93.6M
Mentorship in patient-oriented research to optimize community-based HIV prevention for adults at high-risk of HIV at alcohol drinking venues in East AfricaK24AA031211 · NIAAA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Gabriel Chamie · 2023 to 2026
$785k
NIAAA NIH HHS K24 AA031211NIAID NIH HHS P30 AI027763
6 · The paper itself

Abstract

Objective: We sought to characterize indicators of digital literacy among persons testing for COVID-19 and community health workers (CHWs) providing testing via a digital platform in low-income, majority-Latino communities in California. Materials and Methods: From March 2021 to March 2022, we trained CHWs to provide community-based COVID-19 testing that relied on a digital platform for registration, recording and reporting of results. Among community members, we examined factors associated with accessing test results digitally and time to results receipt. Among CHWs, we evaluated factors associated with self-reported difficulty using the digital platform and improvement post-training. Results: Overall, 5044 community members were tested for COVID-19. Accessing results digitally vs non-digitally was associated with younger age (Odds Ratio [OR]: 1.02 [95% Confidence Interval [CI], 1.01-1.03], for each year decrease), rural residence (OR:1.61 [95% CI, 1.30-1.99]), and providing an email address at registration (OR: 2.18 [95% CI, 1.80-2.65]). The likelihood of providing an email address at registration was increased among younger, non-Latino, English-speaking, female, and rural testers. Among persons accessing results digitally, median time from testing to result receipt was 41 min, with increased time associated with rural residence and older age. Among 42 CHWs surveyed, 29 (68%) reported technology-related challenges when providing testing: those reporting challenges were more likely to be older and rural CHWs. Rural CHWs were less likely to report technical skill improvement post-training. Discussion: Email provision may be an indicator of digital literacy among persons testing for COVID-19 in low-income, majority-Latino communities. Rural and older CHWs may need more intensive digital training. Conclusion: Efforts to improve digital literacy in underserved communities are likely needed to realize the full potential of community-based health interventions that utilize digital platforms.

Indexed as

community health workerCOVID-19digital literacyinformatics

Identifiers

PMID39530052
PMCPMC11552631

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.