Evidence map›Paper›PMID 42727061›Full record

ArticleJMIR formative research2026

Assessment of Technology Usage and Literacy From a Patient Tech Testing Panel in an Adult Primary Care Practice: Cross-Sectional Study.

Antony Nguyen, Tiffany Chinn, Anthony Louie, Eric Chu, Ashwin Vasudevan, Jane Jih

Abstract read
In one paragraph

Article in JMIR formative research, 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.

Antony NguyenDivision of General Internal Medicine, University of California, San Francisco, 1545 Divisadero St, San Francisco, CA, 94143, United States, 1 4158857563.ORCID http://orcid.org/0009-0007-5696-0229
Tiffany ChinnDivision of General Internal Medicine, University of California, San Francisco, 1545 Divisadero St, San Francisco, CA, 94143, United States, 1 4158857563.ORCID http://orcid.org/0009-0002-5526-0697
Anthony LouieDivision of General Internal Medicine, University of California, San Francisco, 1545 Divisadero St, San Francisco, CA, 94143, United States, 1 4158857563.ORCID http://orcid.org/0009-0000-9386-4614
Eric ChuDivision of General Internal Medicine, University of California, San Francisco, 1545 Divisadero St, San Francisco, CA, 94143, United States, 1 4158857563.ORCID http://orcid.org/0009-0009-5365-1476
Ashwin VasudevanDivision of General Internal Medicine, University of California, San Francisco, 1545 Divisadero St, San Francisco, CA, 94143, United States, 1 4158857563.ORCID http://orcid.org/0009-0006-1087-060X
Jane JihDivision of General Internal Medicine, University of California, San Francisco, 1545 Divisadero St, San Francisco, CA, 94143, United States, 1 4158857563.ORCID http://orcid.org/0000-0001-9367-7376

Funding

Addressing Contextual Factors in Chronic Disease Management in Minority Older Adults through Photo-based Patient-Clinician CommunicationK23MD015089 · NIMHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JIH, JANE · 2021 to 2025
$874k
AHRQ HHS U18 HS026883NIMHD NIH HHS K23 MD015089
6 · The paper itself

Abstract

Unlabelled: Tech testing panels (TTPs) can assess the usability of patient-facing health technology and provide critical feedback; TTPs should draw upon diverse patient populations by language preference and with a range of technology usage and literacy to ensure that digital health interventions are equitably designed.

Indexed as

Health LiteracyAdultCross-Sectional StudiesDigital HealthFemaleHumansPrimary Health CareSurveys and Questionnairesdigital healthlanguage barriersprimary caretechnology literacytech testing panel

Identifiers

PMID42727061
PMCPMC13568595

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.