Evidence map›Paper›PMID 35928514›Full record

ArticlemHealth2022

Exploration of a Mobile Technology Vulnerability Scale's association with antiretroviral adherence among young adults living with HIV in the United States.

Parya Saberi, Shadi Eskaf, Chadwick K Campbell, Torsten B Neilands, John A Sauceda, Karine Dubé

Abstract read
In one paragraph

Article in mHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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.

Parya SaberiDivision of Prevention Sciences, University of California, San Francisco, San Francisco, CA, USA.
Shadi EskafSchool of Government, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Chadwick K CampbellDivision of Prevention Sciences, University of California, San Francisco, San Francisco, CA, USA.
Torsten B NeilandsDivision of Prevention Sciences, University of California, San Francisco, San Francisco, CA, USA.
John A SaucedaDivision of Prevention Sciences, University of California, San Francisco, San Francisco, CA, USA.
Karine DubéGillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Funding

Ujima Mentoring ProgramP30MH062246 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MALLORY O JOHNSON · 2001 to 2026
$57.4M
Training Program for Scientists Conducting Research to Reduce HIV Health DisparitR25MH067127 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Emily A Arnold, Torsten Brian Neilands · 2003 to 2026
$5.4M
Perceptions of Risks and Benefits of Participating in HIV Cure-related Research among Diverse Youth and Young Adults Living with HIV in the United StatesR21MH122280 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DUBE, KARINE, SABERI, PARYA · 2020 to 2021
$458k
NIMH NIH HHS P30 MH062246NIMH NIH HHS R21 MH122280NIMH NIH HHS R25 MH067127
6 · The paper itself

Abstract

Background: Young adults living with HIV (YLWH) have suboptimal adherence to antiretroviral therapy (ART) and HIV care outcomes. Mobile health technologies are increasingly used to deliver interventions to address HIV health outcomes. However, not all YLWH have equal and consistent access to mobile technologies. Methods: Using our novel Mobile Technology Vulnerability Scale (MTVS) to evaluate how vulnerable an individual feels with regard to their personal access to mobile technology in the past 6 months, we conducted a cross-sectional online survey with 271 YLWH (18-29 years) in the US to evaluate the relationships between MTVS and self-reported ART adherence. Results: Participants reported changes in phone numbers (25%), stolen (14%) or lost (22%) phones, and disconnections of phone service due to non-payment (39%) in the past 6 months. On a scale of 0 to 1 (0 having no mobile technology vulnerability and 1 having complete mobile technology vulnerability), participants had a mean MTVS of 0.33 (SD =0.26). Black and financially constrained participants had the highest MTVS, which was significantly higher that other racial/ethnic and financially non-constrained groups, respectively. Higher MTVS was significantly associated with ART non-adherence and non-persistence. Conclusions: Findings suggest the need to measure MTVS to recognize pitfalls when using mobile health interventions and identify populations whose inconsistent mobile technology access may be related to worse health outcomes.

Indexed as

adherenceantiretroviral therapy (ART)mobile technologyvulnerability scaleYouth living with HIV

Identifiers

PMID35928514
PMCPMC9343971

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.