Evidence mapPaperPMID 40131316Full record

ArticleJMIR diabetes2025

Examining How Adults With Diabetes Use Technologies to Support Diabetes Self-Management: Mixed Methods Study.

Timothy Bober, Sophia Garvin, Jodi Krall, Margaret Zupa, Carissa Low, Ann-Marie Rosland

Abstract read
In one paragraph

Article in JMIR diabetes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Timothy Bober *Caring for Complex Chronic Conditions Research Center, Department of Medicine, Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0002-5313-2387
Sophia Garvin *Caring for Complex Chronic Conditions Research Center, Department of Medicine, Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID https://orcid.org/0009-0009-7070-8155
Jodi Krall *University of Pittsburgh Medical Center, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0002-9798-0345
Margaret Zupa *Caring for Complex Chronic Conditions Research Center, Department of Medicine, Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0002-8244-9295
Carissa Low *Mobile Sensing + Health Institute (MoSHI), Department of Medicine, Division of Hematology/Oncology, University of Pittsburgh, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0002-3318-7495
Ann-Marie Rosland *Caring for Complex Chronic Conditions Research Center, Department of Medicine, Division of General Internal Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID https://orcid.org/0000-0002-5809-5861

Funding

J. NRSA Training CoreTL1TR001858 · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2025 to 2025
$930k
Understanding the Impact of Digital Health Literacy and Health Supporters on Technology Use for Self-Management among Adults with Type 2 DiabetesR01DK136788 · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2025 to 2025
$553k
NCATS NIH HHS TL1 TR001858NIDDK NIH HHS R01 DK136788
6 · The paper itself

Abstract

backgroundTechnologies such as mobile apps, continuous glucose monitors (CGMs), and activity trackers are available to support adults with diabetes, but it is not clear how they are used together for diabetes self-management.

objectiveThis study aims to understand how adults with diabetes with differing clinical profiles and digital health literacy levels integrate data from multiple behavior tracking technologies for diabetes self-management.

methodsAdults with type 1 or 2 diabetes who used ≥1 diabetes medications responded to a web-based survey about health app and activity tracker use in 6 categories: blood glucose level, diet, exercise and activity, weight, sleep, and stress. Digital health literacy was assessed using the Digital Health Care Literacy Scale, and general health literacy was assessed using the Brief Health Literacy Screen. We analyzed descriptive statistics among respondents and compared health technology use using independent 2-tailed t tests for continuous variables, chi-square for categorical variables, and Fisher exact tests for digital health literacy levels. Semistructured interviews examined how these technologies were and could be used to support daily diabetes self-management. We summarized interview themes using content analysis.

resultsOf the 61 survey respondents, 21 (34%) were Black, 23 (38%) were female, and 29 (48%) were aged ≥45 years; moreover, 44 (72%) had type 2 diabetes, 36 (59%) used insulin, and 34 (56%) currently or previously used a CGM. Respondents had high levels of digital and general health literacy: 87% (46/53) used at least 1 health app, 59% (36/61) had used an activity tracker, and 62% (33/53) used apps to track ≥1 health behaviors. CGM users and nonusers used non-CGM health apps at similar rates (16/28, 57% vs 12/20, 60%; P=.84). Activity tracker use was also similar between CGM users and nonusers (20/33, 61% vs 14/22, 64%; P=.82). Respondents reported sharing self-monitor data with health care providers at similar rates across age groups (17/32, 53% for those aged 18-44 y vs 16/29, 55% for those aged 45-70 y; P=.87). Combined activity tracker and health app use was higher among those with higher Digital Health Care Literacy Scale scores, but this difference was not statistically significant (P=.09). Interviewees (18/61, 30%) described using blood glucose level tracking apps to personalize dietary choices but less frequently used data from apps or activity trackers to meet other self-management goals. Interviewees desired data that were passively collected, easily integrated across data sources, visually presented, and tailorable to self-management priorities.

conclusionsAdults with diabetes commonly used apps and activity trackers, often alongside CGMs, to track multiple behaviors that impact diabetes self-management but found it challenging to link tracked behaviors to glycemic and diabetes self-management goals. The findings indicate that there are untapped opportunities to integrate data from apps and activity trackers to support patient-centered diabetes self-management.

Indexed as

continuous glucose monitorsdiabetesdigital health literacyhealth technologymobile healthself-management

Identifiers

PMID40131316
PMCPMC11979526

What Socratic 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 Socratic graph.