Evidence map›Paper›PMID 41732179›Full record

ArticleDigital health

Usability, user experience, and workflow readiness of a digital health solution for publicly insured pregnant individuals living with type 2 diabetes.

Naleef Fareed, Christine Swoboda, Yiting Wang, Joshua J Joseph, Kartik K Venkatesh

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

5 authors.

Naleef FareedDepartment of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH, USA.ORCID https://orcid.org/0000-0001-8764-1625
Christine SwobodaDepartment of Family and Community Medicine, College of Medicine, The Ohio State University, Columbus, OH, USA.
Yiting WangDepartment of Research Information Technology, College of Medicine, The Ohio State University, Columbus, OH, USA.
Joshua J JosephDepartment of Internal Medicine, Division of Endocrinology, Diabetes, and Metabolism, The Ohio State University, Columbus, OH, USA.
Kartik K VenkateshDepartment of Obstetrics and Gynecology, Division of Maternal Fetal Medicine, The Ohio State University, Columbus, OH, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We conducted usability sessions with publicly insured pregnant individuals living with type 2 diabetes (T2D) and unmet social needs, and their care team members to assess: (1) interface usability, (2) user experience, and (3) clinical workflow integration facets of a high-fidelity prototype of our multi-component digital solution to refine user specifications for the randomized controlled trial (RCT). Methods: Five patients and eight care team members from a tertiary Diabetes in Pregnancy Program participated between March and July 2023. Data collection included think-aloud sessions, empathy mapping, and semi-structured discussions guided by the double diamond framework. Transcripts were coded by four researchers, with saturation assessed across participants. Personas were created grounded in Social Cognitive Theory. Usability feedback was synthesized using affinity diagramming and IBM prioritization matrices. We conducted a reference-based validation study in which care members addressed persona-driven scenarios; proficiency, efficiency, and concordance with expert recommendations were calculated to identify areas for refinement. Results: We identified 21 desired mHealth and six dashboard topics. The top three mHealth topic frequencies were personalized prompts (85%), learning card content (62%), and glucose tracking (62%). The top three dashboard topics were prioritized clinical and social needs pathways (63%), social needs risk levels (50%), and glucose tracking (50%). Three personas emerged: (1) "hands off," (2) "overwhelmed but trying," and (3) "engaged." In the validation study, concordance varied: goal setting showed 100% concordance, while social needs referrals had the highest discordance (60%). Average proficiency and efficiency scores across scenarios were 40% and 37%, respectively, with the lowest agreement for "engaged" persona scenarios. Conclusion: Patients and care team members identified highly valued and implementation-challenging features using our prototypes. The personas highlighted distinct engagement needs, and validation results underscored variability in concordance for social needs management. These findings inform pre-RCT refinements of the digital solution.

Indexed as

dashboarddiabetes managementmobile applicationPregnancyuser-centered

Identifiers

PMID41732179
PMCPMC12925030

What OpenQuestion holds

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LicenceCC BY-NC
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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.