Evidence map›Paper›PMID 40513002›Full record

ArticleJMIR formative research2025

Recommendations for Designing a Digital Health Tool for Blindness Prevention Among High-Risk Diabetic Retinopathy Patients: Qualitative Focus Group Study of Adults With Diabetes.

Akua Frimpong, Alvaro Granados, Thomas Chang, Julia Fu, Shannan G Moore, Serina Applebaum, Bolatito Adepoju, Mahima Kaur, Vignesh Hari Krishnan, Amanda Levi and 2 more

Abstract read
In one paragraph

Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

12 authors.

Akua FrimpongDepartment of Ophthalmology and Visual Science, Yale University, 300 George Street, New Haven, CT, 06511, United States, 1 2037763539.ORCID 0009-0002-0308-1013
Alvaro GranadosDepartment of Ophthalmology and Visual Science, Yale University, 300 George Street, New Haven, CT, 06511, United States, 1 2037763539.ORCID 0009-0007-9600-0142
Thomas ChangDepartment of Ophthalmology and Visual Science, Yale University, 300 George Street, New Haven, CT, 06511, United States, 1 2037763539.ORCID 0000-0001-5067-1150
Julia FuDepartment of Ophthalmology and Visual Science, Yale University, 300 George Street, New Haven, CT, 06511, United States, 1 2037763539.ORCID 0000-0003-4351-9534
Shannan G MooreDepartment of Ophthalmology and Visual Science, Yale University, 300 George Street, New Haven, CT, 06511, United States, 1 2037763539.ORCID 0009-0003-9585-7348
Serina ApplebaumDepartment of Ophthalmology and Visual Science, Yale University, 300 George Street, New Haven, CT, 06511, United States, 1 2037763539.ORCID 0000-0001-9062-6178
Bolatito AdepojuDivision of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.ORCID 0009-0000-3451-4091
Mahima KaurDivision of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.ORCID 0000-0001-7147-4084
Vignesh Hari KrishnanDivision of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.ORCID 0009-0005-4354-693X
Amanda LeviDivision of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.ORCID 0009-0009-7031-2927
Terika McCallDivision of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States.ORCID 0000-0002-8143-5393
Kristen Harris NwanyanwuDepartment of Ophthalmology and Visual Science, Yale University, 300 George Street, New Haven, CT, 06511, United States, 1 2037763539.ORCID 0000-0003-1146-7733

Funding

Short Term Research Training: Students in Health Professional SchoolsT35DK104689 · NIDDK · YALE UNIVERSITY · PI LLOYD G CANTLEY, Sarwat I Chaudhry · 2015 to 2026
$2.6M
NIDDK NIH HHS T35 DK104689
6 · The paper itself

Abstract

Background: Diabetic retinopathy (DR) is a leading cause of preventable blindness among working-aged adults. Black, Latine, and low-income individuals are screened less for DR, diagnosed later, treated less often, and go blind more than White individuals. Objective: This study aimed to engage members to co-design a digital health tool that is accessible, user-friendly, and culturally relevant, through a community-led research approach,. Methods: Using a qualitative approach, we conducted 4 semistructured focus group interviews with 19 individuals from the Greater New Haven area, aged 18 years or older, and diagnosed with diabetes. We transcribed and coded the focus group interviews and categorized them into themes using affinity mapping. The specific aims were to complete a comprehensive needs assessmen for the development of a community-responsive digital health tool and to increase access to information about DR screening in high-risk populations. We transcribed the focus group interviews, used rapid qualitative analysis to generate themes, and completed affinity mapping to identify content and features for a digital health tool for preventing blindness from DR. Results: We interviewed 19 individuals (68% [13/19] female, 47% [9/19] Black, 26% [5/19]) Hispanic) in 4 focus groups. Over 80% (15/19) had access to smart devices, including smartphones (17/19, 89%), smartwatches (4/19, 21%), computers (14/19, 74%), and tablets (11/19, 58%). Many participants had access to multiple devices (17/19, 89%). Participants self-reported hemoglobin A1c (mean hemoglobin A1c 6.77, SD 1.93) and age (mean age 58.79, SD 19.54). Education levels among participants varied. Almost half of all the participants (9/19, 47%) completed some college, a little less than a quarter (4/19, 21%) achieved a high school diploma or general education development certificate, and a little less than a quarter (4/19, 21%) completed less than a high school equivalent of education. Household income levels across nearly all participants (14/19, 74%) were below US $50,000, but household size data were not collected. Participants reported extensive experience with diabetes or prediabetes (mean years with diabetes or prediabetes 17.06, SD 17.53). The themes obtained from coding focus group interviews included the mental toll of diabetes, peer support like accountability and local community events, education about diabetes management, barriers to DR screening like long wait times for appointments or cost of medications, and diet-related topics like how to find cost-effective healthy food. Conclusions: DR is one of the leading causes of blindness, and many treatments exist. Despite the existence of treatments, historically marginalized populations experience poor health outcomes, including blindness. Our community-based approach aids in the creation of a culturally responsive digital health tool.

Indexed as

BlindnessDiabetic RetinopathyAdultAgedDigital HealthFemaleFocus GroupsHumansMaleMiddle AgedQualitative Researchapplicationsblindnessdiabetesdiabetes mellitusdiabetic retinopathydigital healthdigital interventionsdigital technologyDMHealth disparitiesmHealthmobile applicationmobile healthneeds assessmentsmartphonestype 1 diabetestype 2 diabetes

Identifiers

PMID40513002
PMCPMC12180678

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.