ArticleHealth science reports2026
Design and Validation of a Minimum Dataset for a Self-Care Mobile Application for Patients With Diabetic Retinopathy: Descriptive-Validation Study.
Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aim: Diabetic retinopathy is one of the most common microvascular complications of diabetes, with over 100 million people affected worldwide. The development of mobile health applications can play an effective role in managing and monitoring diabetic retinopathy. Still, the development of these applications first requires the identification of the minimum dataset. Therefore, the purpose of this study is to identify and determine the minimum dataset as the first step in designing a self-care mobile application for patients with diabetic retinopathy. Methods: This Descriptive-Validation Study was conducted in 2025 in two phases: design and validation of the MDS. In the first phase, a comprehensive review of the research literature was conducted and electronic databases such as PubMed, Web of Science, Scopus, and Google Scholar were searched until October 2024. Then, data elements were extracted and identified. In the second phase, these elements were validated by 20 experts from the fields of endocrinology, ophthalmology, and health information management using the Delphi technique. Then, in order to include patients' opinions, a researcher-made questionnaire was administered to 20 patients with diabetic retinopathy. Results: Fifty-five MDS elements were validated in three domains: administrative, clinical, and functional data, using two rounds of the Delphi technique. Data elements with over 75% expert approval were included in the final dataset: 13 administrative, 19 clinical, and 19 functional elements. Conclusion: The Ministry of Health and Medical Education, app designers, and developers can utilize the findings of this study to develop a high-quality application that addresses the educational and informational needs of patients with diabetic retinopathy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.