ArticleMayo Clinic proceedings. Digital health2025
Digital Medicine Tools and the Work of Being a Patient: A Qualitative Investigation of Digital Treatment Burden in Patients With Diabetes.
Article in Mayo Clinic proceedings. Digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Impact of Digital Interventions on the Treatment Burden of Patients With Chronic Conditions: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Treatment burden and health-related quality of life in young adults with type 1 diabetes.Diabetic medicine : a journal of the British Diabetic Association · 2026Article
- Artificial Intelligence in Type 1 Diabetes Management: A Scoping Review of Randomised Controlled Trials.Diabetes, obesity & metabolism · 2026Article
- Digital therapeutics use burden in patients with chronic diseases: a scoping review.Frontiers in public health · 2026Article
- Validation of a novel patient-reported measure of the burden of digital care in diabetes.BMC medicine · 2025Article
- Development of the TBQ+D: A Novel Patient-Reported Measure of The Burden of Digital Care.Patient preference and adherence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To understand the contribution of digital medicine tools (eg, continuous glucose monitoring systems, scheduling, and messaging applications) to treatment burden in patients with diabetes. Patients and Methods: Between October and November 2023, we invited patients with type 1 or type 2 diabetes to participate in semistructured interviews. The interviewees completed the Treatment Burden Questionnaire as they reflected on how digital medicine tools affect their daily routines. A published taxonomy of treatment burden guided the qualitative content analysis of interview transcripts. Results: In total, 20 patients agreed to participate and completed interviews (aged 21-77 years, 55% female, 60% living with type 2 diabetes). We found 5 categories of tasks related to the use of digital medicine tools that patients had to complete (eg, calibrating continuous glucose monitors), 3 factors that made these tasks burdensome (eg, cost of device replacements), and 2 categories of consequences of burdensome tasks on patient wellbeing (eg, fatigue from device alarms). Conclusion: Patients identified how digital medicine tools contribute to their treatment burden. The resulting digital burden taxonomy can be used to inform the design, implementation, and prescription of digital medicine tools including support for patients as they normalize them in their lives.
Identifiers
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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.