Evidence map›Paper›PMID 41030516›Full record

ArticlePatient preference and adherence2025

Development of the TBQ+D: A Novel Patient-Reported Measure of The Burden of Digital Care.

Misk Al Zahidy, Kerly Guevara Maldonado, Suvyaktha Simha, Mariana Borras-Osorio, Megan E Branda, Viet-Thi Tran, Jennifer L Ridgeway, Victor M Montori

Abstract read
In one paragraph

Article in Patient preference and adherence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Misk Al ZahidyKnowledge and Evaluation Research Unit, Division of Endocrinology and Diabetes, Mayo Clinic, Rochester, MN, 55905, USA.ORCID 0009-0007-1999-9351
Kerly Guevara MaldonadoKnowledge and Evaluation Research Unit, Division of Endocrinology and Diabetes, Mayo Clinic, Rochester, MN, 55905, USA.ORCID 0000-0003-1881-3571
Suvyaktha SimhaKnowledge and Evaluation Research Unit, Division of Endocrinology and Diabetes, Mayo Clinic, Rochester, MN, 55905, USA.
Mariana Borras-OsorioKnowledge and Evaluation Research Unit, Division of Endocrinology and Diabetes, Mayo Clinic, Rochester, MN, 55905, USA.ORCID 0000-0001-5500-6491
Megan E BrandaKnowledge and Evaluation Research Unit, Division of Endocrinology and Diabetes, Mayo Clinic, Rochester, MN, 55905, USA.
Viet-Thi TranCRESS, INSERM, INRAE, Université Paris Cité, Paris, France.
Jennifer L RidgewayKnowledge and Evaluation Research Unit, Division of Endocrinology and Diabetes, Mayo Clinic, Rochester, MN, 55905, USA.ORCID 0000-0001-7658-6763
Victor M MontoriKnowledge and Evaluation Research Unit, Division of Endocrinology and Diabetes, Mayo Clinic, Rochester, MN, 55905, USA.ORCID 0000-0003-0595-2898

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Patients with diabetes manage complex treatment regimens that include the use of digital medicine tools. Existing instruments do not explicitly capture treatment burden, i.e., workload and its effect on patient's quality of life, from using digital medicine tools. Objective: To engage patients and clinical experts in adapting the Treatment Burden Questionnaire (TBQ) to capture digital treatment burden. The adapted instrument underwent cognitive testing and refinements to ensure it captures the burden of using digital medicine tools in diabetes self-management. Methods: This two-phase study was conducted with adults with diabetes at the Division of Endocrinology at Mayo Clinic (Rochester, MN). First, we mapped themes from prior concept elicitation interviews to existing TBQ items to identify content gaps related to digital burden. Based on these gaps, the study team and expert panel generated new items and adapted existing ones to better reflect the workload and burdens from using digital medicine tools. The resulting instrument underwent three rounds of cognitive testing with adult patients living with diabetes, using a think-aloud protocol to assess clarity, relevance, and comprehensiveness. Results of cognitive testing informed iterative refinements across three rounds of interviews, leading to improved clarity, reduced redundancy, and improved relevance of items. Results: The final TBQ+D retained the original 15-item TBQ structure, added 8 new items, and modified 8 extant ones to capture burden of digital care (e.g, syncing issues, discomfort from sensors, and device malfunctions). Cognitive testing demonstrated strong content relevance and patient comprehension. Conclusion: The TBQ+D can measure digital treatment burden in patients with diabetes. Limitations include a relatively homogeneous sample drawn from a single center. Next steps include field testing for validation across diverse populations and settings.

Indexed as

burden of digital carecognitive interviewingdiabetes mellituspatient-reported outcome measuresself-managementtreatment burden questionnaire

Identifiers

PMID41030516
PMCPMC12477269

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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.