Misk Al Zahidy, Kerly Guevara Maldonado, Suvyaktha Simha, Mariana Borras-Osorio, Megan E Branda, Viet-Thi Tran, Jennifer L Ridgeway, Victor M Montori
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The adapted instrument underwent cognitive testing and refinements to ensure it captures the burden of using digital medicine tools in diabetes self-management.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":19972,"journal":{"name":"Patient preference and adherence","volume":"19 ","pages":"2975-2984"},"PeriodicalIF":2.0000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12477269/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development of the TBQ+D: A Novel Patient-Reported Measure of The Burden of Digital Care.\",\"authors\":\"Misk Al Zahidy, Kerly Guevara Maldonado, Suvyaktha Simha, Mariana Borras-Osorio, Megan E Branda, Viet-Thi Tran, Jennifer L Ridgeway, Victor M Montori\",\"doi\":\"10.2147/PPA.S540026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>The TBQ+D can measure digital treatment burden in patients with diabetes. Limitations include a relatively homogeneous sample drawn from a single center. 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Development of the TBQ+D: A Novel Patient-Reported Measure of The Burden of Digital Care.
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.
期刊介绍:
Patient Preference and Adherence is an international, peer reviewed, open access journal that focuses on the growing importance of patient preference and adherence throughout the therapeutic continuum. The journal is characterized by the rapid reporting of reviews, original research, modeling and clinical studies across all therapeutic areas. Patient satisfaction, acceptability, quality of life, compliance, persistence and their role in developing new therapeutic modalities and compounds to optimize clinical outcomes for existing disease states are major areas of interest for the journal.
As of 1st April 2019, Patient Preference and Adherence will no longer consider meta-analyses for publication.