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

BackgroundPatients with diabetes often manage complex treatment regimens that increasingly include the use of digital medicine tools. While several instruments measure treatment burden, none capture the specific burden introduced by digital medicine tools used in self-care. Development of patient reported measures to capture digital treatment burden are needed to assess the lived experiences and challenges patients face when using digital medicine tools. ObjectiveTo engage patients and clinical experts in adapting an existing measure of treatment burden--the Treatment Burden Questionnaire (TBQ). The adapted instrument underwent cognitive testing and refinements to ensure it could capture the burden of using digital medicine tools in the self-management and care of diabetes. MethodsThis two-phase study was conducted with adults with diabetes and other chronic conditions at the Division of Endocrinology at Mayo Clinic in Rochester, Minnesota. 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 followed an item development guide to generate new items and adapt existing ones to better reflect the workload and burdens imposed by digital medicine tools. The resulting adapted 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. ResultsThe final TBQ+D retained the structure of the original 15-item TBQ and included 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. ConclusionThe TBQ+D appears able to measure digital treatment burden in patients with diabetes. Planned next steps include field testing the instrument to test validity hypotheses, and if successful, extending this evaluation to diverse populations and clinical and research settings.