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1000
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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Background</jats:title>
<jats:p>Mobile health (mhealth) is gaining interest, with mobile devices and apps being ever more available among medical facilities and patients. However, in the field of radiation oncology, the medical benefits of mhealth apps are still underexplored. As an additional approach to patient care during radiotherapy, we designed a mobile treatment surveillance app based on patient-reported outcomes.</jats:p>
</jats:sec><jats:sec>
<jats:title>Objective</jats:title>
<jats:p>We aimed to examine the feasibility of app-based treatment surveillance in patients undergoing radiotherapy (RT). Alongside technical practicability and acceptance, we assessed patient satisfaction and quality of life during treatment.</jats:p>
</jats:sec><jats:sec>
<jats:title>Methods</jats:title>
<jats:p>This prospective single-center study was performed at Heidelberg University Hospital between August 2018 and January 2020. During RT we measured patients’ quality of life, symptoms, and treatment satisfaction. Respective questionnaires (EORTC QLQ-C30 with diagnosis-specific modules, RAND PSQ-18) were presented to patients via a mobile app running on a designated tablet device. The primary endpoint was determined by the fraction of patients who completed at least 80% of the items. Secondary endpoints were disease-related quality of life and patient satisfaction.</jats:p>
</jats:sec><jats:sec>
<jats:title>Results</jats:title>
<jats:p>A total of 49 cancer patients (14 breast, 13 pelvic, 12 lung, 10 prostate) were eligible for analysis. 79.6% (95% confidence interval: 66.4–88.5%; <jats:italic>n</jats:italic> = 39) of all patients completed at least 80% of the items received by the mobile app. A mean of 227.5 ± 48.25 questions were answered per patient. Breast cancer patients showed the highest rate of answered questions, with 92.9% (<jats:italic>n</jats:italic> = 13) completing at least 80% of the items.</jats:p>
</jats:sec><jats:sec>
<jats:title>Conclusion</jats:title>
<jats:p>Patients showed high acceptance, with 79.6% (<jats:italic>n</jats:italic> = 39) completing at least 80% of the given items. The use of a mobile app for reporting symptoms and quality of life during RT is feasible and well accepted by patients. It may allow for resource-efficient, detailed feedback to the medical staff and assist in the assessment of side effects over time.</jats:p>
</jats:sec>
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1000
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Hinweis
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DeepGreen-ID: 27ab261bb9854ba6863f675babd05a49 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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