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• W2396607427 abstract "DIABMEMORY is a telehealth system supporting patients suffering from diabetes mellitus in selfmanagement of their disease. Patients are equipped with a mobile software application running on a Near-FieldCommunication (NFC)-enabled mobile phone to collect essential health parameters, such as glucose levels, blood pressure, well-being, body weight and physical activity on a regular basis. Data are transmitted to a central database, where physicians and diabetes experts can review incoming data and provide patients with a textual feedback (delivered as short text message) on a weekly basis. Physicians are furthermore provided with two default templates. Since 2010, 386 patients have transmitted more than 200,000 datasets. In this work we present a content analysis of 3,519 textual feedbacks written over the course of 9 months. The work is organized as follows: First, we introduce an annotation scheme following based on Taylor’s model for information use. A random sample of 188 feedbacks was selected and annotated by two annotators with experience in the field of telehealth. Each feedback was annotated with one or more categories: Motivational, confirmational, personal or factual. Annotators’ agreement was evaluated using Cohen’s kappa. Second, we trained 6 classifiers (Naive Bayes) based on this annotation to automatically categorize the whole corpus. The classifiers were evaluated using 8-fold cross-validation and were applied to the whole corpus. Furthermore we performed a keyword-analysis extracting top-terms in the categories blood pressure (21 terms), food & nutrition (20 terms), weight (16 terms), medication (7 terms), physical activity (21 terms), well-being (3 terms) and glucose levels (26 terms). Results: Most feedbacks are of motivational nature (60.41 %). Out of 3519 feedbacks, only 19.26% contained confirmational content. In terms of content, the majority of the feedbacks refer to glucose levels (42.95%) and blood pressure 32.98%. While diet has a significant impact on diabetes, only 10.36% of the feedbacks refer to diet instructions. Conclusion: physicians actively use feedbacks, though it is not used to engage in an active dialogue with the patient. It still has to be investigated, why the number of references to diet and nutrition is low compared to advice on glucose and blood pressure." @default.
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• W2396607427 date "2012-01-01" @default.
• W2396607427 modified "2023-09-23" @default.
• W2396607427 title "On the Use of Text Messaging in a Diabetes Telehealth System Results and Evaluation of a Content Analysis." @default.
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