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dc.contributor.authorErsotelos, Nikolaosen
dc.contributor.authorMargioris, Andrew N.en
dc.contributor.authorZhang, Xuen
dc.contributor.authorDong, Fengen
dc.date.accessioned2018-12-20T13:35:07Z
dc.date.available2018-12-20T13:35:07Z
dc.date.issued2018-10-13
dc.identifier.citationErsotelos NT, Margioris AN, Zhang X, Dong F (2018) 'Review of mobile applications for optimizing the follow-up care of patients with diabetes', Hormones -Athens-, 17 (4), pp.541-550.en
dc.identifier.issn1109-3099
dc.identifier.pmid30317460
dc.identifier.doi10.1007/s42000-018-0062-0
dc.identifier.urihttp://hdl.handle.net/10547/623044
dc.description.abstractSeveral smartphone applications aim at facilitating communication between patients and healthcare providers. In this review, we evaluate and compare the most promising applications in the field of diabetes mellitus (DM) and obesity. Most applications monitor body weight, fasting or postprandial blood glucose, glycosylated hemoglobin (Hgb) A1c (HgbA1c), and units and types of insulin used. Nine clinically tested applications and two Web platforms were grouped into three categories that were evaluated and compared. Group 1 included seven applications focusing mainly on monitoring DM, fitness and weight, blood glucose levels, and HbA1c. Group 2 included two applications that focus on insulin dosage calculators and glucose self-monitoring tests. Group 3 included two web-platforms that interact with patients via SMS (short message service) messaging. A common feature of the applications examined was the limited number of clinical parameters tested, the small number of subjects taking part in the evaluation, and the fact that the controls were not randomized. Furthermore, the interfaces of the applications varied and were not standardized. Finally, another common characteristic across applications was the lack of standardization of the interface and the overall structure due to language barriers, the devices usually having been designed around a specific language. Lastly, most applications lacked a critical mass of evaluators and were thus not worthy of being considered of serious clinical relevance. The current smartphone applications for DM are characterized by a limited number of participants, a small number of parameters, and a lack of standardization. BACKGROUND METHODS RESULTS CONCLUSIONS
dc.language.isoenen
dc.publisherHellenic Endocrine Society/Springeren
dc.relation.urlhttps://link.springer.com/article/10.1007/s42000-018-0062-0en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectDiabetes Mellitusen
dc.subjectmobile applicationsen
dc.subjectG920 Others in Computing Sciencesen
dc.titleReview of mobile applications for optimizing the follow-up care of patients with diabetesen
dc.typeArticleen
dc.identifier.eissn2520-8721
dc.contributor.departmentUniversity of Bedfordshireen
dc.contributor.departmentUniversity of Creteen
dc.identifier.journalHormones -Athens-en
dc.date.updated2018-12-20T13:32:35Z
html.description.abstractSeveral smartphone applications aim at facilitating communication between patients and healthcare providers. In this review, we evaluate and compare the most promising applications in the field of diabetes mellitus (DM) and obesity. Most applications monitor body weight, fasting or postprandial blood glucose, glycosylated hemoglobin (Hgb) A1c (HgbA1c), and units and types of insulin used. Nine clinically tested applications and two Web platforms were grouped into three categories that were evaluated and compared. Group 1 included seven applications focusing mainly on monitoring DM, fitness and weight, blood glucose levels, and HbA1c. Group 2 included two applications that focus on insulin dosage calculators and glucose self-monitoring tests. Group 3 included two web-platforms that interact with patients via SMS (short message service) messaging. A common feature of the applications examined was the limited number of clinical parameters tested, the small number of subjects taking part in the evaluation, and the fact that the controls were not randomized. Furthermore, the interfaces of the applications varied and were not standardized. Finally, another common characteristic across applications was the lack of standardization of the interface and the overall structure due to language barriers, the devices usually having been designed around a specific language. Lastly, most applications lacked a critical mass of evaluators and were thus not worthy of being considered of serious clinical relevance. The current smartphone applications for DM are characterized by a limited number of participants, a small number of parameters, and a lack of standardization. BACKGROUND METHODS RESULTS CONCLUSIONS


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