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      Long-Term Engagement With a Mobile Self-Management System for People With Type 2 Diabetes

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          Abstract

          Background

          In a growing number of intervention studies, mobile phones are used to support self-management of people with Type 2 diabetes mellitus (T2DM). However, it is difficult to establish knowledge about factors associated with intervention effects, due to considerable differences in research designs and outcome measures as well as a lack of detailed information about participants’ engagement with the intervention tool.

          Objective

          To contribute toward accumulating knowledge about factors associated with usage and usability of a mobile self-management application over time through a thorough analysis of multiple types of investigation on each participant’s engagement.

          Methods

          The Few Touch application is a mobile-phone–based self-management tool for patients with T2DM. Twelve patients with T2DM who have been actively involved in the system design used the Few Touch application in a real-life setting from September 2008 until October 2009. During this period, questionnaires and semistructured interviews were conducted. Recorded data were analyzed to investigate usage trends and patterns. Transcripts from interviews were thematically analyzed, and the results were further analyzed in relation to the questionnaire answers and the usage trends and patterns.

          Results

          The Few Touch application served as a flexible learning tool for the participants, responsive to their spontaneous needs, as well as supporting regular self-monitoring. A significantly decreasing ( P<.05) usage trend was observed among 10 out of the 12 participants, though the magnitude of the decrease varied widely. Having achieved a sense of mastery over diabetes and experiences of problems were identified as reasons for declining motivation to continue using the application. Some of the problems stemmed from difficulties in integrating the use of the application into each participant’s everyday life and needs, although the design concepts were developed in the process where the participants were involved. The following factors were identified as associated with usability and/or usage over time: Integration with everyday life; automation; balance between accuracy and meaningfulness of data with manual entry; intuitive and informative feedback; and rich learning materials, especially about foods.

          Conclusion

          Many grounded design implications were identified through a thorough analysis of results from multiple types of investigations obtained through a year-long field trial of the Few Touch application. The study showed the importance and value of involving patient-users in a long-term trial of a tool to identify factors influencing usage and usability over time. In addition, the study confirmed the importance of detailed analyses of each participant’s usage of the provided tool for better understanding of participants’ engagement over time.

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          Most cited references64

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          Adherence to long-term therapies: evidence for action.

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            Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis.

              To assess the effect of mobile phone intervention on glycaemic control in diabetes self-management. We searched three electronic databases (PubMed, EMBASE and Cochrane Library) using the following terms: diabetes or diabetes mellitus and mobile phone or cellular phone, or text message. We also manually searched reference lists of relevant papers to identify additional studies. Clinical studies that used mobile phone intervention and reported changes in glycosylated haemoglobin (HbA(1c) ) values in patients with diabetes were reviewed. The study design, intervention methods, sample size and clinical outcomes were extracted from each trial. The results of the HbA(1c) change in the trials were pooled using meta-analysis methods.   A total of 22 trials were selected for the review. Meta-analysis among 1657 participants showed that mobile phone interventions for diabetes self-management reduced HbA(1c) values by a mean of 0.5% [6 mmol/mol; 95% confidence interval, 0.3-0.7% (4-8 mmol/mol)] over a median of 6 months follow-up duration. In subgroup analysis, 11 studies among Type 2 diabetes patients reported significantly greater reduction in HbA(1c) than studies among Type 1 diabetes patients [0.8 (9 mmol/mol) vs. 0.3% (3 mmol/mol); P=0.02]. The effect of mobile phone intervention did not significantly differ by other participant characteristics or intervention strategies.   Results pooled from the included trials provided strong evidence that mobile phone intervention led to statistically significant improvement in glycaemic control and self-management in diabetes care, especially for Type 2 diabetes patients. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.
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              Features of Mobile Diabetes Applications: Review of the Literature and Analysis of Current Applications Compared Against Evidence-Based Guidelines

              Background Interest in mobile health (mHealth) applications for self-management of diabetes is growing. In July 2009, we found 60 diabetes applications on iTunes for iPhone; by February 2011 the number had increased by more than 400% to 260. Other mobile platforms reflect a similar trend. Despite the growth, research on both the design and the use of diabetes mHealth applications is scarce. Furthermore, the potential influence of social media on diabetes mHealth applications is largely unexplored. Objective Our objective was to study the salient features of mobile applications for diabetes care, in contrast to clinical guideline recommendations for diabetes self-management. These clinical guidelines are published by health authorities or associations such as the National Institute for Health and Clinical Excellence in the United Kingdom and the American Diabetes Association. Methods We searched online vendor markets (online stores for Apple iPhone, Google Android, BlackBerry, and Nokia Symbian), journal databases, and gray literature related to diabetes mobile applications. We included applications that featured a component for self-monitoring of blood glucose and excluded applications without English-language user interfaces, as well as those intended exclusively for health care professionals. We surveyed the following features: (1) self-monitoring: (1.1) blood glucose, (1.2) weight, (1.3) physical activity, (1.4) diet, (1.5) insulin and medication, and (1.6) blood pressure, (2) education, (3) disease-related alerts and reminders, (4) integration of social media functions, (5) disease-related data export and communication, and (6) synchronization with personal health record (PHR) systems or patient portals. We then contrasted the prevalence of these features with guideline recommendations. Results The search resulted in 973 matches, of which 137 met the selection criteria. The four most prevalent features of the applications available on the online markets (n = 101) were (1) insulin and medication recording, 63 (62%), (2) data export and communication, 61 (60%), (3) diet recording, 47 (47%), and (4) weight management, 43 (43%). From the literature search (n = 26), the most prevalent features were (1) PHR or Web server synchronization, 18 (69%), (2) insulin and medication recording, 17 (65%), (3) diet recording, 17 (65%), and (4) data export and communication, 16 (62%). Interestingly, although clinical guidelines widely refer to the importance of education, this is missing from the top functionalities in both cases. Conclusions While a wide selection of mobile applications seems to be available for people with diabetes, this study shows there are obvious gaps between the evidence-based recommendations and the functionality used in study interventions or found in online markets. Current results confirm personalized education as an underrepresented feature in diabetes mobile applications. We found no studies evaluating social media concepts in diabetes self-management on mobile devices, and its potential remains largely unexplored.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications Inc. (Toronto, Canada )
                2291-5222
                Jan-Jun 2013
                27 March 2013
                : 1
                : 1
                : e1
                Affiliations
                [1] 1Norwegian Centre for Integrated Care and Telemedicine University Hospital of North Norway TromsøNorway
                [2] 2Department of Computer Science University of Tromsø TromsøNorway
                [3] 3Design of Information Systems Group Department of Informatics University of Oslo OsloNorway
                Author notes
                Corresponding Author: Naoe Tatara naoe.tatara@ 123456telemed.no
                Article
                v1i1e1
                10.2196/mhealth.2432
                4114413
                25100649
                d907a99a-ebf8-4280-ba4e-804114963083
                ©Naoe Tatara, Eirik Årsand, Stein Olav Skrøvseth, Gunnar Hartvigsen. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 27.03.2013.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 12 November 2012
                : 06 December 2012
                : 31 January 2013
                : 25 February 2013
                Categories
                Original Paper
                Original Paper

                type 2 diabetes,self-management,user-involved design process,mobile phone,usage,usability,mhealth

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