The impact of mobile monitoring technologies on glycosylated hemoglobin in diabetes: a systematic review

Telerheumatology: A Systematic Review

OBJECTIVE

To identify and summarize the published and gray literature on the use of telemedicine for the diagnosis and management of inflammatory and/or autoimmune rheumatic disease.

METHODS

We performed a registered systematic search (CRD42015025382) for studies using MEDLINE (1946 to July 2015), Embase (1974 to July 2015), Web of Science (1900 to July 2015), and Scopus (1946 to July 2015) databases. We included studies that demonstrated the use of telemedicine for diagnosis and/or management of inflammatory/autoimmune rheumatic disease. Following data extraction, we performed a descriptive analysis.

RESULTS

Our literature search identified 1,468 potentially eligible studies. Of these studies, 20 were ultimately included in this review. Studies varied significantly in publication type, quality of evidence, and the reporting of methods. Most demonstrated a high risk of bias. Rheumatoid arthritis was the most commonly studied rheumatic disease (42% of patients). Studies demonstrated conflicting results regarding the effectiveness of telemedicine (18 found it effective, 1 found it effective but possibly harmful, and 1 found it ineffective). A limited number of studies included some component of a cost analysis (n = 6; 16% of patients); all of these found telemedicine to be cost-effective.

CONCLUSION

Studies identified by this systematic review generally found telemedicine to be effective for the diagnosis and management of autoimmune/inflammatory rheumatic disease; however, there is limited evidence to support this conclusion. Further studies are needed to determine the best uses of telemedicine for the diagnosis and management of these conditions.

mHealth Application Areas and Technology Combinations*. A Comparison of Literature from High and Low/Middle Income Countries

BACKGROUND

With the continuous and enormous spread of mobile technologies, mHealth has evolved as a new subfield of eHealth. While eHealth is broadly focused on information and communication technologies, mHealth seeks to explore more into mobile devices and wireless communication. Since mobile phone penetration has exceeded other infrastructure in low and middle-income countries (LMICs), mHealth is seen as a promising component to provide pervasive and patient-centered care.

OBJECTIVES

The aim of our research work for this paper is to examine the mHealth literature to identify application areas, target diseases, and mHealth service and technology types that are most appropriate for LMICs.

METHODS

Based on the 2011 WHO mHealth report, a combination of search terms, all including the word "mHealth", was identified. A literature review was conducted by searching the PubMed and IEEE Xplore databases. Articles were included if they were published in English, covered an mHealth solution/ intervention, involved the use of a mobile communication device, and included a pilot evaluation study. Articles were excluded if they did not provide sufficient detail on the solution covered or did not focus on clinical efficacy/effectiveness. Cross-referencing was also performed on included articles.

RESULTS

842 articles were retrieved and analyzed, 255 of which met the inclusion criteria. North America had the highest number of applications (n=74) followed by Europe (n=50), Asia (n=44), Africa (n=25), and Australia (n=9). The Middle East (n=5) and South America (n=3) had the least number of studies. The majority of solutions addressed diabetes (n=51), obesity (n=25), CVDs (n=24), HIV (n=18), mental health (n=16), health behaviors (n=16), and maternal and child's health (MCH) (n=11). Fewer solutions addressed asthma (n=7), cancer (n=5), family health planning (n=5), TB (n=3), malaria (n=2), chronic obtrusive pulmonary disease (COPD) (n=2), vision care (n=2), and dermatology (n=2). Other solutions targeted stroke, dental health, hepatitis vaccination, cold and flu, ED prescribed antibiotics, iodine deficiency, and liver transplantation (n=1 each). The remainder of solutions (n=14) did not focus on a certain disease. Most applications fell in the areas of health monitoring and surveillance (n=93) and health promotion and raising awareness (n=88). Fewer solutions addressed the areas of communication and reporting (n=11), data collection (n=6), telemedicine (n=5), emergency medical care (n=3), point of care support (n=2), and decision support (n=2). The majority of solutions used SMS messaging (n=94) or mobile apps (n=71). Fewer used IVR/phone calls (n=8), mobile website/email (n=5), videoconferencing (n=2), MMS (n=2), or video (n=1) or voice messages (n=1). Studies were mostly RCTs, with the majority suffering from small sample sizes and short study durations. Problems addressed by solutions included travel distance for reporting, self-management and disease monitoring, and treatment/medication adherence.

CONCLUSIONS

SMS and app solutions are the most common forms of mHealth applications. SMS solutions are prevalent in both high and LMICs while app solutions are mostly used in high income countries. Common application areas include health promotion and raising awareness using SMS and health monitoring and surveillance using mobile apps. Remaining application areas are rarely addressed. Diabetes is the most commonly targeted medical condition, yet remains deficient in LMICs.

Accuracy and User Performance Evaluation of a New, Wireless-enabled Blood Glucose Monitoring System That Links to a Smart Mobile Device

BACKGROUND

The new Contour®Plus ONE blood glucose monitoring system (BGMS) features an easy-to-use, wireless-enabled blood glucose meter that links to a smart mobile device via Bluetooth® connectivity and can sync with the Contour™ Diabetes app on a smartphone or tablet.

METHODS

The accuracy of the new BGMS was assessed in 2 studies according to ISO 15197:2013 criteria. In Study 1 (laboratory study), fingertip capillary blood samples from 100 subjects were tested in duplicate using 3 test strip lots. In Study 2 (clinical study), 134 subjects with type 1 or type 2 diabetes enrolled at 2 clinical sites. BGMS results and YSI analyzer (YSI) reference results were compared for fingertip blood obtained by untrained subjects' self-testing and for study staff-obtained fingertip, subject palm, and venous results.

RESULTS

In Study 1, 99.0% (594/600) of combined results for all 3 test strip lots fulfilled ISO 15197:2013 Section 6.3 accuracy criteria. In Study 2, 99.2% (133/134) of subject-obtained capillary fingertip results, 99.2% (133/134) of study staff-obtained fingertip results, 99.2% (125/126) of subject-obtained palm results, and 100% (132/132) of study staff-obtained venous results met ISO 15197:2013 Section 8 accuracy criteria. Moreover, 95.5% (128/134) of subject-obtained fingertip self-test results were within ±10 mg/dl (±0.6 mmol/L) or ±10% of the YSI reference result. Questionnaire results showed that most subjects found the BGMS easy to use.

CONCLUSIONS

The BGMS exceeded ISO 15197:2013 accuracy criteria both in the laboratory and in a clinical setting when used by untrained subjects with diabetes.

Telehealth Interventions to Support Self-Management of Long-Term Conditions: A Systematic Metareview of Diabetes, Heart Failure, Asthma, Chronic Obstructive Pulmonary Disease, and Cancer

Background

Self-management support is one mechanism by which telehealth interventions have been proposed to facilitate management of long-term conditions.

Objective

The objectives of this metareview were to (1) assess the impact of telehealth interventions to support self-management on disease control and health care utilization, and (2) identify components of telehealth support and their impact on disease control and the process of self-management. Our goal was to synthesise evidence for telehealth-supported self-management of diabetes (types 1 and 2), heart failure, asthma, chronic obstructive pulmonary disease (COPD) and cancer to identify components of effective self-management support.

Methods

We performed a metareview (a systematic review of systematic reviews) of randomized controlled trials (RCTs) of telehealth interventions to support self-management in 6 exemplar long-term conditions. We searched 7 databases for reviews published from January 2000 to May 2016 and screened identified studies against eligibility criteria. We weighted reviews by quality (revised A Measurement Tool to Assess Systematic Reviews), size, and relevance. We then combined our results in a narrative synthesis and using harvest plots.

Results

We included 53 systematic reviews, comprising 232 unique RCTs. Reviews concerned diabetes (type 1: n=6; type 2, n=11; mixed, n=19), heart failure (n=9), asthma (n=8), COPD (n=8), and cancer (n=3). Findings varied between and within disease areas. The highest-weighted reviews showed that blood glucose telemonitoring with feedback and some educational and lifestyle interventions improved glycemic control in type 2, but not type 1, diabetes, and that telemonitoring and telephone interventions reduced mortality and hospital admissions in heart failure, but these findings were not consistent in all reviews. Results for the other conditions were mixed, although no reviews showed evidence of harm. Analysis of the mediating role of self-management, and of components of successful interventions, was limited and inconclusive. More intensive and multifaceted interventions were associated with greater improvements in diabetes, heart failure, and asthma.

Conclusions

While telehealth-mediated self-management was not consistently superior to usual care, none of the reviews reported any negative effects, suggesting that telehealth is a safe option for delivery of self-management support, particularly in conditions such as heart failure and type 2 diabetes, where the evidence base is more developed. Larger-scale trials of telehealth-supported self-management, based on explicit self-management theory, are needed before the extent to which telehealth technologies may be harnessed to support self-management can be established.

A New, Wireless-enabled Blood Glucose Monitoring System That Links to a Smart Mobile Device: Accuracy and User Performance Evaluation

BACKGROUND

These studies investigated the accuracy of the new Contour®Next ONE blood glucose monitoring system (BGMS) that is designed to sync with the Contour™ Diabetes app on a smartphone or tablet.

METHODS

A laboratory study tested fingertip capillary blood samples from 100 subjects in duplicate using 3 test strip lots, based on ISO 15197:2013 Section 6.3 analytical accuracy standards. A clinical study assessed accuracy per ISO 15197:2013 Section 8 criteria. Subjects with (n = 333) or without (n = 43) diabetes and who had not used the BGMS previously were enrolled. Each subject performed a self-test using the BGMS, which was repeated by a site staff member. Alternate site tests and venipunctures were also performed for analysis. A questionnaire was provided to assess user feedback on ease of use.

RESULTS

In the laboratory study, 100% (600/600) of combined results for all 3 test strip lots met ISO 15197:2013 Section 6.3 accuracy criteria. In the clinical study, among subjects with diabetes, 99.4% (327/329) of subject self-test results, 99.7% (331/332) of results obtained by study staff, 97.2% (309/318) of subject palm results, and 100% (330/330) of venous results met ISO 15197:2013 Section 8 accuracy criteria. Moreover, 97.6% (321/329) of subject self-test results were within ±10 mg/dl (±0.6 mmol/L) or ±10% of the YSI reference result. Questionnaire results indicated that most subjects considered the system easy to use.

CONCLUSIONS

The BGMS exceeded ISO 15197:2013 accuracy criteria in the laboratory and in a clinical setting.

Effect of telemedicine on glycated hemoglobin in diabetes: a systematic review and meta-analysis of randomized trials

BACKGROUND

Telemedicine, the use of telecommunications to deliver health services, expertise and information, is a promising but unproven tool for improving the quality of diabetes care. We summarized the effectiveness of different methods of telemedicine for the management of diabetes compared with usual care.

METHODS

We searched MEDLINE, Embase and the Cochrane Central Register of Controlled Trials databases (to November 2015) and reference lists of existing systematic reviews for randomized controlled trials (RCTs) comparing telemedicine with usual care for adults with diabetes. Two independent reviewers selected the studies and assessed risk of bias in the studies. The primary outcome was glycated hemoglobin (HbA1C) reported at 3 time points (≤ 3 mo, 4-12 mo and > 12 mo). Other outcomes were quality of life, mortality and episodes of hypoglycemia. Trials were pooled using randomeffects meta-analysis, and heterogeneity was quantified using the I2 statistic.

RESULTS

From 3688 citations, we identified 111 eligible RCTs (n = 23 648). Telemedicine achieved significant but modest reductions in HbA1C in all 3 follow-up periods (difference in mean at ≤ 3 mo: -0.57%, 95% confidence interval [CI] -0.74% to -0.40% [39 trials]; at 4-12 mo: -0.28%, 95% CI -0.37% to -0.20% [87 trials]; and at > 12 mo: -0.26%, 95% CI -0.46% to -0.06% [5 trials]). Quantified heterogeneity (I2 statistic) was 75%, 69% and 58%, respectively. In meta-regression analyses, the effect of telemedicine on HbA1C appeared greatest in trials with higher HbA1C concentrations at baseline, in trials where providers used Web portals or text messaging to communicate with patients and in trials where telemedicine facilitated medication adjustment. Telemedicine had no convincing effect on quality of life, mortality or hypoglycemia.

INTERPRETATION

Compared with usual care, the addition of telemedicine, especially systems that allowed medication adjustments with or without text messaging or a Web portal, improved HbA1C but not other clinically relevant outcomes among patients with diabetes.

Effectiveness of mHealth interventions for patients with diabetes: An overview of systematic reviews

Background

Diabetes is a common chronic disease that places an unprecedented strain on health care systems worldwide. Mobile health technologies such as smartphones, mobile applications, and wearable devices, known as mHealth, offer significant and innovative opportunities for improving patient to provider communication and self-management of diabetes.

Objective

The purpose of this overview is to critically appraise and consolidate evidence from multiple systematic reviews on the effectiveness of mHealth interventions for patients with diabetes to inform policy makers, practitioners, and researchers.

Methods

A comprehensive search on multiple databases was performed to identify relevant systematic reviews published between January 1996 and December 2015. Two authors independently selected reviews, extracted data, and assessed the methodological quality of included reviews using AMSTAR.

Results

Fifteen systematic reviews published between 2008 and 2014 were eligible for inclusion. The quality of the reviews varied considerably and most of them had important methodological limitations. Focusing on systematic reviews that offered the most direct evidence, this overview demonstrates that on average, mHealth interventions improve glycemic control (HbA1c) compared to standard care or other non-mHealth approaches by as much as 0.8% for patients with type 2 diabetes and 0.3% for patients with type 1 diabetes, at least in the short-term (≤12 months). However, limitations in the overall quality of evidence suggest that further research will likely have an important impact in these estimates of effect.

Conclusions

Findings are consistent with clinically relevant improvements, particularly with respect to patients with type 2 diabetes. Similar to home telemonitoring, mHealth interventions represent a promising approach for self-management of diabetes.

Barriers to Remote Health Interventions for Type 2 Diabetes: A Systematic Review and Proposed Classification Scheme

Background

Diabetes self-management involves adherence to healthy daily habits typically involving blood glucose monitoring, medication, exercise, and diet. To support self-management, some providers have begun testing remote interventions for monitoring and assisting patients between clinic visits. Although some studies have shown success, there are barriers to widespread adoption.

Objective

The objective of our study was to identify and classify barriers to adoption of remote health for management of type 2 diabetes.

Methods

The following 6 electronic databases were searched for articles published from 2010 to 2015: MEDLINE (Ovid), Embase (Ovid), CINAHL, Cochrane Central, Northern Light Life Sciences Conference Abstracts, and Scopus (Elsevier). The search identified studies involving remote technologies for type 2 diabetes self-management. Reviewers worked in teams of 2 to review and extract data from identified papers. Information collected included study characteristics, outcomes, dropout rates, technologies used, and barriers identified.

Results

A total of 53 publications on 41 studies met the specified criteria. Lack of data accuracy due to input bias (32%, 13/41), limitations on scalability (24%, 10/41), and technology illiteracy (24%, 10/41) were the most commonly cited barriers. Technology illiteracy was most prominent in low-income populations, whereas limitations on scalability were more prominent in mid-income populations. Barriers identified were applied to a conceptual model of successful remote health, which includes patient engagement, patient technology accessibility, quality of care, system technology cost, and provider productivity. In total, 40.5% (60/148) of identified barrier instances impeded patient engagement, which is manifest in the large dropout rates cited (up to 57%).

Conclusions

The barriers identified represent major challenges in the design of remote health interventions for diabetes. Breakthrough technologies and systems are needed to alleviate the barriers identified so far, particularly those associated with patient engagement. Monitoring devices that provide objective and reliable data streams on medication, exercise, diet, and glucose monitoring will be essential for widespread effectiveness. Additional work is needed to understand root causes of high dropout rates, and new interventions are needed to identify and assist those at the greatest risk of dropout. Finally, future studies must quantify costs and benefits to determine financial sustainability.

Do Mobile Phone Applications Improve Glycemic Control (HbA1c) in the Self-management of Diabetes? A Systematic Review, Meta-analysis, and GRADE of 14 Randomized Trials

OBJECTIVE

To investigate the effect of mobile phone applications (apps) on glycemic control (HbA_1c) in the self-management of diabetes.

RESEARCH DESIGN AND METHODS

Relevant studies that were published between 1 January 1996 and 1 June 2015 were searched from five databases: Medline, CINAHL, Cochrane Library, Web of Science, and Embase. Randomized controlled trials that evaluated diabetes apps were included. We conducted a systematic review with meta-analysis and GRADE (Grading of Recommendations Assessment, Development and Evaluation) of the evidence.

RESULTS

Participants from 14 studies (n = 1,360) were included and quality assessed. Although there may have been clinical diversity, all type 2 diabetes studies reported a reduction in HbA_1c. The mean reduction in participants using an app compared with control was 0.49% (95% Cl 0.30, 0.68; I² = 10%), with a moderate GRADE of evidence. Subgroup analyses indicated that younger patients were more likely to benefit from the use of diabetes apps, and the effect size was enhanced with health care professional feedback. There was inadequate data to describe the effectiveness of apps for type 1 diabetes.

CONCLUSIONS

Apps may be an effective component to help control HbA_1c and could be considered as an adjuvant intervention to the standard self-management for patients with type 2 diabetes. Given the reported clinical effect, access, and nominal cost of this technology, it is likely to be effective at the population level. The functionality and use of this technology need to be standardized, but policy and guidance are anticipated to improve diabetes self-management care.

Effect of Telehealth Interventions on Hospitalization Indicators: A Systematic Review

BACKGROUND

Telehealth has been defined as the remote delivery of healthcare services using information and communication technology. Where resource-limited health systems face challenges caused by the increasing burden of chronic diseases and an aging global population, telehealth has been advocated as a solution for changing and improving the paradigm of healthcare delivery to cope with these issues. The aim of this systematic review is to investigate the effect of telehealth interventions on two indicators: hospitalization rate and length of stay.

MATERIALS AND METHODS

The reviewers searched the PubMed, ScienceDirect, and Springer electronic databases from January 2005 to November 2013. A search strategy was developed using a combination of the following search keywords: impact, effect, telehealth, telemedicine, telecare, hospitalization, length of stay, and resource utilization. Both randomized controlled trials and observational studies were included in the review. To be included in the review, articles had to be written in English. The results of study were compiled, reviewed, and analyzed on the basis of the review aims.

RESULTS

This systematic review examined 22 existing studies with a total population of 19,086 patients. The effect of telehealth on all-cause hospitalization was statistically significant in 40 percent of the related studies, whereas it was not statistically significant in 60 percent. Similarly, the effect of telehealth on the all-cause length of stay was statistically significant in 36 percent of the studies and nonsignificant in 64 percent.

CONCLUSION

Considering the fact that hospitalization rate and length of stay can be confounded by factors other than telehealth intervention, studies examining the effect of the intervention on these indicators must take into account all other factors influencing them. Otherwise any judgment on the effect of telehealth on these indicators cannot be valid.

Diabetes care related process modelling using Process Mining techniques. Lessons learned in the application of Interactive Pattern Recognition: coping with the Spaghetti Effect

Diabetes is one of the metabolic disorders with more growth expectations in next decades. The literature points to a correct self-management, to an appropriate treatment and to an adequate healthy lifestyle as a way to dramatically improve the quality of life of patients with diabetes. The implementation of a holistic diabetes care system, using rising information technologies for deploying cares based on the thesis of the Evidence-Based Medicine can be a effective solution to provide an adequate and continuous care to patients. However, the design and deployment of computer readable careflows is not a easy task. In this paper, we propose the use of Interactive Pattern Recognition techniques for the iterative design of those protocols and we analyze the problems of using Process Mining to infer careflows and how to how to cope with the resulting Spaghetti Effect.

Mobile Applications for Control and Self Management of Diabetes: A Systematic Review

Mobile applications (apps) can be very useful software on smartphones for all aspects of people's lives. Chronic diseases, such as diabetes, can be made manageable with the support of mobile apps. Applications on smartphones can also help people with diabetes to control their fitness and health. A systematic review of free apps in the English language for smartphones in three of the most popular mobile app stores: Google Play (Android), App Store (iOS) and Windows Phone Store, was performed from November to December 2015. The review of freely available mobile apps for self-management of diabetes was conducted based on the criteria for promoting diabetes self-management as defined by Goyal and Cafazzo (monitoring blood glucose level and medication, nutrition, physical exercise and body weight). The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) was followed. Three independent experts in the field of healthcare-related mobile apps were included in the assessment for eligibility and testing phase. We tested and evaluated 65 apps (21 from Google Play Store, 31 from App Store and 13 from Windows Phone Store). Fifty-six of these apps did not meet even minimal requirements or did not work properly. While a wide selection of mobile applications is available for self-management of diabetes, current results show that there are only nine (5 from Google Play Store, 3 from App Store and 1 from Windows Phone Store) out of 65 reviewed mobile apps that can be versatile and useful for successful self-management of diabetes based on selection criteria. The levels of inclusion of features based on selection criteria in selected mobile apps can be very different. The results of the study can be used as a basis to prvide app developers with certain recommendations. There is a need for mobile apps for self-management of diabetes with more features in order to increase the number of long-term users and thus influence better self-management of the disease.

A randomised, controlled trial of the effects of a mobile telehealth intervention on clinical and patient-reported outcomes in people with poorly controlled diabetes

Objective

The objective of this research is to determine the effects of mobile telehealth (MTH) on glycosylated haemoglobin (HbA1c) and other clinical and patient-reported outcomes in insulin-requiring people with diabetes.

Methods

A nine-month randomised, controlled trial compared standard care to standard care supplemented with MTH (self-monitoring, mobile-phone data transmissions, graphical and nurse-initiated feedback, and educational calls). Clinical (HbA1c, blood pressure, daily insulin dose, diabetes outpatient appointments (DOAs)) and questionnaire data (health-related quality of life, depression, anxiety) were collected. Mean group changes over time were compared using hierarchical linear models and Mann-Whitney tests.

Results

Eighty-one participants with a baseline HbA1c of 8.98% ± 1.82 were randomised to the intervention ( n = 45) and standard care ( n = 36). The Group by Time effect revealed MTH did not significantly influence HbA1c ( p = 0.228), but p values were borderline significant for blood pressure ( p = 0.054) and mental-health related quality of life ( p = 0.057). Examination of effect sizes and 95% confidence intervals for mean group differences at nine months supported the existence of a protective effect of MTH on mental health-related quality of life as well as depression. None of the other measured outcomes were found to be affected by the MTH intervention.

Conclusions

Findings from this study must be interpreted with caution given the small sample size, but they do not support the widespread adoption of MTH to achieve clinically significant changes in HbA1c. MTH may, however, have positive effects on blood pressure and protective effects on some aspects of mental health.

Remote Health Consultations Supported by a Diabetes Management Web Application With a New Glucose Meter Demonstrates Improved Glycemic Control

BACKGROUND

Cloud-connected diabetes applications enable health care professionals (HCPs) to monitor patient progress and offer the potential for remote consultations. OneTouch Reveal (OTR) is a cloud-based web application that aggregates data from blood glucose (BG) meters or insulin pumps and provides analytics to help patients and HCPs make more informed treatment and lifestyle decisions. This study assessed the experience of patients using OTR and the OneTouch Verio (OTV) BG meter and determined the extent of changes in glycemic control.

METHODS

Subjects with T1DM (23) or T2DM (17) uploaded BG meter results to OTR for 12 weeks. HCPs remotely reviewed progress using OTR and delivered telephone consultations at 4 and 8 weeks based on OTR insights.

RESULTS

After 12 weeks, mean HbA1c decreased by 0.4% (P < .001) and 25% of subjects had a reduction of ≥1.0%. Reduction in HbA1c was similar in subjects with T1DM and T2DM, although subjects with T1DM started with higher baselines. In subjects with T2DM, mean BG decreased significantly from 175 to 161 mg/dl (P < .001) with the percentage of above-range BG results decreasing from 33% to 24%. 80% of subjects confirmed OTR detected out-of-range glucose patterns and 84% of these subjects were able to correct the underlying pattern to get BG back in-range.

CONCLUSIONS

OTR web application in combination with the OTV meter helped subjects with T1DM and T2DM effectively manage their diabetes and was associated with improved BG control over 12 weeks. Real-time visibility to subject data may help HCPs deliver focused and effective remote consultations.

Influences on Technology Use and Efficacy in Type 1 Diabetes

The majority of people with type 1 diabetes have suboptimal glycemic control, increasing their complication risk. Technology to support diabetes self-care has advanced significantly and includes self-monitoring of blood glucose (SMBG), insulin pump therapy (IPT), continuous glucose monitoring (CGM), and sensor-augmented pump therapy (SAPT), which are stepping stones toward the "artificial pancreas" using closed-loop technology. Use of these technologies improves clinical outcomes for patients with the appropriate skills and motivation. This review addresses the psychosocial factors that influence both technology provision and clinical outcome and also how technology impacts on psychological outcomes. Optimal use of the various diabetes self-management technologies is influenced by previous self-care behaviors, demographic and psychological factors. Provision of IPT is also influenced by the same factors. Despite technology increasing the complexity of treatment, the lack of evidence for adverse psychological outcomes is reassuring. Treatment satisfaction is high, and discontinuation rates are low. However, technology will widen the health inequality gap if its use is limited to motivated patients who demonstrate good self-care behaviors. Pivotal to the success of the various technologies is provision of appropriate education at initiation of the technology, regular ongoing contact for treatment adjustments and trouble-shooting device issues plus access to psychological support when required. Additional support strategies may be required to help patients struggling with their diabetes to benefit from the available technology, recognizing that they may have most to gain.

Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review

Diabetic individuals need to tightly control their blood glucose concentration. Several methods have been developed for this purpose, such as the finger-prick or continuous glucose monitoring systems (CGMs). However, these methods present the disadvantage of being invasive. Moreover, CGMs have limited accuracy, notably to detect hypoglycemia. It is also known that physical exercise, and even daily activity, disrupt glucose dynamics and can generate problems with blood glucose regulation during and after exercise. In order to deal with these challenges, devices for monitoring patients’ physical activity are currently under development. This review focuses on non-invasive sensors using physiological parameters related to physical exercise that were used to improve glucose monitoring in type 1 diabetes (T1DM) patients. These devices are promising for diabetes management. Indeed they permit to estimate glucose concentration either based solely on physical activity parameters or in conjunction with CGM or non-invasive CGM (NI-CGM) systems. In these last cases, the vital signals are used to modulate glucose estimations provided by the CGM and NI-CGM devices. Finally, this review indicates possible limitations of these new biosensors and outlines directions for future technologic developments.

Usability Pitfalls of Diabetes mHealth Apps for the Elderly

Diabetes mellitus has high prevalence in the ageing population and is often accompanied by other comorbidities, such as Alzheimer's disease, and general disabilities, such as poor eyesight. These comorbidities have redefined ways in which patients use mHealth apps, including diabetes apps. The latter have proven benefits for monitoring blood glucose levels and insulin tracking in the general population. In this paper, we analyse a diabetes monitoring app DeStress Assistant (DeSA), which was developed as a part of an EU project and tested in a hospital setting. Due to the increasing number of older adults, we wanted to ensure the app was suitable for that demographic. Based on a number of supervised tests, we show that the app, which was developed with the help of workshops and feedback from tech-savvy patients and clinicians, is difficult to use by elderly users. We demonstrate that with a small number of changes it is possible to raise the usability of the app in a number of categories. We summarise the lessons learned in the discussion. Our findings demonstrate that special care needs to be taken when developing mHealth apps for the elderly population.

Managing diabetes in the digital age

The prevalence of diabetes is rising globally. Poor glucose control results in higher rates of diabetes-related complications and an increase in health care expenditure. Diabetes self-management education (DSME) training has shown to improve glucose control, and thus may reduce long-term complications. Implementation of diabetes self-management education programs may not be feasible for all the institutions or in developing countries due to lack of resources and higher costs associated with DSME training. With the increasing use of smartphones and Internet, there is an opportunity to use digital tools for training people with diabetes to self-manage their disease. A number of mobile applications, Internet portal, and websites are available to help patients to improve their diabetes care. However, the studies are limited to show its effectiveness and cost-benefits in diabetes self-management. In addition, there are many challenges ahead for the digital health industry. In this review, we assess the use of newer technologies and digital health in diabetes self-management with a focus on future directions and potential challenges.

Mobile Health Devices as Tools for Worldwide Cardiovascular Risk Reduction and Disease Management

We examined evidence on whether mobile health (mHealth) tools, including interactive voice response calls, short message service, or text messaging, and smartphones, can improve lifestyle behaviors and management related to cardiovascular diseases throughout the world. We conducted a state-of-the-art review and literature synthesis of peer-reviewed and gray literature published since 2004. The review prioritized randomized trials and studies focused on cardiovascular diseases and risk factors, but included other reports when they represented the best available evidence. The search emphasized reports on the potential benefits of mHealth interventions implemented in low- and middle-income countries. Interactive voice response and short message service interventions can improve cardiovascular preventive care in developed countries by addressing risk factors including weight, smoking, and physical activity. Interactive voice response and short message service-based interventions for cardiovascular disease management also have shown benefits with respect to hypertension management, hospital readmissions, and diabetic glycemic control. Multimodal interventions including Web-based communication with clinicians and mHealth-enabled clinical monitoring with feedback also have shown benefits. The evidence regarding the potential benefits of interventions using smartphones and social media is still developing. Studies of mHealth interventions have been conducted in >30 low- and middle-income countries, and evidence to date suggests that programs are feasible and may improve medication adherence and disease outcomes. Emerging evidence suggests that mHealth interventions may improve cardiovascular-related lifestyle behaviors and disease management. Next-generation mHealth programs developed worldwide should be based on evidence-based behavioral theories and incorporate advances in artificial intelligence for adapting systems automatically to patients' unique and changing needs.

mobile Digital Access to a Web-enhanced Network (mDAWN): Assessing the Feasibility of Mobile Health Tools for Self-Management of Type-2 Diabetes

The mobile Digital Access to a Web-enhanced Network (mDAWN) program was implemented as an online, mobile self-management system to support patients with type-2 diabetes and their informal caregivers. Patients used wireless physiological sensors, received text messages, and had access to a secure web platform with health resources and semi-facilitated discussion forum. Outcomes were evaluated using (1) pre and post self-reported health behavior measures, (2) physiological outcomes, (3) program cost, and (4) in-depth participant interviews. The group had significantly decreased health distress, HbA1c levels, and systolic blood pressure. Participants largely saw the mDAWN as providing good value for the costs involved and found the program to be empowering in gaining control over their diabetes. mHealth programs have the potential to improve clinical outcomes through cost effective patient-led care for chronic illness. Further evaluation needs to examine integration of similar mHealth programs into the patient-physician relationship.

Personal health technology: A new era in cardiovascular disease prevention

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide yet the majority of related risk factors are largely preventable (primary prevention [PP]) and effectively treatable (secondary prevention [SP]) with healthy lifestyle behaviors. The use of information and communication technology (ICT) offers a unique approach to personal health and CVD prevention, as these mediums are relatively affordable, approachable, and accessible. The purpose of this review is to provide an overview of ICT-driven personal health technologies and their potential role in promoting and supporting self-care behaviors for PP and SP of CVD. In this review, we focus on technological interventions that have been successful at supporting positive behavior change in order to determine which tools, resources, and methods are most appropriate for delivering interventions geared towards CVD prevention. We conducted a literature search from a range of sources including scholarly, peer-reviewed journal articles indexed in PubMed and CINAHL, gray literature, and reputable websites and other Internet-based media. A synthesis of existing literature indicates that the overall efficacy of ICT-driven personal health technologies is largely determined by: 1) the educational resources provided and the extent to which the relayed information is customized or individually tailored; and 2) the degree of self-monitoring and levels of personalized feedback or other interactions (e.g. interpersonal communications). We conclude that virtually all the technological tools and resources identified (e.g. Internet-based communications including websites, weblogs and wikis, mobile devices and applications, social media, and wearable monitors) can be strategically leveraged to enhance self-care behaviors for CVD risk reduction and SP but further research is needed to evaluate their efficacy, cost-effectiveness, and long-term maintainability.

A mobile telehealth intervention for adults with insulin-requiring diabetes: early results of a mixed-methods randomized controlled trial

Background

The role of technology in health care delivery has grown rapidly in the last decade. The potential of mobile telehealth (MTH) to support patient self-management is a key area of research. Providing patients with technological tools that allow for the recording and transmission of health parameters to health care professionals (HCPs) may promote behavior changes that result in improved health outcomes. Although for some conditions the evidence of the effectiveness of MTH is clear, to date the findings on the effects of MTH on diabetes management remain inconsistent.

Objective

This study aims to evaluate an MTH intervention among insulin-requiring adults with diabetes to establish whether supplementing standard care with MTH results in improved health outcomes—glycated hemoglobin (HbA1c), blood pressure (BP), health-related quality of life (HRQoL), diabetes self-management behaviors, diabetes health care utilization, and diabetes self-efficacy and illness beliefs. An additional objective was to explore the acceptability of MTH and patients’ perceptions of, and experience, using it.

Methods

A mixed-method design consisting of a 9-month, two-arm, parallel randomized controlled trial (RCT) was used in combination with exit qualitative interviews. Quantitative data was collected at baseline, 3 months, and 9 months. Additional intervention fidelity data, such as participants’ MTH transmissions and contacts with the MTH nurse during the study, were also recorded.

Results

Data collection for both the quantitative and qualitative components of this study has ended and data analysis is ongoing. A total of 86 participants were enrolled into the study. Out of 86 participants, 45 (52%) were randomized to the intervention group and 36 (42%) to the control group. Preliminary data on MTH training sessions and MTH usage by intervention participants are presented in this paper. We expect to publish complete study results in 2015.

Conclusions

The range of data collected in this study will allow for a comprehensive evaluation of processes and outcomes. The early results presented suggest that MTH usage decreases over time and that MTH participants would benefit from attending more than one training session.

Trial Registration

ClinicalTrials.gov NCT00922376; http://clinicaltrials.gov/ct2/show/NCT00922376 (Archived by WebCite at http://www.webcitation.org/6Vu4nhLI6).

Using new technologies to improve the prevention and management of chronic conditions in populations

Lifestyle factors are important in the development of chronic diseases, such as heart disease, respiratory disease, and diabetes, and chronic disease risk can be reduced by changes in lifestyle behaviors linked to these conditions. The use of mass media and community-wide strategies targeting these behaviors has been extensively evaluated since the 1970s. This review summarizes some examples of interventions and their use of media conducted within the old communications landscape of the 1970s and 1980s and the key lessons learned from their design, implementation, and evaluation. We then consider the potential and evidence base for using contemporary technology applications and platforms-within the new communications landscape-to improve the prevention and management of lifestyle-related chronic diseases in the future. We discuss the implications and adaptation of lessons derived from the ways in which new technologies are being used in commercial and political contexts and their relevance for public health. Finally, we consider some recent examples of applying new technologies to public health issues and consider some of the challenges in this rapidly developing field.

A Mobile Health Intervention for Self-Management and Lifestyle Change for Persons With Type 2 Diabetes, Part 2: One-Year Results From the Norwegian Randomized Controlled Trial RENEWING HEALTH

Background

Self-management is crucial in the daily management of type 2 diabetes. It has been suggested that mHealth may be an important method for enhancing self-management when delivered in combination with health counseling.

Objective

The objective of this study was to test whether the use of a mobile phone–based self-management system used for 1 year, with or without telephone health counseling by a diabetes specialist nurse for the first 4 months, could improve glycated hemoglobin A_1c (HbA_1c) level, self-management, and health-related quality of life compared with usual care.

Methods

We conducted a 3-arm prospective randomized controlled trial involving 2 intervention groups and 1 control group. Eligible participants were persons with type 2 diabetes with an HbA_1c level ≥7.1% (≥54.1 mmol/mol) and aged ≥18 years. Both intervention groups received the mobile phone–based self-management system Few Touch Application (FTA). The FTA consisted of a blood glucose–measuring system with automatic wireless data transfer, diet manual, physical activity registration, and management of personal goals, all recorded and operated using a diabetes diary app on the mobile phone. In addition, one intervention group received health counseling based on behavior change theory and delivered by a diabetes specialist nurse for the first 4 months after randomization. All groups received usual care by their general practitioner. The primary outcome was HbA_1c level. Secondary outcomes were self-management (heiQ), health-related quality of life (SF-36), depressive symptoms (CES-D), and lifestyle changes (dietary habits and physical activity). Data were analyzed using univariate methods (t test, ANOVA) and multivariate linear and logistic regression.

Results

A total of 151 participants were randomized: 51 to the FTA group, 50 to the FTA-health counseling (FTA-HC) group, and 50 to the control group. Follow-up data after 1 year were available for 120 participants (79%). HbA_1c level decreased in all groups, but did not differ between groups after 1 year. The mean change in the heiQ domain skills and technique acquisition was significantly greater in the FTA-HC group after adjusting for age, gender, and education (P=.04). Other secondary outcomes did not differ between groups after 1 year. In the FTA group, 39% were substantial users of the app; 34% of the FTA-HC group were substantial users. Those aged ≥63 years used the app more than their younger counterparts did (OR 2.7; 95% CI 1.02-7.12; P=.045).

Conclusions

The change in HbA_1c level did not differ between groups after the 1-year intervention. Secondary outcomes did not differ between groups except for an increase in the self-management domain of skill and technique acquisition in the FTA-HC group. Older participants used the app more than the younger participants did.

Effectiveness and cost-effectiveness of ehealth interventions in somatic diseases: a systematic review of systematic reviews and meta-analyses

Background

eHealth potentially enhances quality of care and may reduce health care costs. However, a review of systematic reviews published in 2010 concluded that high-quality evidence on the benefits of eHealth interventions was still lacking.

Objective

We conducted a systematic review of systematic reviews and meta-analyses on the effectiveness/cost-effectiveness of eHealth interventions in patients with somatic diseases to analyze whether, and to what possible extent, the outcome of recent research supports or differs from previous conclusions.

Methods

Literature searches were performed in PubMed, EMBASE, The Cochrane Library, and Scopus for systematic reviews and meta-analyses on eHealth interventions published between August 2009 and December 2012. Articles were screened for relevance based on preset inclusion and exclusion criteria. Citations of residual articles were screened for additional literature. Included papers were critically appraised using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement before data were extracted. Based on conclusions drawn by the authors of the included articles, reviews and meta-analyses were divided into 1 of 3 groups: suitable, promising, or limited evidence on effectiveness/cost-effectiveness. Cases of uncertainty were resolved by consensus discussion. Effect sizes were extracted from papers that included a meta-analysis. To compare our results with previous findings, a trend analysis was performed.

Results

Our literature searches yielded 31 eligible reviews, of which 20 (65%) reported on costs. Seven papers (23%) concluded that eHealth is effective/cost-effective, 13 (42%) underlined that evidence is promising, and others found limited or inconsistent proof. Methodological quality of the included reviews and meta-analyses was generally considered high. Trend analysis showed a considerable accumulation of literature on eHealth. However, a similar percentage of papers concluded that eHealth is effective/cost-effective or evidence is at least promising (65% vs 62%). Reviews focusing primarily on children or family caregivers still remained scarce. Although a pooled (subgroup) analysis of aggregate data from randomized studies was performed in a higher percentage of more recently published reviews (45% vs 27%), data on economic outcome measures were less frequently reported (65% vs 85%).

Conclusions

The number of reviews and meta-analyses on eHealth interventions in patients with somatic diseases has increased considerably in recent years. Most articles show eHealth is effective/cost-effective or at least suggest evidence is promising, which is consistent with previous findings. Although many researchers advocate larger, well-designed, controlled studies, we believe attention should be given to the development and evaluation of strategies to implement effective/cost-effective eHealth initiatives in daily practice, rather than to further strengthen current evidence.

Smartphone and tablet self management apps for asthma

BACKGROUND

Asthma is one of the most common long-term conditions worldwide, which places considerable pressure on patients, communities and health systems. The major international clinical guidelines now recommend the inclusion of self management programmes in the routine management of patients with asthma. These programmes have been associated with improved outcomes in patients with asthma. However, the implementation of self management programmes in clinical practice, and their uptake by patients, is still poor. Recent developments in mobile technology, such as smartphone and tablet computer apps, could help develop a platform for the delivery of self management interventions that are highly customisable, low-cost and easily accessible.

OBJECTIVES

To assess the effectiveness, cost-effectiveness and feasibility of using smartphone and tablet apps to facilitate the self management of individuals with asthma.

SEARCH METHODS

We searched the Cochrane Airways Group Register (CAGR), the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, CINAHL, Global Health Library, Compendex/Inspec/Referex, IEEEXplore, ACM Digital Library, CiteSeer(x) and CAB abstracts via Web of Knowledge. We also searched registers of current and ongoing trials and the grey literature. We checked the reference lists of all primary studies and review articles for additional references. We searched for studies published from 2000 onwards. The latest search was run in June 2013.

SELECTION CRITERIA

We included parallel randomised controlled trials (RCTs) that compared self management interventions for patients with clinician-diagnosed asthma delivered via smartphone apps to self management interventions delivered via traditional methods (e.g. paper-based asthma diaries).

DATA COLLECTION AND ANALYSIS

We used standard methods expected by the Cochrane Collaboration. Our primary outcomes were symptom scores; frequency of healthcare visits due to asthma exacerbations or complications and health-related quality of life.

MAIN RESULTS

We included two RCTs with a total of 408 participants. We found no cluster RCTs, controlled before and after studies or interrupted time series studies that met the inclusion criteria for this systematic review. Both RCTs evaluated the effect of a mobile phone-based asthma self management intervention on asthma control by comparing it to traditional, paper-based asthma self management. One study allowed participants to keep daily entries of their asthma symptoms, asthma medication usage, peak flow readings and peak flow variability on their mobile phone, from which their level of asthma control was calculated remotely and displayed together with the corresponding asthma self management recommendations. In the other study, participants recorded the same readings twice daily, and they received immediate self management feedback in the form of a three-colour traffic light display on their phones. Participants falling into the amber zone of their action plan twice, or into the red zone once, received a phone call from an asthma nurse who enquired about the reasons for their uncontrolled asthma.We did not conduct a meta-analysis of the data extracted due to the considerable degree of heterogeneity between these studies. Instead we adopted a narrative synthesis approach. Overall, the results were inconclusive and we judged the evidence to have a GRADE rating of low quality because further evidence is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. In addition, there was not enough information in one of the included studies to assess the risk of bias for the majority of the domains. Although the other included study was methodologically rigorous, it was not possible to blind participants or personnel in the study. Moreover, there are concerns in both studies in relation to attrition bias and other sources of bias.One study showed that the use of a smartphone app for the delivery of an asthma self management programme had no statistically significant effect on asthma symptom scores (mean difference (MD) 0.01, 95% confidence interval (CI) -0.23 to 0.25), asthma-related quality of life (MD of mean scores 0.02, 95% CI -0.35 to 0.39), unscheduled visits to the emergency department (OR 7.20, 95% CI 0.37 to 140.76) or frequency of hospital admissions (odds ratio (OR) 3.07, 95% CI 0.32 to 29.83). The other included study found that the use of a smartphone app resulted in higher asthma-related quality of life scores at six-month follow-up (MD 5.50, 95% CI 1.48 to 9.52 for the physical component score of the SF-12 questionnaire; MD 6.00, 95% CI 2.51 to 9.49 for the mental component score of the SF-12 questionnaire), improved lung function (PEFR) at four (MD 27.80, 95% CI 4.51 to 51.09), five (MD 31.40, 95% CI 8.51 to 54.29) and six months (MD 39.20, 95% CI 16.58 to 61.82), and reduced visits to the emergency department due to asthma-related complications (OR 0.20, 95% CI 0.04 to 0.99). Both studies failed to find any statistical differences in terms of adherence to the intervention and occurrence of other asthma-related complications.

AUTHORS' CONCLUSIONS

The current evidence base is not sufficient to advise clinical practitioners, policy-makers and the general public with regards to the use of smartphone and tablet computer apps for the delivery of asthma self management programmes. In order to understand the efficacy of apps as standalone interventions, future research should attempt to minimise the differential clinical management of patients between control and intervention groups. Those studies evaluating apps as part of complex, multicomponent interventions, should attempt to tease out the relative contribution of each intervention component. Consideration of the theoretical constructs used to inform the development of the intervention would help to achieve this goal. Finally, researchers should also take into account: the role of ancillary components in moderating the observed effects, the seasonal nature of asthma and long-term adherence to self management practices.

Role of health information technologies in the Patient-centered Medical Home

A national effort to reform primary care, known as the Patient-Centered Medical Home (PCMH), requires fulfillment of six standards determined by the National Committee for Quality Assurance to (1) enhance access and continuity, (2) identify and manage patient populations, (3) plan and manage care, (4) provide self-care and community support, (5) track and coordinate care, and (6) measure and improve performance. Information technologies play a vital role in the support of most, if not all, of these standards. However, given the newness of the PCMH, little is known on how health information technologies (HITs) have been employed to accomplish these objectives. This article will review the role of HITs, including electronic health records, web-based patient portals, telemedicine, and patient registries, with a focus on diabetes care, and how these technologies have been engaged in the establishment of the PCMH. In addition, we will discuss the benefits and potential risks and barriers to employing these technologies, including privacy and security concerns, as well as describe next steps for future work in this important area.

Lessons learned from the development of health applications in a tertiary hospital

BACKGROUND

Adoption of smart devices for hospital use has been increasing with the development of health applications (apps) for patient point-of-care and hospital management. To promote the use of health apps, we describe the lessons learned from developing 12 health apps in the largest tertiary hospital in Korea.

MATERIALS AND METHODS

We reviewed and analyzed 12 routinely used apps in three categories-Smart Clinic, Smart Patient, and Smart Hospital-based on target users and functions. The log data for each app were collected from the date of release up until December 2012.

RESULTS

Medical personnel accessed a mobile electronic medical record app classified as Smart Clinic an average of 452 times per day. Smart Hospital apps are actively used to communicate with each other. Patients logged on to a mobile personal health record app categorized as Smart Patient an average of 222 times per day. As the mobile trend, the choice of supporting operating system (OS) is more difficult. By developing these apps, a monitoring system is needed for evaluation.

CONCLUSIONS

We described the lessons learned regarding OS support, device choice, and developmental strategy. The OS can be chosen according to market share or hospital strategic plan. Smartphones were favored compared with tablets. Alliance with an information technology company can be the best way to develop apps. Health apps designed for smart devices can be used to improve healthcare. However, to develop health apps, hospitals must define their future goals and carefully consider all the aspects.

The current status of mHealth for diabetes: will it be the next big thing?

mHealth is an emerging concept in health care and uses mobile communications devices for health services and information. Mobile phones, patient monitoring devices, tablets, personal digital assistants, and other wireless devices can be part of mHealth systems. With mHealth systems, glucose data can now be automatically collected, transmitted, aggregated with other physiologic data, analyzed, stored, and presented as actionable information. mHealth systems use mobile decision support software applications (or apps) to assist or direct health care professionals to make decisions, or they can assist or direct patients to make decisions without waiting for input from a clinician. With real-time decision support for patients, appropriate actions can be taken in real time without waiting to see a clinician. Decisions can be personalized if individual treatment goals and personal preferences for treatment are inputted into an app. Few mHealth apps for diabetes have been rigorously tested. Outcome studies of the use of mHealth for diabetes from the literature have shown the potential for benefits, but higher-quality studies are needed. Regulatory approval of mHealth products will require demonstration of safety and effectiveness, especially where information and trends are not just presented to patients, but used to make treatment recommendations. Three additional hurdles must be overcome to facilitate widespread adoption of this technology, including demonstration of the following: (1) privacy to satisfy regulators, (2) clinical benefit to satisfy clinicians, and (3) economic benefit to satisfy payers. mHealth for diabetes is making rapid strides and is expected to be a transforming technology that will be the next big thing.

Long-term engagement with a mobile self-management system for people with type 2 diabetes

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.