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

A telemonitoring intervention design for patients with poorly controlled type 2 diabetes: protocol for a feasibility study

BACKGROUND

Maintaining optimal glycemic control in type 2 diabetes (T2D) is difficult. Telemedicine has the potential to support people with poorly regulated T2D in the achievement of glycemic control, especially if the telemedicine solution includes a telemonitoring component. However, the ideal telemonitoring design for people with T2D remains unclear. Therefore, the aim of this feasibility study is to evaluate the feasibility of two telemonitoring designs for people with non-insulin-dependent T2D with a goal of identifying the optimal telemonitoring intervention for a planned future large-scale randomized controlled trial.

METHOD

This 3-month randomized feasibility study will be conducted in four municipalities in North Denmark starting in January 2024. There will be 15 participants from each municipality. Two different telemonitoring intervention designs will be tested. One intervention will include self-monitoring of blood glucose (SMBG) combined with sleep and mental health monitoring. The second intervention will include an identical setup but with the addition of blood pressure and activity monitoring. Two municipalities will be allocated to one intervention design, whereas the other two municipalities will be allocated to the second intervention design. Qualitative interviews with participants and clinicians will be conducted to gain insight into their experiences with and acceptance of the intervention designs and trial procedures (e.g., blood sampling and questionnaires). In addition, sources of differences in direct intervention costs between the two alternative interventions will be investigated.

DISCUSSION

Telemonitoring has the potential to support people with diabetes in achieving glycemic control, but the existing evidence is inconsistent, and thus, the optimal design of interventions remains unclear. The results of this feasibility study are expected to produce relevant information about telemonitoring designs for people with T2D and help guide the design of future studies. A well-tested telemonitoring design is essential to ensure the quality of telemedicine initiatives, with goals of user acceptance and improved patient outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov, ID: NCT06134934 . Registered November 1, 2023. The feasibility trial has been approved (N-20230026) by the North Denmark Region Committee on Health Research Ethics (June 5, 2023).

Effects of online support and social media communities on gestational diabetes: A systematic review

BACKGROUND

Gestational diabetes mellitus (GDM) is a common complication in pregnancy that can lead to negative maternal and fetal outcomes. Online support interventions have been suggested as a potential tool to improve the management of GDM.

OBJECTIVE

This systematic review aimed to summarize the effectiveness of social media and online support interventions for the management of GDM.

METHODS

We conducted a thorough systematic search across Web of Science, Scopus, and PubMed, following PRISMA guidelines, and supplemented it with a manual search. Our results included both qualitative and quantitative research. We rigorously assessed quantitative studies for bias using ROBINS-I and RoB 2 tools, ensuring the reliability of our findings.

RESULTS

We incorporated a total of 22 studies, which were comprised of ten qualitative and twelve quantitative studies. Online support interventions were found to have a positive impact on promoting self-care and improving healthcare outcomes for women with GDM. Individualized diet and exercise interventions resulted in lower odds of weight gain and GDM diagnosis, while online prenatal education increased breastfeeding rates. In addition, telemedicine options reduced the need for in-person clinical visits and improved patient satisfaction.

CONCLUSIONS

Online support interventions show potential to improve outcomes in patients with GDM in this small literature review. Future research is also necessary to determine the effectiveness of different types of online interventions and identify strategies to improve engagement and the quality of the information provided through online resources.

Clinical impact of an integrated e-health system for diabetes self-management support and shared decision making (POWER2DM): a randomised controlled trial

AIMS/HYPOTHESIS

There is a lack of e-health systems that integrate the complex variety of aspects relevant for diabetes self-management. We developed and field-tested an e-health system (POWER2DM) that integrates medical, psychological and behavioural aspects and connected wearables to support patients and healthcare professionals in shared decision making and diabetes self-management.

METHODS

Participants with type 1 or type 2 diabetes (aged >18 years) from hospital outpatient diabetes clinics in the Netherlands and Spain were randomised using randomisation software to POWER2DM or usual care for 37 weeks. This RCT assessed the change in HbA1c between the POWER2DM and usual care groups at the end of the study (37 weeks) as a primary outcome measure. Participants and clinicians were not blinded to the intervention. Changes in quality of life (QoL) (WHO-5 Well-Being Index [WHO-5]), diabetes self-management (Diabetes Self-Management Questionnaire - Revised [DSMQ-R]), glycaemic profiles from continuous glucose monitoring devices, awareness of hypoglycaemia (Clarke hypoglycaemia unawareness instrument), incidence of hypoglycaemic episodes and technology acceptance were secondary outcome measures. Additionally, sub-analyses were performed for participants with type 1 and type 2 diabetes separately.

RESULTS

A total of 226 participants participated in the trial (108 with type 1 diabetes; 118 with type 2 diabetes). In the POWER2DM group (n=111), HbA1c decreased from 60.6±14.7 mmol/mol (7.7±1.3%) to 56.7±12.1 mmol/mol (7.3±1.1%) (means ± SD, p<0.001), compared with no change in the usual care group (n=115) (baseline: 61.7±13.7 mmol/mol, 7.8±1.3%; end of study: 61.0±12.4 mmol/mol, 7.7±1.1%; p=0.19) (between-group difference 0.24%, p=0.008). In the sub-analyses in the POWER2DM group, HbA1c in participants with type 2 diabetes decreased from 62.3±17.3 mmol/mol (7.9±1.6%) to 54.3±11.1 mmol/mol (7.1±1.0%) (p<0.001) compared with no change in HbA1c in participants with type 1 diabetes (baseline: 58.8±11.2 mmol/mol [7.5±1.0%]; end of study: 59.2±12.7 mmol/mol [7.6±1.2%]; p=0.84). There was an increase in the time during which interstitial glucose levels were between 3.0 and 3.9 mmol/l in the POWER2DM group, but no increase in clinically relevant hypoglycaemia (interstitial glucose level below 3.0 mmol/l). QoL improved in participants with type 1 diabetes in the POWER2DM group compared with the usual care group (baseline: 15.7±3.8; end of study: 16.3±3.5; p=0.047 for between-group difference). Diabetes self-management improved in both participants with type 1 diabetes (from 7.3±1.2 to 7.7±1.2; p=0.002) and those with type 2 diabetes (from 6.5±1.3 to 6.7±1.3; p=0.003) within the POWER2DM group. The POWER2DM integrated e-health support was well accepted in daily life and no important adverse (or unexpected) effects or side effects were observed.

CONCLUSIONS/INTERPRETATION

POWER2DM improves HbA1c levels compared with usual care in those with type 2 diabetes, improves QoL in those with type 1 diabetes, improves diabetes self-management in those with type 1 and type 2 diabetes, and is well accepted in daily life.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03588104.

FUNDING

This study was funded by the European Union's Horizon 2020 Research and Innovation Programme (grant agreement number 689444).

The Use of Digital Telehealth for the Self-Management of Type 2 Diabetes Patients in Hinds County, Mississippi: A Pilot Study

Self-management is crucial for the management of type 2 diabetes. Remote patient monitoring via telehealth may enhance self-management and control of diabetes. A three-arm randomized controlled trial involving 90 participants randomized into two intervention groups and one control group was conducted. The purpose of this study is to test whether the use of a mobile phone-based app, with or without telehealth counseling, could improve HbA1c level, self-management, and health-related quality of life compared with usual care. The two intervention groups received a mobile phone with a self-management app. One intervention group additionally received telehealth counseling delivered by a diabetes specialist nurse for 6 months. All three groups continued to receive the usual care from their provider. The primary outcome is a reduction in HbA1c level. Secondary outcomes are self-management, health-related quality of life, depressive symptoms, and lifestyle changes. Data were analyzed using univariate and multivariate (descriptive, t-test, MANOVA) methods. There was a significant reduction in the HbA1c levels of participants after 3 and 6 months. There was also a significant difference in HbA1c levels between the control and two intervention groups. Pre- and posteducation surveys for intervention group 2 showed an improvement in the understanding of type 2 diabetes risk factors, diabetes, and self-management. Digital telehealth demonstrated considerable potential for reducing blood sugar levels, enhancing self-management, and improving the quality of life of type 2 diabetic patients. The addition of telehealth education and counseling further improved the positive outcomes.

Digital health interventions for non-communicable disease management in primary health care in low-and middle-income countries

Current evidence on digital health interventions is disproportionately concerned with high-income countries and hospital settings. This scoping review evaluates the extent of use and effectiveness of digital health interventions for non-communicable disease (NCD) management in primary healthcare settings of low- and middle-income countries (LMICs) and identifies factors influencing digital health interventions' uptake. We use PubMed, Embase, and Web of Science search results from January 2010 to 2021. Of 8866 results, 52 met eligibility criteria (31 reviews, 21 trials). Benchmarked against World Health Organization's digital health classifications, only 14 out of 28 digital health intervention categories are found, suggesting critical under-use and lagging innovation. Digital health interventions' effectiveness vary across outcomes: clinical (mixed), behavioral (positively inclined), and service implementation outcomes (clear effectiveness). We further identify multiple factors influencing digital health intervention uptake, including political commitment, interactivity, user-centered design, and integration with existing systems, which points to future research and practices to invigorate digital health interventions for NCD management in primary health care of LMICs.

The Diabetes teleMonitoring of patients in insulin Therapy (DiaMonT) trial: study protocol for a randomized controlled trial

BACKGROUND

The effect of telemedicine solutions in diabetes remains inconclusive. However, telemedicine studies have shown a positive trend in regards to glycemic control. The telemedicine interventions that facilitate adjustment of medication seems to improve glycemic control more effectively. Hence, it is recommended that future telemedicine studies for patients with diabetes include patient-specific suggestions for changes in medicine. Hence, the aim of the trial is to explore the effect of telemonitoring in patients with type 2 diabetes (T2D) on insulin therapy.

METHODS

The trial is an open-label randomized controlled trial with a trial period of 3 months conducted in two sites in Denmark. Patients with T2D on insulin therapy will be randomized (1:1) to a telemonitoring group (intervention) or a usual care group (control). The telemonitoring group will use a continuous glucose monitor (CGM), an insulin pen, an activity tracker, and smartphone applications throughout the trial. Hospital staff will monitor the telemonitoring group and contact the subjects by telephone repeatedly throughout the trial period. The usual care group will use a blinded CGM the first and last 20 days of the trial and will use a blinded insulin pen for the entire period. The primary endpoint will be changed from baseline in CGM time in range (3.9-10.0 mmol/L) 3 months after randomization. Secondary endpoints include change from baseline in glycated hemoglobin (HbA1c), total daily dose, time above range, and time below range 3 months after randomization. Exploratory endpoints include health-related quality of life, diabetes-related quality of life, etc. DISCUSSION: The DiaMonT trial will test a telemonitoring setup including various devices. Such a setup may be criticized, because it is impossible to determine which element(s) add to the potential effect. However, it is not possible and counterproductive to test the elements individually, since it is the full telemedicine setup that is being evaluated. The DiaMonT trial is the first Danish trial to explore the effect of telemonitoring on patients on insulin therapy. Thus, the DiaMonT trial has the potential to form the basis for the implementation of telemedicine for patients with T2D in Denmark.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04981808. Registered on 8 June 2021.

The Use of Mobile Health Interventions for Outcomes among Middle-Aged and Elderly Patients with Prediabetes: A Systematic Review

BACKGROUND

There are currently limited systematic reviews of mobile health interventions for middle-aged and elderly patients with prediabetes from trial studies. This review aimed to gather and analyze information from experimental studies investigating the efficacy of mobile health usability for outcomes among middle-aged and elderly patients with prediabetes.

METHODS

We conducted a literature search in five databases: Clinicaltrials.gov, the International Clinical Trials Registry Platform (ICTRP), PubMed, ProQuest, and EBSCO, with a date range of January 2007 to July 2022 written in English, following a registered protocol on PROSPERO (CRD42022354351). The quality and possibility of bias were assessed using the Jadad score. The data extraction and analysis were conducted in a methodical manner.

RESULTS

A total of 25 studies were included in the qualitative synthesis, with 19 studies using randomized trial designs and 6 studies with non-randomized designs. The study outcomes were the incidence of diabetes mellitus, anthropometric measures, laboratory examinations, measures of physical activity, and dietary behavior. During long-term follow-up, there was no significant difference between mobile health interventions and controls in reducing the incidence of type 2 diabetes. The findings of the studies for weight change, ≥3% and ≥5% weight loss, body mass index, and waist circumference changes were inconsistent. The efficacy of mobile health as an intervention for physical activity and dietary changes was lacking in conclusion. Most studies found that mobile health lacks sufficient evidence to change hbA1c. According to most of these studies, there was no significant difference in blood lipid level reduction.

CONCLUSIONS

The use of mobile health was not sufficiently proven to be effective for middle-aged and elderly patients with prediabetes.

Effectiveness of training in disease management for patients with type 2 diabetes mellitus: A systematic review

INTRODUCTION

Diabetes mellitus (DM) is included in the disease group described as the pandemic of the century. Although disease management is possible, it can significantly reduce the quality of life when glycaemic control is poor. The objective of this systematic review was to examine the effectiveness of different educational programmes on the management of the disease among type 2 DM patients.

METHODS

In the literature review, the flow chart of PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) was used. A literature search was conducted from 2010 to 2020 using the Ulakbim National Database, Google Scholar, Scopus, PubMed, Library, Science Direct, Web of Science, Medline, Ebscohost and Cochrane Library, and 18 English randomised controlled studies were included.

RESULTS

Within the scope of these studies, it was found that individualised and face-to-face training and long-term follow-up after the training were effective on metabolic control. Peer support was also determined as an important factor in the efficacy of the training. In line with the training, the self-management and quality-of-life scores of the individuals with diabetes were positively affected.

CONCLUSIONS

It can be suggested that planned and regular training has a positive effect on metabolic control variables, self-management behaviours and quality of life of individuals with diabetes. Regular training for individuals with diabetes and follow-up for more than 6 months are recommended since they have a positive effect on the disease. It is also recommended to integrate peer support into training programmes.

The Effectiveness of Telemedicine Solutions in Type 1 Diabetes Management: A Systematic Review and Meta-analysis

BACKGROUND

Telemedicine holds a potential to strengthen self-management support outside health care settings in the everyday management of type 1 diabetes (T1D). However, existing effectiveness reviews are older or include a relatively narrow focus on specific definitions of telemedicine or included databases.

OBJECTIVE

To conduct a systematic review of the effectiveness of telemedicine solutions versus any comparator on diabetes-related outcomes among people with T1D.

METHODS

Studies including adults (≥18 years) with T1D published before October 14, 2020, were eligible. Primary outcome was glycated hemoglobin (HbA1c, %). The Cochrane Library, PubMed, EMBASE, and CINAHL were searched. Meta-analysis based on the mean difference in HbA1c% was used to pool effects. The Cochrane tool was applied to assess risk-of-bias, and the certainty of evidence was graded using the GRADE approach.

RESULTS

A total of 22 studies were included (with 1615 participants). Treatment effect for HbA1c% favored telemedicine (mean difference of -0.26% [95% confidence interval:-0.37% to -0.15%]) with moderate effect certainty. Heterogeneity was moderate (I² = 33.30%). Although not significant, secondary outcomes were all in favor of telemedicine except number of severe hypoglycemic events and diabetes knowledge, but the certainty of the evidence for those outcomes was all low or very low.

DISCUSSION

Reducing average HbA1c% levels are important to combat the risk of diabetic complications and premature death. However, the evidence mostly consist of small studies with a relative short duration and the estimated pooled effect is smaller than could be expected from quality improvement strategies in general for diabetes management.

PROSPERO NUMBER

CRD42020123565.

The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression

BACKGROUND

Previous systematic reviews have aimed to clarify the effect of telemedicine on diabetes. However, such reviews often have a narrow focus, which calls for a more comprehensive systematic review within the field. Hence, the objective of the present systematic review, meta-analysis, and meta-regression is to evaluate the effectiveness of telemedicine solutions versus any comparator without the use of telemedicine on diabetes-related outcomes among adult patients with type 2 diabetes (T2D).

METHODS

This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We considered telemedicine randomized controlled trials (RCT) including adults (≥18 years) diagnosed with T2D. Change in glycated hemoglobin (HbA1c, %) was the primary outcome. PubMed, EMBASE, and the Cochrane Library Central Register of Controlled Trials (CENTRAL) were searched on October 14, 2020. An overall treatment effect was estimated using a meta-analysis performed on the pool of included studies based on the mean difference (MD). The revised Cochrane risk-of-bias tool was applied and the certainty of evidence was graded using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

RESULTS

The final sample of papers included a total of 246, of which 168 had sufficient information to calculate the effect of HbA1c%. The results favored telemedicine, with an MD of -0.415% (95% confidence interval [CI] = -0.482% to -0.348%). The heterogeneity was great (I² = 93.05%). A monitoring component gave rise to the higher effects of telemedicine.

CONCLUSIONS

In conclusion, telemedicine may serve as a valuable supplement to usual care for patients with T2D. The inclusion of a telemonitoring component seems to increase the effect of telemedicine.

Effectiveness of training in disease management for patients with type 2 diabetes mellitus: A systematic review

INTRODUCTION

Diabetes mellitus (DM) is included in the disease group described as the pandemic of the century. Although disease management is possible, it can significantly reduce the quality of life when glycaemic control is poor. The objective of this systematic review was to examine the effectiveness of different educational programmes on the management of the disease among type 2 DM patients.

METHODS

In the literature review, the flow chart of PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) was used. A literature search was conducted from 2010 to 2020 using the Ulakbim National Database, Google Scholar, Scopus, PubMed, Library, Science Direct, Web of Science, Medline, Ebscohost and Cochrane Library, and 18 English randomised controlled studies were included.

RESULTS

Within the scope of these studies, it was found that individualised and face-to-face training and long-term follow-up after the training were effective on metabolic control. Peer support was also determined as an important factor in the efficacy of the training. In line with the training, the self-management and quality-of-life scores of the individuals with diabetes were positively affected.

CONCLUSIONS

It can be suggested that planned and regular training has a positive effect on metabolic control variables, self-management behaviours and quality of life of individuals with diabetes. Regular training for individuals with diabetes and follow-up for more than 6 months are recommended since they have a positive effect on the disease. It is also recommended to integrate peer support into training programmes.

Digital Health: Unlocking Value in a Post-Pandemic World

The COVID-19 pandemic has forever changed health care, spurring a revolution in digital health technologies. Across the world, hundreds of thousands of health care systems are considering a central question: how do we connect with our patients? Digital health has been used as a stopgap in many cases to continue the essential functions of health systems. As the post-pandemic world and our "new normal" come into focus, further needs will have to be met with a digital patient interaction, with an eye toward value transformation. One barrier to fully leveraging digital tools is the lack of a framework for classifying the type of digital health care. This can limit our ability to design, deploy, evaluate, and communicate through digital means. This article presents 3 categories of digital health and their relationships to value metrics: (1) telehealth or direct care delivery, (2) digital access tools, and (3) digital monitoring. An evidence-based discussion reveals past successes, current promises, and future challenges in reducing defects in value through digital care. In the coming years, value transformation will become more crucial to the success of health care systems. By using the taxonomy in this article, health systems can better implement digital tools with a value-driven purpose. Defining the role of digital health in the post-pandemic world is needed to assist health systems and practices to build a bridge to value-based care.

Telemetric Interventions Offer New Opportunities for Managing Type 1 Diabetes Mellitus: Systematic Meta-review

BACKGROUND

The prevalence of diabetes mellitus (DM) is increasing rapidly worldwide. Simultaneously, technological advances are offering new opportunities for better management of type 1 diabetes mellitus (T1DM). Telemetry, the remote acquisition of patient data via a telecommunication system, is a promising field of application in eHealth and is rapidly gaining importance.

OBJECTIVE

The aim of this study was to summarize the current evidences available on the effectiveness of telemetric approaches in T1DM management. This systematic meta-review examined different types of interventions of the technologies used in communication between health care professionals and patients as well as the key outcomes.

METHODS

We performed a systematic search in Web of Science Core Collection, EMBASE, Cochrane Library, MEDLINE via PubMed, and CINAHL databases in April 2020 with regard to the effectiveness of telemetric interventions for T1DM. We classified the interventions into 4 categories according to the technology used: (1) real-time video communication, (2) real-time audio communication, (3) asynchronous communication, and (4) combined forms of communication (real-time and asynchronous). We considered various study designs such as systematic reviews, clinical trials, meta-analyses, and randomized controlled trials and focused on the key outcomes. Additionally, a funnel plot based on hemoglobin A_1c (HbA_1c) values and different quality assessments were performed.

RESULTS

We identified 17 (6 high quality and 9 moderate quality) eligible publications: randomized controlled trials (n=9), systematic reviews and meta-analyses (n=5), cohort studies (n=2), and qualitative publications (n=1). Of 12 studies, 8 (67%) indicated a (significant or nonsignificant) reduction in HbA_1c levels; 65% (11/17) of the studies reported overall (mildly) positive effects of telemetric interventions by addressing all the measured outcomes. Asynchronous interventions were the most successful for patients diagnosed with T1DM, but no technology was clearly superior. However, there were many nonsignificant results and not sustained effects, and in some studies, the control group benefited from telemetric support or increased frequency of contacts.

CONCLUSIONS

Based on the currently available literature, this systematic meta-review shows that telemetric interventions cause significant reduction in HbA_1c levels and result in overall positive effects in T1DM management. However, more specified effects of telemetric approaches in T1DM management should be analyzed in detail in larger cohorts.

A Web-Based eHealth Intervention to Improve the Quality of Life of Older Adults With Multiple Chronic Conditions: Protocol for a Randomized Controlled Trial

Background

Multiple chronic conditions (MCCs) are common among older adults and expensive to manage. Two-thirds of Medicare beneficiaries have multiple conditions (eg, diabetes and osteoarthritis) and account for more than 90% of Medicare spending. Patients with MCCs also experience lower quality of life and worse medical and psychiatric outcomes than patients without MCCs. In primary care settings, where MCCs are generally treated, care often focuses on laboratory results and medication management, and not quality of life, due in part to time constraints. eHealth systems, which have been shown to improve multiple outcomes, may be able to fill the gap, supplementing primary care and improving these patients’ lives.

Objective

This study aims to assess the effects of ElderTree (ET), an eHealth intervention for older adults with MCCs, on quality of life and related measures.

Methods

In this unblinded study, 346 adults aged 65 years and older with at least 3 of 5 targeted high-risk chronic conditions (hypertension, hyperlipidemia, diabetes, osteoarthritis, and BMI ≥30 kg/m2) were recruited from primary care clinics and randomized in a ratio of 1:1 to one of 2 conditions: usual care (UC) plus laptop computer, internet service, and ET or a control consisting of UC plus laptop and internet but no ET. Patients with ET have access for 12 months and will be followed up for an additional 6 months, for a total of 18 months. The primary outcomes of this study are the differences between the 2 groups with regard to measures of quality of life, psychological well-being, and loneliness. The secondary outcomes are between-group differences in laboratory scores, falls, symptom distress, medication adherence, and crisis and long-term health care use. We will also examine the mediators and moderators of the effects of ET. At baseline and months 6, 12, and 18, patients complete written surveys comprising validated scales selected for good psychometric properties with similar populations; laboratory data are collected from eHealth records; health care use and chronic conditions are collected from health records and patient surveys; and ET use data are collected continuously in system logs. We will use general linear models and linear mixed models to evaluate primary and secondary outcomes over time, with treatment condition as a between-subjects factor. Separate analyses will be conducted for outcomes that are noncontinuous or not correlated with other outcomes.

Results

Recruitment was conducted from January 2018 to December 2019, and 346 participants were recruited. The intervention period will end in June 2021.

Conclusions

With self-management and motivational strategies, health tracking, educational tools, and peer community and support, ET may help improve outcomes for patients coping with ongoing, complex MCCs. In addition, it may relieve some stress on the primary care system, with potential cost implications.

Trial Registration

ClinicalTrials.gov NCT03387735; https://www.clinicaltrials.gov/ct2/show/NCT03387735.

International Registered Report Identifier (IRRID)

DERR1-10.2196/25175

Clinical Improvements by Telemedicine Interventions Managing Type 1 and Type 2 Diabetes: Systematic Meta-review

Background

Diabetes mellitus (DM) is one of the world’s greatest health threats with rising prevalence. Global digitalization leads to new digital approaches in diabetes management, such as telemedical interventions. Telemedicine, which is the use of information and communication technologies, may provide medical services over spatial distances to improve clinical patient outcomes by increasing access to diabetes care and medical information.

Objective

This study aims to examine whether telemedical interventions effectively improve diabetes control using studies that pooled patients with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), and whether the benefits are greater in patients diagnosed with T2DM than in those diagnosed with T1DM. We analyzed the primary outcome glycated hemoglobin A_1c (HbA_1c) and the secondary outcomes fasting blood glucose (FBG), blood pressure (BP), body weight, BMI, quality of life (QoL), cost, and time saving.

Methods

Publications were systematically identified by searching Cochrane Library, MEDLINE via PubMed, Web of Science Core Collection, Embase, and CINAHL databases for studies published between January 2008 and April 2020, considering systematic reviews (SRs), meta-analyses (MAs), randomized controlled trials (RCTs), and clinical trials (CTs). Study quality was assessed using the A Measurement Tool to Assess Systematic Reviews, Effective Public Health Practice Project, and National Institute for Health and Care Excellence qualitative checklist. We organized the trials by communication technologies in real-time video or audio interventions, asynchronous interventions, and combined interventions (synchronous and asynchronous communication).

Results

From 1116 unique citations, we identified 31 eligible studies (n=15 high, n=14 moderate, n=1 weak, and n=1 critically low quality). We selected 21 SRs and MAs, 8 RCTs, 1 non-RCT, and 1 qualitative study. Of the 10 trials, 3 were categorized as real-time video, 1 as real-time video and audio, 4 as asynchronous, and 2 as combined intervention. Significant decline in HbA_1c levels based on pooled T1DM and T2DM patients data ranged from −0.22% weighted mean difference (WMD; 95% CI −0.28 to −0.15; P<.001) to −0.64% mean difference (95% CI −1.01 to −0.26; P<.001). The intervention effect on lowering HbA_1c values might be significantly smaller for patients with T1DM than for patients with T2DM. Evidence on the impact on BP, body weight, FBG, cost effectiveness, and time saving was smaller compared with HbA_1c but indicated potential in some publications.

Conclusions

Telemedical interventions might be clinically effective in improving diabetes control overall, and they might significantly improve HbA_1c concentrations. Patients with T2DM could benefit more than patients with T1DM regarding lowering HbA_1c levels. Further studies with longer duration and larger cohorts are necessary.

Effects of mobile health interventions on improving glycemic stability and quality of life in patients with type 1 diabetes: A meta-analysis

This meta-analysis aimed to examine the effects of mobile-health-based (mHealth) interventions on improving glycemic stability and quality of life (QOL) in patients with type 1 diabetes (T1D). Various databases, including PubMed, Embase, CINAHL, Cochrane Library, ProQuest, Chinese Electronic Periodical Services, and China Knowledge Resource Integrated, were used to search for relevant articles. A fixed-effects model or random-effects model was used to examine the overall effect. Various methods, including Egger's test, Begg's test, and trim-and-fill, were adopted to examine publication bias. In total, 26 studies were recruited. Results of the random-effects model showed that the use of mHealth-based interventions significantly decreased glycated hemoglobin (HbA1c) (mean difference = -0.37, 95% confidence interval (CI) = -0.53 to -0.22, p < .001), and improved life satisfaction (Hedges' g = 0.30, 95% CI = 0.10 to 0.50, p = .003), worry of diabetes (Hedges' g = -0.25, 95% CI = -0.41 to 0.08, p = .004), and mental health (Hedges' g = 0.36, 95% CI = 0.08 to 0.64, p = .012). Both adults and youths with T1D can benefit from mHealth-based interventions to improve HbA1c (Hedges' g = -0.44, p = .002 vs. -0.30, p = .003). The effect of mHealth-based interventions on improving QOL in both adults and youths could not be examined due to only one study published in adults with T1D. Moreover, those studies that included the function of feedback from professionals showed a significant effect of decreasing HbA1c compared to those without that function (Hedges' g = -0.48 vs. -0.16, p = .019). Mobile devices are convenient, instantaneous, and easy to use to communicate. Applying mHealth-based interventions with the function of feedback from professionals can be considered an alternative healthcare service to achieve optimal glycemic stability in adults and youths with T1D.

Effectiveness of Telemedicine Solutions for the Management of Patients With Diabetes: Protocol for a Systematic Review and Meta-Analysis

Background

Telemedicine is often suggested as a promising approach to support patients with diabetes. However, the effectiveness of diabetes-related telemedicine interventions in regard to patient-related outcomes requires further evaluation. Previous systematic reviews describing the effectiveness of telemedicine in diabetes management focus on a specific type of telemedicine, a specific type of diabetes, specific comparators, or specific outcomes. Moreover, the rapid development within telemedicine emphasizes the need for a new review.

Objective

The present review has a broad scope with an eye to performing an updated and exhaustive review within the field. The review aims to evaluate the effectiveness of existing telemedicine solutions versus any comparator without the use of telemedicine on diabetes-related outcomes among adult patients with diabetes.

Methods

The review will consider studies that include adult subjects with a diagnosis of diabetes (type 1, 2, or gestational), studies that evaluate various types of telemedicine interventions, and randomized controlled trials comparing a telemedicine intervention to any control that does not include telemedicine. Peer-reviewed full-text papers in English, Norwegian, Danish, and Swedish will be considered. A thorough search will be performed in the PubMed, CINAHL, EMBASE, and Cochrane Library Central Register of Controlled Trials (CENTRAL) databases. Data extraction will include details about the populations, study methods, interventions, and outcomes of significance based on the review objective.

Results

The results of the review are expected to provide an estimate of the treatment effect. The studies will be pooled via statistical meta-analysis and supplemented with narrative comparisons when necessary.

Conclusions

The review is important as it will inform clinicians and investigators about the effect of various telemedicine solutions within the field of diabetes.

International Registered Report Identifier (IRRID)

DERR1-10.2196/22062

E-health education interventions on HbA1c in patients with type 1 diabetes on intensive insulin therapy: A systematic review and meta-analysis of randomized controlled trials

AIMS

Patient-centered education improves glycemic control in subjects with type 1 diabetes (T1D). E-health technologies are widely used to support medical decision-making, patient advising or teleconsultations; however, the active participation of a patient is missing. Challenges remain whether e-health education can be effectively incorporated into clinical pathways. The purpose of the study was to examine the effects of e-health education, compared to standard care, on HbA_1c. MATERIAL AND METHODS: We conducted a literature search (EMBASE, MEDLINE, The Cochrane Library and Web of Science) up to February 2018 for randomized controlled trials (RCTs) of Internet-/ mobile application-based educational interventions, with the active involvement of patients, provided in addition to, or substituting usual care in patients with T1D on intensive insulin therapy. The primary outcome was the standardized difference in means (SDM) of HbA_1c change from baseline between intervention and comparator groups.

RESULTS

Eight RCTs involving 757 subjects were included on 6335 screened citations. After excluding two trials with a high risk of bias from the meta-analysis, the HbA_1c change from baseline did not significantly differ between intervention and comparator groups (SDM = -0.154, 95% CI: -0.335 to 0.025; P = 0.01, random-effect model). The number of studies is limited with a relatively short duration. Reporting of educational outcomes was not rigorous.

CONCLUSIONS

The effect of e-health educational interventions on HbA_1c in patients with T1D is comparable to the standard care. This review highlights the need for further well-designed RCTs that will investigate the opportunities of incorporating e-health education into clinical pathways.

Assessing the user experience and usability of the PRECIOUS system: a randomized controlled trial in obese patients

Objective To assess users' usability, satisfaction, acceptance and effectiveness of the PRECIOUS system to promote behavior change toward healthier lifestyles. Design: Thirty-one adult patients with BMI>30 (M = 44.23, SD = 5.91) were recruited and randomized into three conditions for a longitudinal study (3 months length): 1) Control group (TAU + biofeedback + follow-ups); 2) PRECIOUS only (app + biofeedback + follow-ups); 3) PRECIOUS + MI (app + biofeedback + motivational interviewing follow-ups). Main Outcome Measures: Usability, satisfaction, acceptance and effectiveness of PRECIOUS, and stages of change (S-Weight questionnaire). Results: The system was described as easy to use, flexible, fairly satisfying and good as a preventive health system. Participants rated biofeedback and the Physical Activity module as the most satisfying features. However, participants were unsatisfied with the Diet module. All additional features received acceptable scores in terms of satisfaction. Despite this, the PRECIOUS only group reported that they would probably recommend the system to others because it meets its purposes quite well. Conclusion: PRECIOUS was found a usable and acceptable solution, although improving several features in the Diet module in successive versions of the app would promote sustained use and satisfaction among users, possibly increasing its effectiveness in promoting healthier lifestyles. Abbreviations: ADA American Diabetes Association; BG2: BodyGuard2; BMI: Body Mass Index; CBT: Cognitive-behavioral therapy; EMA: Ecological Momentary Assessment; eHealth: Electronic health; mHealth: Mobile health; MI: Motivational interviewing; NCD: Non-communicable diseases; PA: Physical activity; PRECIOUS: PREventive Care Infrastructure based On Ubiquitous Sensing.

A Web-Based Mobile App (INTERACCT App) for Adolescents Undergoing Cancer and Hematopoietic Stem Cell Transplantation Aftercare to Improve the Quality of Medical Information for Clinicians: Observational Study

Background

A growing number of cancer and hematopoietic stem cell transplant (HSCT) survivors require long-term follow-up with optimal communication schemes, and patients' compliance is crucial. Adolescents have various unmet needs. Regarding self-report of symptoms and health status, users of mobile apps showed enhanced compliance. Currently, HSCT aftercare at the HSCT outpatient clinic of the St. Anna Children’s Hospital in Vienna, Austria, is based on handwritten diaries, carrying various disadvantages. Recently, we developed the prototype of a web-based, self-monitoring gamified mobile app tailored for adolescents: the INTERACCT (Integrating Entertainment and Reaction Assessment into Child Cancer Therapy) app.

Objective

This observational, prospective study evaluated the usability of the INTERACCT app for tracking real-time self-reported symptoms and health status data in adolescent HSCT patients and a healthy matched control group. The primary outcome of the study was the quality of the self-reported medical information. We hypothesized that the mobile app would provide superior medical information for the clinicians than would the handwritten diaries.

Methods

Health data were reported via paper diary and mobile app for 5 consecutive days each. The quality of medical information was rated on a 5-point scale independently and blinded by two HSCT clinicians, and the duration of use was evaluated. A total of 52 participant questionnaires were assessed for gaming patterns and device preferences, self-efficacy, users’ satisfaction, acceptability, and suggestions for improvement of the mobile app. Interrater reliability was calculated with the intraclass correlation coefficient, based on a two-way mixed model; one-way repeated-measures analysis of variance and t tests were conducted post hoc. Descriptive methods were used for correlation with participants’ demographics. For users’ satisfaction and acceptability of the mobile app, the median and the IQR were calculated.

Results

Data from 42 participants—15 patients and 27 healthy students—with comparable demographics were evaluated. The results of our study indicated a superiority of the quality of self-reported medical data in the INTERACCT app over traditional paper-and-pencil assessment (mobile app: 4.14 points, vs paper-based diary: 3.77 points, P=.02). The mobile app outperformed paper-and-pencil assessments mainly among the patients, in particular among patients with treatment-associated complications (mobile app: 4.43 points, vs paper-based diary: 3.73 points, P=.01). The mobile app was used significantly longer by adolescents (≥14 years: 4.57 days, vs ≤13 years: 3.14 days, P=.03) and females (4.76 days for females vs 2.95 days for males, P=.004). This corresponds with a longer duration of use among impaired patients with comorbidities. User satisfaction and acceptability ratings for the mobile app were high across all groups, but adherence to entering a large amount of data decreased over time. Based on our results, we developed a case vignette of the target group.

Conclusions

Our study was the first to show that the quality of patient-reported medical information submitted via the INTERACCT app embedded in a serious game is superior to that submitted via a handwritten diary. In light of these results, a refinement of the mobile app supported by a machine learning approach is planned within an international research project.

Primary Care Clinic Nurse Activities with a Telehealth Monitoring System

The purpose of this study was to evaluate differences in the types of nursing activities and communication processes reported in a primary care clinic between patients who used a home-based monitoring system to electronically communicate self-monitored blood glucose and blood pressure values and those who assumed usual care. Data were extracted from electronic medical records from individuals who participated in a randomized controlled trial comparing in-home monitoring and usual care in patients with Type 2 diabetes and hypertension being treated in a primary care clinic. Data about nursing activities initiated by primary care clinic nurses were compared between groups using descriptive statistics and independent t-tests. Significant differences between groups were identified for the direct care nursing activities of providing lifestyle and health education, medication adjustments, and patient follow-up. This study provides evidence of greater nursing activity reported in a primary care clinic in patients who utilized a home-based monitoring system.

Effectiveness of Mobile Health Interventions on Diabetes and Obesity Treatment and Management: Systematic Review of Systematic Reviews

BACKGROUND

Diabetes and obesity have become epidemics and costly chronic diseases. The impact of mobile health (mHealth) interventions on diabetes and obesity management is promising; however, studies showed varied results in the efficacy of mHealth interventions.

OBJECTIVE

This review aimed to evaluate the effectiveness of mHealth interventions for diabetes and obesity treatment and management on the basis of evidence reported in reviews and meta-analyses and to provide recommendations for future interventions and research.

METHODS

We systematically searched the PubMed, IEEE Xplore Digital Library, and Cochrane databases for systematic reviews published between January 1, 2005, and October 1, 2019. We analyzed 17 reviews, which assessed 55,604 original intervention studies, that met the inclusion criteria. Of those, 6 reviews were included in our meta-analysis.

RESULTS

The reviews primarily focused on the use of mobile apps and text messaging and the self-monitoring and management function of mHealth programs in patients with diabetes and obesity. All reviews examined changes in biomarkers, and some reviews assessed treatment adherence (n=7) and health behaviors (n=9). Although the effectiveness of mHealth interventions varied widely by study, all reviews concluded that mHealth was a feasible option and had the potential for improving patient health when compared with standard care, especially for glycemic control (-0.3% to -0.5% greater reduction in hemoglobin A1c) and weight reduction (-1.0 kg to -2.4 kg body weight). Overall, the existing 6 meta-analysis studies showed pooled favorable effects of these mHealth interventions (-0.79, 95% CI -1.17 to -0.42; I2=90.5).

CONCLUSIONS

mHealth interventions are promising, but there is limited evidence about their effectiveness in glycemic control and weight reduction. Future research to develop evidence-based mHealth strategies should use valid measures and rigorous study designs. To enhance the effectiveness of mHealth interventions, future studies are warranted for the optimal formats and the frequency of contacting patients, better tailoring of messages, and enhancing usability, which places a greater emphasis on maintaining effectiveness over time.

Mapping the Evidence on the Effectiveness of Telemedicine Interventions in Diabetes, Dyslipidemia, and Hypertension: An Umbrella Review of Systematic Reviews and Meta-Analyses

Background

Telemedicine is defined by three characteristics: (1) using information and communication technologies, (2) covering a geographical distance, and (3) involving professionals who deliver care directly to a patient or a group of patients. It is said to improve chronic care management and self-management in patients with chronic diseases. However, currently available guidelines for the care of patients with diabetes, hypertension, or dyslipidemia do not include evidence-based guidance on which components of telemedicine are most effective for which patient populations.

Objective

The primary aim of this study was to identify, synthesize, and critically appraise evidence on the effectiveness of telemedicine solutions and their components on clinical outcomes in patients with diabetes, hypertension, or dyslipidemia.

Methods

We conducted an umbrella review of high-level evidence, including systematic reviews and meta-analyses of randomized controlled trials. On the basis of predefined eligibility criteria, extensive automated and manual searches of the databases PubMed, EMBASE, and Cochrane Library were conducted. Two authors independently screened the studies, extracted data, and carried out the quality assessments. Extracted data were presented according to intervention components and patient characteristics using defined thresholds of clinical relevance. Overall certainty of outcomes was assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool.

Results

Overall, 3564 references were identified, of which 46 records were included after applying eligibility criteria. The majority of included studies were published after 2015. Significant and clinically relevant reduction rates for glycated hemoglobin (HbA_1c; ≤−0.5%) were found in patients with diabetes. Higher reduction rates were found for recently diagnosed patients and those with higher baseline HbA_1c (>8%). Telemedicine was not found to have a significant and clinically meaningful impact on blood pressure. Only reviews or meta-analyses reporting lipid outcomes in patients with diabetes were found. GRADE assessment revealed that the overall quality of the evidence was low to very low.

Conclusions

The results of this umbrella review indicate that telemedicine has the potential to improve clinical outcomes in patients with diabetes. Although subgroup-specific effectiveness rates favoring certain intervention and population characteristics were found, the low GRADE ratings indicate that evidence can be considered as limited. Future updates of clinical care and practice guidelines should carefully assess the methodological quality of studies and the overall certainty of subgroup-specific outcomes before recommending telemedicine interventions for certain patient populations.

Application of Artificial Intelligence Techniques for the Estimation of Basal Insulin in Patients with Type I Diabetes

Artificial intelligence techniques have been positioned in the resolution of problems in various areas of healthcare. Clinical decision support systems developed from this technology have optimized the healthcare of patients with chronic diseases through mobile applications. In this study, several models based on this methodology have been developed to calculate the basal insulin dose in patients with type I diabetes using subcutaneous insulin infusion pumps. Methods. A pilot experimental study was performed with data from 56 patients with type 1 diabetes who used insulin infusion pumps and underwent continuous glucose monitoring. Several models based on artificial intelligence techniques were developed to analyze glycemic patterns based on continuous glucose monitoring and clinical variables in order to estimate the basal insulin dose. We used neural networks (NNs), Bayesian networks (BNs), support vector machines (SVMs), and random forests (RF). We then evaluated the agreement between predicted and actual values using several statistical error measurements: mean absolute error (MAE), mean square error (MSE), root-mean-square error (RMSE), Pearson's correlation coefficient (R), and determination coefficient (R ²). Results. Twenty-four different models were obtained, one for each hour of the day, with each chosen technique. Correlation coefficients obtained with RF, SVMs, NNs, and BNs were 0.9999, 0.9921, 0.0303, and 0.7754, respectively. The error increased between 06:00 and 07:00 and between 13:00 and 17:00. Conclusions. The performance of the RF technique was excellent and got very close to the actual values. Intelligence techniques could be used to predict basal insulin dose. However, it is necessary to explore the validity of the results and select the target population. Models that allow for more accurate levels of prediction should be further explored.

Acceptability of Mobile Health Interventions to Increase Diabetic Risk Factor Awareness Among the Commuter Population in Johannesburg: Descriptive Cross-Sectional Study

BACKGROUND

Developing countries are experiencing a shift from infectious diseases such as HIV and tuberculosis to noncommunicable diseases (NCDs) such as diabetes. Diabetes accounts for more disability-adjusted life years than any other NCD in South Africa, and research has identified a number of preventable risk factors; however, there is not enough evidence from lower resource settings as to how best to disseminate this information to the population. Today, 90% of the world's population lives in mobile phone coverage areas, and this provides a unique opportunity to reach large populations with health information.

OBJECTIVE

This study aimed to investigate how potential mobile health (mHealth) platforms should be paired with diabetes risk factor education so that at-risk communities are empowered with information to prevent and manage diabetes.

METHODS

A Likert-style survey was distributed to commuters in the City of Johannesburg in July 2018 that explored participants' background characteristics as well as their knowledge and awareness surrounding diabetic risk factors (such as exercise, smoking, and hypertension) and their comfort level with various information delivery methods (such as WhatsApp, short message service, and email). The grouped variables from diabetic risk factors and information delivery methods were described with mean Likert scores and then investigated for relationships with Spearman Rho correlation coefficients.

RESULTS

Background characteristics revealed that the self-reported prevalence of diabetes was twice as high in this studied commuter population than the national average. WhatsApp was the most favorable mHealth information delivery method and had a moderate correlation coefficient with diet and nutrition (0.338; P<.001) as well as a weaker correlation with physical activity (0.243; P<.001). Although not as robust as the WhatsApp correlations, each of the other information delivery methods also showed weaker, yet statistically significant, relationships with one or more of the risk factors.

CONCLUSIONS

The elevated self-reported diabetes prevalence reinforces the need for diabetes risk factor education in the studied commuter population of Johannesburg. The most feasible mHealth intervention for diabetic risk factor education should focus on WhatsApp messaging while also offering content across other mHealth and traditional platforms to remove barriers to access and enhance the user experience. The content should emphasize diet and nutrition as well as physical activity while also incorporating information on secondary risk factors.

Mobile Health to Support Ageing in Place

The study reported in this article aimed to identify: i) the most relevant application domains of mHealth to support older adults in their domiciles; ii) the most relevant chronic conditions of older adults, whose management is being supported by mHealth; iii) the characteristics, outcomes and impacts of mHealth tools that might support older adults in their domiciles. The method of a systematic review of reviews and meta-analyses was performed based on a search of the literature. The result of a total of 66 reviews and meta-analyses across several chronic diseases were retrieved. These studies compare mHealth interventions with usual care. The conclusion is that mHealth interventions have positive effects on various health related outcomes, but further research is required to allow their incorporation in the clinical practice.

The influence of mobile health applications on patient - healthcare provider relationships: A systematic, narrative review

OBJECTIVE

To explore the influence of mobile health applications on various dimensions of patient and healthcare provider relationships.

METHODS

A systematic, narrative review of English literature reporting experiences and outcomes of using mobile health applications was performed, evaluating communication and relationships between patients and healthcare professionals. Findings were framed thematically within the four dimensions of relationship-centred care. The methodological quality of included articles was appraised.

RESULTS

Thirty-seven articles were included, all of them meeting tenets of relationship-centred care. After adopting mobile health applications patients perceived an overall positive impact on their relationship with healthcare providers, indicating they are ready to transition from traditional clinical ecounters to a different modality. Use of the applications supported patients in assuming active roles in the management of their health in collaboration with health professionals. Reluctance of providers to using mobile health needs to be acknowledged and addressed when encouraging wider use of applications in clinical practice.

CONCLUSION

The use of mobile health applications can influence communication and relationships between patients and providers positively, facilitating relationship-centered healthcare.

PRACTICE IMPLICATION

Implementation of mobile health can support patients' self-efficacy, improve access to healthcare services and improve relationships between patients and providers in ambulatory and hospital settings.

Appropriation of Mobile Health for Diabetes Self-Management: Lessons From Two Qualitative Studies

BACKGROUND

To achieve clarity on mobile health's (mHealth's) potential in the diabetes context, it is necessary to understand potential users' needs and expectations, as well as the factors determining their mHealth use. Recently, a few studies have examined the user perspective in the mHealth context, but their explanatory value is constrained because of their limitation to adoption factors.

OBJECTIVE

This paper uses the mobile phone appropriation model to examine how individuals with type 1 or type 2 diabetes integrate mobile technology into their everyday self-management. The study advances the field beyond mere usage metrics or the simple dichotomy of adoption versus rejection.

METHODS

Data were gathered in 2 qualitative studies in Singapore and Germany, with 21 and 16 respondents, respectively. Conducting semistructured interviews, we asked respondents about their explicit use of diabetes-related apps, their general use of varied mobile technologies to manage their disease, and their daily practices of self-management.

RESULTS

The analysis revealed that although some individuals with diabetes used dedicated diabetes apps, most used tools across the entire mobile-media spectrum, including lifestyle and messaging apps, traditional health information websites and forums. The material indicated general barriers to usage, including financial, technical, and temporal restrictions.

CONCLUSIONS

In sum, we find that use patterns differ regarding users' evaluations, expectancies, and appropriation styles, which might explain the inconclusive picture of effects studies in the diabetes mHealth context.

Boosting diabetes and pre-diabetes detection in rural Ghana

Background: Diabetes is a growing worldwide disease with serious consequences to health and with a high financial burden. Ghana is one of the developing African countries where the prevalence of diabetes is increasing. Moreover, many cases remain undiagnosed, when along with pre-diabetic cases they can be easily detected. The main objective of this study is to propose a novel method to increase diabetes and pre-diabetes early detection in rural areas. A secondary aim is to look for new related behavioral determinants specific to rural Ghana, by comparing subjects at risk with those already diagnosed as diabetic. Methods: The detection approach was based on tests performed pro-actively by community nurses using glucometers and mobile phone apps. As a pilot for future policies, glycemic tests were carried out on 101 subjects from rural communities in Ghana deemed at risk and unaware of their diabetic/pre-diabetic status. A comparison of dietary and lifestyle habits of the screened people was conducted in regards to a cohort of 103 diabetic patients from the same rural communities. Participants for both groups were found through snow-ball sampling. Results: The pilot screening detected 2 diabetic subjects (2% of the cohort) showing WHO diabetic glycemic values, and 20 pre-diabetic subjects (19.8% of the cohort) which showed the effectiveness of the user-friendly approach. Conclusions: Policies based on prevention screening as reported in the manuscript have the potential to reduce diabetes incidence, if actions are taken while patients are pre-diabetic, reduce complication related to late diagnosis and indirectly related health-care costs in the country. The need for further campaigns on alcohol consumption and physical activity has emerged, even in rural areas.

Boosting diabetes and pre-diabetes screening in rural Ghana

Background: Diabetes is a growing worldwide disease with serious consequences to health and with a high financial burden. Ghana is one of the developing African countries where the prevalence of diabetes is increasing. Moreover, many cases remain undiagnosed, when along with pre-diabetic cases they can be easily detected. Pre-diabetes condition occurs when blood sugar levels are higher than normal but are not high enough to be classified as diabetes, and it is still reversible. The main objective of this study is to propose a novel method to increase diabetes and pre-diabetes early detection in rural areas. A secondary aim is to look for new related behavioral determinants specific to rural Ghana, by comparing subjects at risk with those already diagnosed as diabetic. Methods: The screening approach was based on tests performed pro-actively by community nurses using glucometers and mobile phone apps. As a pilot for future policies, glycemic tests were carried out on 101 subjects from rural communities in Ghana deemed at risk and unaware of their diabetic/pre-diabetic status. A comparison of dietary and lifestyle habits of the screened people was conducted in regards to a cohort of 103 diabetic patients from the same rural communities. Results: The pilot screening detected 2 diabetic subjects (2% of the cohort) showing WHO diabetic glycemic values, and 20 pre-diabetic subjects (19.8% of the cohort) which showed the effectiveness of the user-friendly approach. The need for further campaigns on alcohol consumption and physical activity has emerged, even in rural areas. Conclusions: Policies based on prevention screening as reported in the manuscript have the potential to reduce diabetes incidence, if actions are taken while patients are pre-diabetic, reduce complication related to late diagnosis and indirectly related health-care costs in the country.

Mobile phone applications for diabetes management: A systematic review

INTRODUCTION

The number of mobile applications (apps) related to health is increasing, and diabetes mellitus (DM) is not an exception. The aim of this study was to assess the free mobile applications for the management of diabetes available, in Spanish, in the Spanish market.

METHODS

GooglePlay (Android) and AppStore (iOS) were reviewed to identify free apps, in Spanish, aimed at people with diabetes. Their main functions and a series of quality and usability features were evaluated and scored. These scores were used to make a top list with the best apps.

RESULTS

Out of 794 registered apps, 42 were evaluated and included in the quality assessment, while 34 apps were included in the usability assessment. The main function of most of the apps was to act as a blood glucose diary (n: 30; 71.43%). As for privacy, most of the applications (33 apps; 78.6%) access device/personal data. Only a minority of apps [3 (7.1%)] reported being based on evidence, and only 3 apps (7.1%) had a quality label. The top scored apps were: OneTouch Reveal™, Social Diabetes™, mySugr: App Diario de diabetes™, Diabetes menú™, Tactio SALUD™ and Diabetes:M™.

CONCLUSIONS

There are few free apps for diabetes management available in Spanish, most lack quality certification and very few provide scientific references about their content. Furthermore, most of the apps access personal/device data.

Effectiveness of smartphone-based self-management interventions on self-efficacy, self-care activities, health-related quality of life and clinical outcomes in patients with type 2 diabetes: A systematic review and meta-analysis

OBJECTIVES

To review the evidence and determine the effectiveness of smartphone-based self-management interventions on self-efficacy, self-care activities, health-related quality of life, glycated hemoglobin, body mass index (BMI), and blood pressure (BP) levels of adults with type 2 diabetes mellitus .

METHODS

A systematic search of five databases (PubMed, Embase, Cochrane, CINAHL and Scopus) was conducted. Studies published in English from January 2007 to January 2018 were considered. Only randomized controlled trials (RCTs) of smartphone-based self-management interventions for patients with type 2 diabetes mellitus that reported any of the study outcomes were included. Two reviewers independently screened the studies, extracted data and assessed the quality of the studies. Meta-analyses were conducted for the different study outcomes.

RESULTS

A total of 26 articles, consisting of 22 studies with 2645 participants, were included in the review. The results from meta-analysis on the studies revealed that as compared to control group, participants received smartphone-based self-management intervention had better self-efficacy with large effect size of 0.98 (P <  0.001), self-care activities with effect size of 0.90 (P <  0.001), health related quality of life with effect size of 0.26 (p=0.01), and lower glycated hemoglobin (pooled MD=-0.55; p<0.001). Subgroup analyses were also conducted for self-efficacy as significant heterogeneity was present among the studies. The effects on BMI and BP were not statistically significant.

CONCLUSIONS

Smartphone-based self-management interventions appear to have beneficial effects on self-efficacy, self-care activities and health-relevant outcomes for patients with type 2 diabetes mellitus. However, more research with good study design is needed to evaluate the effectiveness of smartphone-based self-care interventions for T2DM.

The Efficacy of Mobile Phone Apps for Lifestyle Modification in Diabetes: Systematic Review and Meta-Analysis

Background

Diabetes and related complications are estimated to cost US $727 billion worldwide annually. Type 1 diabetes, type 2 diabetes, and gestational diabetes are three subtypes of diabetes that share the same behavioral risk factors. Efforts in lifestyle modification, such as daily physical activity and healthy diets, can reduce the risk of prediabetes, improve the health levels of people with diabetes, and prevent complications. Lifestyle modification is commonly performed in a face-to-face interaction, which can prove costly. Mobile phone apps provide a more accessible platform for lifestyle modification in diabetes.

Objective

This review aimed to summarize and synthesize the clinical evidence of the efficacy of mobile phone apps for lifestyle modification in different subtypes of diabetes.

Methods

In June 2018, we conducted a literature search in 5 databases (Cochrane Central Register of Controlled Trials, MEDLINE, Embase, CINAHL, and PsycINFO). We evaluated the studies that passed screening using The Cochrane Collaboration’s risk of bias tool. We conducted a meta-analysis for each subtype on the mean difference (between intervention and control groups) at the posttreatment glycated hemoglobin (HbA_1c) level. Where possible, we analyzed subgroups for short-term (3-6 months) and long-term (9-12 months) studies. Heterogeneity was assessed using the I² statistic.

Results

We identified total of 2669 articles through database searching. After the screening, we included 26 articles (23 studies) in the systematic review, of which 18 studies (5 type 1 diabetes, 11 type 2 diabetes, and 2 prediabetes studies) were eligible for meta-analysis. For type 1 diabetes, the overall effect on HbA_1c was statistically insignificant (P=.46) with acceptable heterogeneity (I²=39%) in the short-term subgroup (4 studies) and significant heterogeneity between the short-term and long-term subgroups (I²=64%). Regarding type 2 diabetes, the overall effect on HbA_1c was statistically significant (P<.01) in both subgroups, and when the 2 subgroups were combined, there was virtually no heterogeneity within and between the subgroups (I² range 0%-2%). The effect remained statistically significant (P<.01) after adjusting for publication bias using the trim and fill method. For the prediabetes condition, the overall effect on HbA_1c was statistically insignificant (P=.67) with a large heterogeneity (I²=65%) between the 2 studies.

Conclusions

There is strong evidence for the efficacy of mobile phone apps for lifestyle modification in type 2 diabetes. The evidence is inconclusive for the other diabetes subtypes.

Comparison of three meta-analytic methods using data from digital interventions on type 2 diabetes

AIMS

Pooling the effect sizes of randomized controlled trials (RCTs) from continuous outcomes, such as glycated hemoglobin level (HbA1c), is an important method in evidence syntheses. However, due to challenges related to baseline imbalances and pre/post correlations, simple analysis of change scores (SACS) and simple analysis of final values (SAFV) meta-analyses result in under- or overestimation of effect estimates. This study was aimed to compare pooled effect sizes estimated by Analysis of Covariance (ANCOVA), SACS, and SAFV meta-analyses, using the example of RCTs of digital interventions with HbA1c as the main outcome.

MATERIALS AND METHODS

Three databases were systematically searched for RCTs published from 1993 through June 2017. Two reviewers independently assessed titles and abstracts using predefined eligibility criteria, assessed study quality, and extracted data, with disagreements resolved by arbitration from a third reviewer.

RESULTS

ANCOVA, SACS, and SAFV resulted in pooled HbA1c mean differences of -0.39% (95% CI: [-0.51, -0.26]), -0.39% (95% CI: [-0.51, -0.26]), and -0.34% (95% CI: [-0.48-0.19]), respectively. Removing studies with both high baseline imbalance (≥±0.2%) and pre/post correlation of ≥±0.6 resulted in a mean difference of -0.39% (95% CI: [-0.53, -0.26]), -0.40% (95% CI: [-0.54, -0.26]), and -0.33% (95% CI: [-0.48, -0.18]) with ANCOVA, SACS, and SAFV meta-analyses, respectively. Substantial heterogeneity was noted. Egger's test for funnel plot symmetry did not indicate evidence of publication bias for all methods.

CONCLUSION

By all meta-analytic methods, digital interventions appear effective in reducing HbA1c in type 2 diabetes. The effort to adjust for baseline imbalance and pre/post correlation using ANCOVA relies on the level of detail reported from individual studies. Reporting detailed summary data and, ideally, access to individual patient data of intervention trials are essential.

Effectiveness of Digital Interventions for Improving Glycemic Control in Persons with Poorly Controlled Type 2 Diabetes: A Systematic Review, Meta-analysis, and Meta-regression Analysis

BACKGROUND

Digital interventions may assist patients with type 2 diabetes in improving glycemic control. We aimed to synthesize effect sizes of digital interventions on glycated hemoglobin (HbA1c) levels and to identify effective features of digital interventions targeting patients with poorly controlled type 2 diabetes.

MATERIALS AND METHODS

MEDLINE, ISI Web of Science, and PsycINFO were searched for randomized controlled trials (RCTs) comparing the effects of digital interventions with usual care. Two reviewers independently assessed studies for eligibility and determined study quality, using the Cochrane Risk of Bias Assessment Tool. The Behavioral Change Technique Taxonomy V1 (BCTTv1) was used to identify BCTs used in interventions. Mean HbA1c differences were pooled using analysis of covariance to adjust for baseline differences and pre-post correlations. To examine effective intervention features and to evaluate differences in effect sizes across groups, meta-regression and subgroup analyses were performed.

RESULTS

Twenty-three arms of 21 RCTs were included in the meta-analysis (n = 3787 patients, 52.6% in intervention arms). The mean HbA1c baseline differences ranged from -0.2% to 0.64%. The pooled mean HbA1c change was statistically significant (-0.39 {95% CI: [-0.51 to -0.26]} with substantial heterogeneity [I² statistic, 80.8%]) and a significant HbA1c reduction was noted for web-based interventions. A baseline HbA1c level above 7.5%, β = -0.44 (95% CI: [-0.81 to -0.06]), the BCTs "problem solving," β = -1.30 (95% CI: [-2.05 to -0.54]), and "self-monitoring outcomes of behavior," β = -1.21 (95% CI: [-1.95 to -0.46]) were significantly associated with reduced HbA1c levels.

CONCLUSIONS

Digital interventions appear effective for reducing HbA1c levels in patients with poorly controlled type 2 diabetes.

Effect of Health Information Technologies on Glycemic Control Among Patients with Type 2 Diabetes

PURPOSE OF REVIEW

This study was to present meta-analysis findings across selected clinical trials for the effect of health information technologies (HITs) on glycemic control among patients with type 2 diabetes.

RECENT FINDINGS

HITs may be promising in diabetes management. However, findings on effect size of glycated hemoglobin level (HbA1c) yielded from HITs varied across previous studies. This is likely due to heterogeneity in sample size, adherence to standard quantitative method, and/or searching criteria (e.g., type of HITs, type of diabetes, specification of patient population, randomized vs. nonrandomized trials). We systematically searched Medline, Cumulative Index of Nursing and Allied Health Literature (CINAHL), and the Cochrane Library for peer-reviewed randomized control trials that studied the effect of HITs on HbA1c reduction. We also used Google Scholar and a hand search to identify additional studies. Thirty-four studies (40 estimates) met the criteria and were included in the analysis. Overall, introduction of HITs to standard diabetes treatment resulted in a statistically and clinically reduced HbA1c. The bias adjusted HbA1c reduction due to the combined HIT interventions was - 0.56 [Hedges' g = - 0.56 (- 0.70, - 0.43)]. The reduction was significant across each of the four types of HIT intervention under review, with mobile phone-based approaches generating the largest effects [Hedges' g was - 0.67 (- 0.90, - 0.45)]. HITs can be an effective tool for glycemic control among patients with type 2 diabetes. Future studies should examine long-term effects of HITs and explore factors that influence their effectiveness.

Comparative effectiveness of telemonitoring versus usual care for type 2 diabetes: A systematic review and meta-analysis

AIMS

This study evaluated clinical effectiveness of telemonitoring on the management of patients with type 2 diabetes.

METHODS

We searched Ovid-Medline, Ovid-EMBASE, and the Cochrane Library to identify randomized controlled trials that compared telemonitoring and usual care in patients with type 2 diabetes.

RESULTS

Thirty-eight studies (6855 patients) were included. Telemonitoring was associated with a significant decrease in glycated haemoglobin levels compared to usual care (weighted mean difference -0.42%, 95% confidence interval -0.56 to -0.27) but there was evidence of heterogeneity (I²= 96.9%). Telemonitoring was associated with a significant glycated haemoglobin reduction when biological data were transmitted through a web-based device weekly, when voice feedback was performed daily or immediately and when patients were provided with counselling. Telemonitoring also reduced glycated haemoglobin level in studies that monitored patients' medication adherence, provided counselling, education and alarm message. The rate of achieving glycated haemoglobin levels of < 7% was 1.8 times higher in the telemonitoring group compared to the usual care group (risk ratio 1.83, 95% confidence interval 1.35 to 2.47, I²= 0%). There was also significant reduction in systolic blood pressure (weighted mean difference -1.33 mm Hg) and body mass index (weighted mean difference -0.25 kg/m²), but the clinical relevance of these results can be questioned. The data available on patient satisfaction, quality of life, medication adherence, prescription changes, stress and depression were limited.

CONCLUSIONS

Telemonitoring interventions may be a better option than usual care in improving glycated haemoglobin control of patients with type 2 diabetes. Further studies should assess clinical benefit according to specific delivery modes of the intervention and patient-reported outcomes.

The impact of telehealth remote patient monitoring on glycemic control in type 2 diabetes: a systematic review and meta-analysis of systematic reviews of randomised controlled trials

Background

There is a growing body of evidence to support the use of telehealth in monitoring HbA1c levels in people living with type 2 diabetes. However, the overall magnitude of effect is yet unclear due to variable results reported in existing systematic reviews. The objective of this study is to conduct a systematic review and meta-analysis of systematic reviews of randomised controlled trials to create an evidence-base for the effectiveness of telehealth interventions on glycemic control in adults with type 2 diabetes.

Methods

Electronic databases including The Cochrane Library, MEDLINE, EMBASE, HMIC, and PsychINFO were searched to identify relevant systematic reviews published between 1990 and April 2016, supplemented by references search from the relevant reviews. Two independent reviewers selected and reviewed the eligible studies. Of the 3279 references retrieved, 4 systematic reviews reporting in total 29 unique studies relevant to our review were included. Both conventional pairwise meta-analyses and network meta-analyses were performed.

Results

Evidence from pooling four systematic reviews found that telehealth interventions produced a small but significant improvement in HbA1c levels compared with usual care (MD: -0.55, 95% CI: -0.73 to − 0.36). The greatest effect was seen in telephone-delivered interventions, followed by Internet blood glucose monitoring system interventions and lastly interventions involving automatic transmission of SMBG using a mobile phone or a telehealth unit.

Conclusion

Current evidence suggests that telehealth is effective in controlling HbA1c levels in people living with type 2 diabetes. However there is need for better quality primary studies as well as systematic reviews of RCTs in order to confidently conclude on the impact of telehealth on glycemic control in type 2 diabetes.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3274-8) contains supplementary material, which is available to authorized users.

Digital Diabetes Management Application Improves Glycemic Outcomes in People With Type 1 and Type 2 Diabetes

BACKGROUND

Diabetes is a chronic condition that requires constant self-management. As a consequence, several software platforms have been developed to facilitate the tracking of diabetes data to improve diabetes management. Our aim was to determine the real-world glycemic benefits of a mobile diabetes management platform used by individuals with type 1 and type 2 diabetes.

METHODS

Mobile platform-using (n = 899) and control (n = 900) participants meeting specific minimum data criteria were randomly selected from a database of diabetes users. All results were modeled using different mixed effect generalized linear models, assigning random intercepts for each user, and adjusting the distribution assumption for each outcome.

RESULTS

Users of the mobile platform increased their frequency of blood glucose monitoring (+8.8 tests per month, 95% CI [3.4, 14.1], P < .001) and had fewer hyperglycemic events and lower average glucose levels compared to the control group. In addition, a mobile user could expect a 3.5% drop in average BG (-6.4 mg/dL, 95% CI [-2.0, -10.7], P < .001) and a 10.7% decrease in hyperglycemia ( P < .001) after 2 months.

CONCLUSION

Users of the mobile platform tested their BG more often and demonstrated greater improvement in blood glucose compared to users who did not use the mobile platform. This supports previous studies indicating that digital technologies can enhance diabetes care in a real-world setting.

Improving Glycemic Control in Adults and Children With Type 1 Diabetes With the Use of Smartphone-Based Mobile Applications: A Systematic Review

OBJECTIVES

Management of type 1 diabetes is often challenging. Smartphone mobile applications (apps) may provide additional support and help to improve glycemic control and clinical outcomes. The objectives of this study were to examine the literature evaluating the use of mobile apps (stand-alone and text messaging/feedback) in type 1 diabetes and to review top-rated mobile apps applicable to type 1 diabetes.

METHODS

Medline, Cochrane and Embase databases were systematically searched to identify studies published from inception to February 2018. Top-rated relevant apps from Google Play Store and Apple App Store were reviewed in July 2017.

RESULTS

The literature search yielded 3,462 studies. Of these studies, 9 evaluated the stand-alone apps; 3 showed significant improvement in glycated hemoglobin (A1C) levels (0.5%, p<0.05, 0.57%, p<0.05, and 0.58%, p=0.02); 3 demonstrated improved adherence to glucose monitoring; and 1 study demonstrated a reduction in hypoglycemic events (glucose<3.0 mmol/L) in 6 of 10 participants who completed the study. Also, 5 studies evaluated a mobile app plus text-messaging/feedback system. Only 1 showed a significant reduction in severe hypoglycemic events (mobile app+text, IQR 0.33, 95% CI 0.17 to 0.63; vs. control, IQR 2.29, 95% CI 1.80 to 2.91), while another single study demonstrated a reduction in median glycated hemoglobin levels (0.3%; p<0.001). Most top-rated mobile apps logged parameters relevant to diabetes management, and some provided graphic analysis and set reminders.

CONCLUSIONS

This study highlights the need for larger and longer studies to explore the efficacy of apps to optimize outcomes in type 1 diabetes, the populations that would benefit most from these tools and the resources needed to support mobile apps plus text-messaging/feedback systems.

Human Factors and Data Logging Processes With the Use of Advanced Technology for Adults With Type 1 Diabetes: Systematic Integrative Review

Background

People with type 1 diabetes (T1D) undertake self-management to prevent short and long-term complications. Advanced technology potentially supports such activities but requires consideration of psychological and behavioral constructs and usability issues. Economic factors and health care provider capacity influence access and uptake of advanced technology. Previous reviews have focused upon clinical outcomes or were descriptive or have synthesized studies on adults with those on children and young people where human factors are different.

Objective

This review described and examined the relationship between human factors and adherence with technology for data logging processes in adults with T1D.

Methods

A systematic literature search was undertaken by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Quality appraisal was undertaken and data were abstracted and categorized into the themes that underpinned the human factor constructs that were examined.

Results

A total of 18 studies were included. A total of 6 constructs emerged from the data analysis: the relationship between adherence to data logging and measurable outcomes; satisfaction with the transition to advanced technology for self-management; use of advanced technology and time spent on diabetes-related activities; strategies to mediate the complexities of diabetes and the use of advanced technology; cognition in the wild; and meanings, views, and perspectives from the users of technology.

Conclusions

Increased treatment satisfaction was found on transition from traditional to advanced technology use—insulin pump and continuous glucose monitoring (CGM); the most significant factor was when blood glucose levels were consistently <7.00 mmol/L (P ≤.01). Participants spent considerable time on their diabetes self-care. Logging of data was positively correlated with increasing age when using an app that provided meaningful feedback (regression coefficient=55.8 recordings/year; P ≤.01). There were benefits of CGM for older people in mediating complexities and fears of hypoglycemia with significant differences in well-being (P ≤.001).

Qualitative studies explored the contextual use and uptake of technology. The results suggested frustrations with CGM, continuous subcutaneous insulin infusion, calibration of devices, and alarms. Furthermore implications for “body image” and the way in which “significant others” impacted on the behavior and attitude of the individual toward technology use. There were wide variations in the normal use of and interaction with technology across a continuum of sociocultural contexts, which has implications for the way in which future technologies should be designed.

Quantitative studies were limited by small sample sizes, making it difficult to generalize findings to other contexts. This was further limited by a sample that was predominantly white, well-controlled, and engaged with self-care. The use of critical appraisal frameworks demonstrated where research into human factors and data logging processes of individuals could be improved. This included engaging people in the design of the technology, especially hard-to-reach or marginalized groups.

Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis

BACKGROUND

Successful treatment of diabetes includes patient self-management behaviors to prevent or delay complications and comorbid diseases. On the basis of findings from large clinical trials and professional guidelines, diabetes education programs and health providers prescribe daily regimens of glucose monitoring, healthy eating, stress management, medication adherence, and physical activity. Consistent, long-term commitment to regimens is challenging. Mobile health is increasingly being used to assist patients with lifestyle changes and self-management behaviors between provider visits. The effectiveness of mobile health to improve diabetes outcomes depends on patient engagement with a technology, content, or interactions with providers.

OBJECTIVES

In the current analysis, we aimed to identify patient engagement themes in diabetes messaging with diabetes providers and determine if differences in engagement in the Mobile Diabetes Intervention Study (MDIS) influenced changes in glycated hemoglobin A1c (HbA1c) over a 1-year treatment period (1.9% absolute decrease in the parent study).

METHODS

In the primary MDIS study, 163 patients were enrolled into 1 of 3 mobile intervention groups or a usual care control group based on their physician cluster randomization assignment. The control group received care from their physicians as usual. Participants in each intervention group had access to a patient portal where they could record monitoring values for blood glucose, blood pressure, medication changes, or other self-management information while also assigned to varying levels of physician access to patient data. Intervention participants could choose to send and receive messages to assigned certified diabetes educators with questions or updates through the secure Web portal. For this secondary analysis, patient engagement was measured using qualitative methods to identify self-care themes in 4109 patient messages. Mixed methods were used to determine the impact of patient engagement on change in HbA1c over 1 year.

RESULTS

Self-care behavior themes that received the highest engagement for participants were glucose monitoring (75/107, 70.1%), medication management (71/107, 66.4%), and reducing risks (71/107, 66.4%). The average number of messages sent per patient were highest for glucose monitoring (9.2, SD 14.0) and healthy eating (6.9, SD 13.2). Compared to sending no messages, sending any messages about glucose monitoring (P=.03) or medication (P=.01) led to a decrease in HbA1c of 0.62 and 0.72 percentage points, respectively. Sending any messages about healthy eating, glucose monitoring, or medication combined led to a decrease in HbA1c of 0.54 percentage points compared to not sending messages in these themes (P=.045).

CONCLUSIONS

The findings from this study help validate the efficacy of the mobile diabetes intervention. The next step is to determine differences between patients who engage in mobile interventions and those who do not engage and identify methods to enhance patient engagement.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT01107015; https://clinicaltrials.gov/ct2/show/NCT01107015 (Archived by WebCite at http://www.webcitation.org/6wh4ekP4R).

The Impact of mHealth Interventions: Systematic Review of Systematic Reviews

Background

Mobile phone usage has been rapidly increasing worldwide. mHealth could efficiently deliver high-quality health care, but the evidence supporting its current effectiveness is still mixed.

Objective

We performed a systematic review of systematic reviews to assess the impact or effectiveness of mobile health (mHealth) interventions in different health conditions and in the processes of health care service delivery.

Methods

We used a common search strategy of five major scientific databases, restricting the search by publication date, language, and parameters in methodology and content. Methodological quality was evaluated using the Measurement Tool to Assess Systematic Reviews (AMSTAR) checklist.

Results

The searches resulted in a total of 10,689 articles. Of these, 23 systematic reviews (371 studies; more than 79,665 patients) were included. Seventeen reviews included studies performed in low- and middle-income countries. The studies used diverse mHealth interventions, most frequently text messaging (short message service, SMS) applied to different purposes (reminder, alert, education, motivation, prevention). Ten reviews were rated as low quality (AMSTAR score 0-4), seven were rated as moderate quality (AMSTAR score 5-8), and six were categorized as high quality (AMSTAR score 9-11). A beneficial impact of mHealth was observed in chronic disease management, showing improvement in symptoms and peak flow variability in asthma patients, reducing hospitalizations and improving forced expiratory volume in 1 second; improving chronic pulmonary diseases symptoms; improving heart failure symptoms, reducing deaths and hospitalization; improving glycemic control in diabetes patients; improving blood pressure in hypertensive patients; and reducing weight in overweight and obese patients. Studies also showed a positive impact of SMS reminders in improving attendance rates, with a similar impact to phone call reminders at reduced cost, and improved adherence to tuberculosis and human immunodeficiency virus therapy in some scenarios, with evidence of decrease of viral load.

Conclusions

Although mHealth is growing in popularity, the evidence for efficacy is still limited. In general, the methodological quality of the studies included in the systematic reviews is low. For some fields, its impact is not evident, the results are mixed, or no long-term studies exist. Exceptions include the moderate quality evidence of improvement in asthma patients, attendance rates, and increased smoking abstinence rates. Most studies were performed in high-income countries, implying that mHealth is still at an early stage of development in low-income countries.

Characterizing Active Ingredients of eHealth Interventions Targeting Persons With Poorly Controlled Type 2 Diabetes Mellitus Using the Behavior Change Techniques Taxonomy: Scoping Review

BACKGROUND

The behavior change technique taxonomy v1 (BCTTv1; Michie and colleagues, 2013) is a comprehensive tool to characterize active ingredients of interventions and includes 93 labels that are hierarchically clustered into 16 hierarchical clusters.

OBJECTIVE

The aim of this study was to identify the active ingredients in electronic health (eHealth) interventions targeting patients with poorly controlled type 2 diabetes mellitus (T2DM) and relevant outcomes.

METHODS

We conducted a scoping review using the BCTTv1. Randomized controlled trials (RCTs), studies with or pre-post-test designs, and quasi-experimental studies examining efficacy and effectiveness of eHealth interventions for disease management or the promotion of relevant health behaviors were identified by searching PubMed, Web of Science, and PsycINFO. Reviewers independently screened titles and abstracts for eligibility using predetermined eligibility criteria. Data were extracted following a data extraction sheet. The BCTTv1 was used to characterize active ingredients of the interventions reported in the included studies.

RESULTS

Of the 1404 unique records screened, 32 studies fulfilled the inclusion criteria and reported results on the efficacy and or or effectiveness of interventions. Of the included 32 studies, 18 (56%) were Web-based interventions delivered via personal digital assistant (PDA), tablet, computer, and/or mobile phones; 7 (22%) were telehealth interventions delivered via landline; 6 (19%) made use of text messaging (short service message, SMS); and 1 employed videoconferencing (3%). Of the 16 hierarchical clusters of the BCTTv1, 11 were identified in interventions included in this review. Of the 93 individual behavior change techniques (BCTs), 31 were identified as active ingredients of the interventions. The most common BCTs identified were instruction on how to perform behavior, adding objects to the environment, information about health consequences, self-monitoring of the outcomes and/or and prefers to be explicit to avoid ambiguity. Response: Checked and avoided of a certain behavior Author: Please note that the journal discourages the use of parenthesis to denote either and/or and prefers to be explicit to avoid ambiguity. Response: Checked and avoided "and/or" and prefers to be explicit to avoid ambiguity. Response: Checked and avoided, and feedback on outcomes of behavior.

CONCLUSIONS

Our results suggest that the majority of BCTs employed in interventions targeting persons with T2DM revolve around the promotion of self-regulatory behavior to manage the disease or to assist patients in performing health behaviors necessary to prevent further complications of the disease. Detailed reporting of the BCTs included in interventions targeting this population may facilitate the replication and further investigation of such interventions.

Usability and clinical efficacy of diabetes mobile applications for adults with type 2 diabetes: A systematic review

OBJECTIVES

To assess the usability and clinical effectiveness of diabetes mobile applications (diabetes apps) developed for adults with type 2 diabetes.

METHOD

A systematic review of the usability and effectiveness of diabetes apps was conducted. Searches were performed using MEDLINE, EMBASE, COMPENDEX, and IEEE XPLORE for articles published from January 1, 2011, to January 17, 2017. Search terms included: diabetes, mobile apps, and mobile health (mHealth).

RESULTS

The search yielded 723 abstracts of which seven usability studies and ten clinical effectiveness studies met the inclusion criteria from 20 publications. Usability, as measured by satisfaction ratings from experts and patients, ranged from 38% to 80%. Usability problem ratings ranged from moderate to catastrophic. Top usability problems are multi-steps task, limited functionality and interaction, and difficult system navigation. Clinical effectiveness, measured by reductions in HbA1c, ranged from 0.15% to 1.9%.

CONCLUSION

Despite meager satisfaction ratings and major usability problems, there is some limited evidence supporting the effectiveness of diabetes apps to improve glycemic control for adults with type 2 diabetes. Findings strongly suggest that efforts to improve user satisfaction, incorporate established principles of health behavior change, and match apps to user characteristics will increase the therapeutic impact of diabetes apps.

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.