On the efficacy of behavior change techniques in mHealth for self-management of diabetes: A meta-analysis

Mobile apps for diabetes self-management: An updated review of app features and effectiveness

Self-management of diabetes is extremely challenging and non-adherence is common. Health consequences are significant for those unable to adhere to the complex treatment regimen, which includes regular oral medication and/or insulin use, frequent blood sugar checks, strict dietary management, and regular physical activity. Mobile applications (apps) present a tremendous opportunity to help patients improve adherence to these behaviors. The availability of commercial diabetes self-management apps is increasing exponentially, making it difficult for patients and providers to stay informed about app options and benefits. Previous reviews have described commercial diabetes apps and their features and usability for patients with diabetes. A smaller number have reviewed the effectiveness of these apps in improving blood glucose as well as other aspects of diabetes management. The aim of this article is to update our 2016 review, summarize the results of new reviews, review outcomes of diabetes apps described in the literature, and offer recommendations for app features, effectiveness research, and marketing in apps for diabetes self-management. Although higher-quality research is needed, current reviews suggest that many diabetes apps are effective in lowering HbA1c. Recommendations for future research include reporting critical details such as patient demographics and intervention elements and designing studies to identify the most effective components of diabetes management apps. Furthermore, clearly labeling apps that have data supporting clinical efficacy in app stores would allow both providers and patients to easily identify apps that might be most beneficial. Future research should explore the use of apps for the prevention of diabetes in individuals diagnosed with prediabetes.

Mobile phone interventions to improve health outcomes among patients with chronic diseases: an umbrella review and evidence synthesis from 34 meta-analyses

This umbrella review of 34 meta-analyses, representing 235 randomised controlled trials done across 52 countries and 48 957 participants and ten chronic conditions, aimed to evaluate evidence on the efficacy of mobile phone interventions for populations with chronic diseases. We evaluated the strengths of evidence via the Fusar-Poli and Radua methodology. Compared with usual care, mobile apps had convincing effects on glycated haemoglobin reduction among adults with type 2 diabetes (d=0·44). Highly suggestive effects were found for both text messages and apps on various outcomes, including medication adherence (among patients with HIV in sub-Saharan Africa and people with cardiovascular disease), glucose management in type 2 diabetes, and blood pressure reduction in hypertension. Many effects (42%) were non-significant. Various gaps were identified, such as a scarcity of reporting on moderators and publication bias by meta-analyses, little research in low-income and lower-middle-income countries, and little reporting on adverse events.

Behavior Change Techniques Used in Self-Management Interventions Based on mHealth Apps for Adults With Hypertension: Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Hypertension has become an important global public health challenge. Mobile health (mHealth) intervention is a viable strategy to improve outcomes for patients with hypertension. However, evidence on the effect of mHealth app interventions on self-management in patients with hypertension is yet to be updated, and the active ingredients promoting behavior change in interventions remain unclear.

OBJECTIVE

We aimed to evaluate the effect of mHealth app self-management interventions on blood pressure (BP) management and investigate the use of behavior change techniques (BCTs) in mHealth app interventions.

METHODS

We conducted a literature search in 6 electronic databases from January 2009 to October 2023 for studies reporting the application of mHealth apps in self-management interventions. The Cochrane Risk of Bias (version 2) tool for randomized controlled trials was used to assess the quality of the studies. BCTs were coded according to the Taxonomy of BCTs (version 1). The extracted data were analyzed using RevMan5.4 software (Cochrane Collaboration).

RESULTS

We reviewed 20 studies, of which 16 were included in the meta-analysis. In total, 21 different BCTs (mean 8.7, SD 3.8 BCTs) from 12 BCT categories were reported in mHealth app interventions. The most common BCTs were self-monitoring of outcomes of behavior, feedback on outcomes of behavior, instruction on how to perform the behavior, and pharmacological support. The mHealth app interventions resulted in a -5.78 mm Hg (95% CI -7.97 mm Hg to -3.59 mm Hg; P<.001) reduction in systolic BP and a -3.28 mm Hg (95% CI -4.39 mm Hg to -2.17 mm Hg; P<.001) reduction in diastolic BP. The effect of interventions on BP reduction was associated with risk factors, such as hypertension, that were addressed by the mHealth app intervention (multiple risk factors vs a single risk factor: -6.50 mm Hg, 95% CI -9.00 mm Hg to -3.99 mm Hg vs -1.54 mm Hg, 95% CI -4.15 mm Hg to 1.06 mm Hg; P=.007); the presence of a theoretical foundation (with vs without behavior change theory: -10.06 mm Hg, 95% CI -16.42 mm Hg to -3.70 mm Hg vs -4.13 mm Hg, 95% CI -5.50 to -2.75 mm Hg; P=.07); intervention duration (3 vs ≥6 months: -8.87 mm Hg, 95% CI -10.90 mm Hg to -6.83 mm Hg vs -5.76 mm Hg, 95% CI -8.74 mm Hg to -2.77 mm Hg; P=.09); and the number of BCTs (≥11 vs <11 BCTs: -9.68 mm Hg, 95% CI -13.49 mm Hg to -5.87 mm Hg vs -2.88 mm Hg, 95% CI -3.90 mm Hg to -1.86 mm Hg; P<.001).

CONCLUSIONS

The self-management interventions based on mHealth apps were effective strategies for lowering BP in patients with hypertension. The effect of interventions was influenced by factors related to the study's intervention design and BCT.

Improving the management of type 2 diabetes in China using a multifaceted digital health intervention in primary health care: the SMARTDiabetes cluster randomised controlled trial

Background

There is limited evidence, mainly from high-income countries, that digital health interventions improve type 2 diabetes (T2DM) care. Large-scale implementation studies are lacking.

Methods

A multifaceted digital health intervention comprising: (1) a self-management application ('app') for patients and lay 'family health promotors' (FHPs); and (2) clinical decision support for primary care doctors was evaluated in an open-label, parallel, cluster randomized controlled trial in 80 communities (serviced by a primary care facility for >1000 residents) in Hebei Province, China. People >40 years with T2DM and a glycated haemoglobin (HbA1c) ≥7% were recruited (∼25/community). After baseline assessment, community clusters were randomly assigned to intervention or control groups (1:1) via a web-based system, stratified by locality (rural/urban). Control arm clusters received usual care without access to the digital health application or family health promoters. The primary outcome was at the participant level defined as the proportion with ≥2 "ABC" risk factor targets achieved (HbA1c < 7.0%, blood pressure < 140/80 mmHg and LDL-cholesterol < 2.6 mmol/L) at 24 months.

Findings

A total of 2072 people were recruited from the 80 community clusters (40 urban and 40 rural), with 1872 (90.3%) assessed at 24 months. In the intervention arm, patients used FHPs for support more in rural than urban communities (252 (48.6%) rural vs 92 (21.5%) urban, p < 0.0001). The mean monthly proportion of active app users was 46.4% (SD 7.8%) with no significant difference between urban and rural usage rates. The intervention was associated with improved ABC control rates (339 [35.9%] intervention vs 276 [29.9%] usual care; RR 1.20, 95% CI 1.02-1.40; p = 0.025), with significant heterogeneity by geography (rural 220 [42.6%] vs 158 [31.0%]; urban 119 [27.9%] vs 118 [28.6%]; p = 0.022 for interaction). Risk factor reductions were mainly driven by improved glycaemic control (mean HbA1C difference -0.33%, 95% CI -0.48 to -0.17; p = 0.00025 and mean fasting plasma glucose difference -0.58 mmol, 95% CI -0.89 to -0.27; p = 0.00013). There were no changes in blood pressure and LDL-cholesterol levels.

Interpretation

A multifaceted digital health intervention improved T2DM risk factor control rates, particularly in rural communities where there may be stronger relationships between patients and doctors and greater family member support.

Funding

National Health and Medical Research CouncilGlobal Alliance for Chronic Diseases (ID 1094712).

Serial mediation roles of empowerment and self-care activities connecting health literacy, quality of life, and glycemic control in people with type 2 diabetes

BACKGROUND

Health literacy, empowerment, and self-care activities are likely the crucial concepts affecting the quality of life and glycemic control in people with type 2 diabetes (T2D). However, evidence demonstrating the mechanisms underlying these concepts is scarce.

AIMS

The aim of this study was to test the serial mediation roles of empowerment and self-care activities on the relationships between health literacy and quality of life and between health literacy and hemoglobin A1c (HbA1c) in people with T2D.

METHODS

A cross-sectional study was conducted among 319 people with T2D in Guangzhou, China, from July 2019 to January 2020. Data were collected using the Health Literacy Scale, the Diabetes Empowerment Scale-Short Form, the Summary of Diabetes Self-Care Activities Measure, and the Adjusted Diabetes-Specific Quality of Life Scale. RStudio 4.2.1 was used for serial mediation analysis.

RESULTS

The dimension of communicative health literacy accounted for the most total variance (β = 0.810, p < .001) in the construct of health literacy. The serial multiple mediation of empowerment and self-care activities in the associations between health literacy and quality of life (β = -.046, p = .019) and between health literacy and HbA1c (β = -.045, p = .005) were statistically significant.

LINKING EVIDENCE TO ACTION

This study emphasized the vital role of communicative health literacy when improving health literacy in people with T2D. Diabetes care and education specialists could implement empowerment approaches and flexible self-care strategies to improve the quality of life and glycemic control in people with T2D. Enhancing health literacy was suggested as a favorable strategy for promoting empowerment and self-care activities in people with T2D.

Effects of web-based diabetes education on knowledge retention in adult general population: An experiment

OBJECTIVE

To conduct a study to improve diabetes knowledge through a web-based diabetes course in the general adult population. We hypothesised that participation in a web-based diabetes course would have a positive impact on diabetes knowledge retention.

METHODS

Participants were randomly assigned to an experimental or control group. Participants in the experimental group attended an interactive web-based diabetes course. The Diabetes Knowledge Questionnaire (DKQ24) was used to assess the diabetes knowledge levels. The DKQ24 was completed at the beginning and end of the observation period of 3 months. The experimental group also completed it immediately after the intervention.

RESULTS

At the end of the observation period, a statistically significant difference in the mean rank of DKQ24 scores was found in favor of the experimental group (p < .001). The results of the experimental group had a lower interquartile range (IQR = 3) than those of the control group (IQR = 5).

CONCLUSIONS

This study suggests that providing a web-based diabetes course to the general population is effective and can improve diabetes knowledge and retention.

Which behaviour change techniques work best for diabetes self-management mobile apps? Results from a systematic review and meta-analysis of randomised controlled trials

BACKGROUND

Self-management is pivotal in addressing noncommunicable diseases, such as diabetes. The increased availability of digital behaviour change interventions (DBCIs) delivered through mobile health apps offers unprecedented opportunities to enhance self-management and improve health outcomes. However, little is known about the characteristics of DBCIs for diabetes that significantly impact glycaemic control. Therefore, our systematic review with meta-analysis aimed to summarize characteristics and behaviour change components in DBCIs for diabetes self-management and explore potential associations with metabolic outcomes.

METHODS

A systematic search was conducted in PubMed, Embase, the Cochrane Central Register of Controlled Trials, and Scopus to identify randomized controlled trials published until November 2023. The main outcome variable was the change in the mean difference of HbA1c levels between baseline and follow-up across intervention and control groups. Random-effects meta-regression was used to explore variation in glycaemic control as a function of prespecified characteristics of study designs and app interventions.

FINDINGS

A total of 57 studies was included in the analysis, showing a statistically significant percentage point reduction in HbA1c for the intervention group compared to the control arm (-0.36, 95% CI = -0.46 to -0.26, p < 0.001). The inclusion of "self-monitoring of behaviour" as a behaviour change technique (β = -0.22, p = 0.04) and "taking medication" as a target behaviour (β = -0.20, p = 0.05) was associated with improved metabolic outcomes.

INTERPRETATION

Our analyses endorse the use of diabetes self-management apps, highlighting characteristics statistically associated with intervention effectiveness and guiding the design of more effective DBCIs.

FUNDING

This project received funding from the European Union's Horizon 2020 programme.

An umbrella review of effectiveness and efficacy trials for app-based health interventions

Health interventions based on mobile phone or tablet applications (apps) are promising tools to help patients manage their conditions more effectively. Evidence from randomized controlled trials (RCTs) on efficacy and effectiveness of such interventions is increasingly available. This umbrella review aimed at mapping and narratively summarizing published systematic reviews on efficacy and effectiveness of mobile app-based health interventions within patient populations. We followed a pre-specified publicly available protocol. Systematic reviews were searched in two databases from inception until August 28, 2023. Reviews that included RCTs evaluating integrated or stand-alone health app interventions in patient populations with regard to efficacy/effectiveness were considered eligible. Information on indications, outcomes, app characteristics, efficacy/effectiveness results and authors' conclusions was extracted. Methodological quality was assessed using the AMSTAR2 tool. We identified 48 systematic reviews published between 2013 and 2023 (35 with meta-analyses) that met our inclusion criteria. Eleven reviews included a broad spectrum of conditions, thirteen focused on diabetes, five on anxiety and/or depression, and others on various other indications. Reported outcomes ranged from medication adherence to laboratory, anthropometric and functional parameters, symptom scores and quality of life. Fourty-one reviews concluded that health apps may be effective in improving health outcomes. We rated one review as moderate quality. Here we report that the synthesized evidence on health app effectiveness varies largely between indications. Future RCTs should consider reporting behavioral (process) outcomes and measures of healthcare resource utilization to provide deeper insights on mechanisms that make health apps effective, and further elucidate their impact on healthcare systems.

Effectiveness of mobile health interventions for pregnant women with gestational diabetes mellitus: a systematic review and meta-analysis

Gestational diabetes mellitus is a growing global health problem. Inadequate management during pregnancy can lead to maternal and foetal complications. Currently, mobile health (mHealth) delivers healthcare services, playing an increasingly important role in the management of blood glucose in GDM. This study aimed to systematically evaluate the effectiveness of mHealth intervention in pregnant women with GDM. Based on randomised controlled trials of mHealth application in GDM patients searched from the database, literature screening, data extraction, and quality evaluation were conducted independently by two researchers. Statistical analysis was performed using Review Manager 5.4 software. The review included 27 studies with a total of 3483 patients. The results showed a significant improvement in glycemic control. In addition, mHealth interventions could reduce the occurrence of adverse pregnancy outcomes and improve self-management ability. In a subgroup analysis, recording of delivery mode and WeChat combined phone call indicated significant differences with mHealth interventions. It was suggested that mHealth interventions imposed a positive effect on glycemic control and reduction of adverse pregnancy outcomes in GDM patients. Our results demonstrated that the application of mHealth interventions can act as an effective and feasible approach to self-management to promote the self-management level and awareness of GDM patients.

A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring

The complex relationships between continuously monitored health signals and therapeutic regimens can be modelled via machine learning. However, the clinical implementation of the models will require changes to clinical workflows. Here we outline ClinAIOps ('clinical artificial-intelligence operations'), a framework that integrates continuous therapeutic monitoring and the development of artificial intelligence (AI) for clinical care. ClinAIOps leverages three feedback loops to enable the patient to make treatment adjustments using AI outputs, the clinician to oversee patient progress with AI assistance, and the AI developer to receive continuous feedback from both the patient and the clinician. We lay out the central challenges and opportunities in the deployment of ClinAIOps by means of examples of its application in the management of blood pressure, diabetes and Parkinson's disease. By enabling more frequent and accurate measurements of a patient's health and more timely adjustments to their treatment, ClinAIOps may substantially improve patient outcomes.

Effective Behavior Change Techniques in Digital Health Interventions for the Prevention or Management of Noncommunicable Diseases: An Umbrella Review

BACKGROUND

Despite an abundance of digital health interventions (DHIs) targeting the prevention and management of noncommunicable diseases (NCDs), it is unclear what specific components make a DHI effective.

PURPOSE

This narrative umbrella review aimed to identify the most effective behavior change techniques (BCTs) in DHIs that address the prevention or management of NCDs.

METHODS

Five electronic databases were searched for articles published in English between January 2007 and December 2022. Studies were included if they were systematic reviews or meta-analyses of DHIs targeting the modification of one or more NCD-related risk factors in adults. BCTs were coded using the Behavior Change Technique Taxonomy v1. Study quality was assessed using AMSTAR 2.

RESULTS

Eighty-five articles, spanning 12 health domains and comprising over 865,000 individual participants, were included in the review. We found evidence that DHIs are effective in improving health outcomes for patients with cardiovascular disease, cancer, type 2 diabetes, and asthma, and health-related behaviors including physical activity, sedentary behavior, diet, weight management, medication adherence, and abstinence from substance use. There was strong evidence to suggest that credible source, social support, prompts and cues, graded tasks, goals and planning, feedback and monitoring, human coaching and personalization components increase the effectiveness of DHIs targeting the prevention and management of NCDs.

CONCLUSIONS

This review identifies the most common and effective BCTs used in DHIs, which warrant prioritization for integration into future interventions. These findings are critical for the future development and upscaling of DHIs and should inform best practice guidelines.

Use of Behavior Change Techniques and Quality of Commercially Available Inflammatory Bowel Disease Apps

BACKGROUND

Inclusion of evidence-based behavior change techniques (e.g., self-monitoring) in mobile health apps has the potential to promote adherence to inflammatory bowel disease treatment. While inflammatory bowel disease management apps exist, the extent to which they incorporate behavior change techniques remains unknown.

AIMS

The present study systematically evaluated the content and quality of free, commercially available inflammatory bowel disease management apps.

METHODS

Apps were identified using a systematic search of the Apple App and Google Play stores. Apps were evaluated using Abraham and Michie's taxonomy of 26 behavior change techniques. A literature search was conducted to identify behavior change techniques specific and relevant for people with inflammatory bowel disease. App quality was assessed using the Mobile App Rating Scale with scores ranging from 1 (Inadequate) to 5 (Excellent).

RESULTS

A total of 51 inflammatory bowel disease management apps were evaluated. Apps included 0-16 behavior change techniques (Mean = 4.55) and 0-10 inflammatory bowel disease management behavior change techniques (Mean = 3.43). App quality ranged from 2.03 to 4.62 (Mean = 3.39) out of 5.00. Two apps, My IBD Care: Crohn's & Colitis and MyGiHealth GI Symptom Tracker, included the highest number of overall and inflammatory bowel disease management behavior change techniques along with high-quality scores. Bezzy IBD was the only app with a high number of overall and inflammatory bowel disease management behavior change techniques with a primary focus on social support/change.

CONCLUSION

Most inflammatory bowel disease management apps reviewed included evidence-based inflammatory bowel disease management behavior change techniques.

Digital Behavior Change Interventions to Reduce Sedentary Behavior and Promote Physical Activity in Adults with Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Technological advancements and ease of Internet access have increased the number of digital behavior change interventions (DBCIs). This systematic review and meta-analysis aimed to assess the effectiveness of DBCIs in reducing sedentary behavior (SB) and promoting physical activity (PA) in adults with diabetes.

METHODS

A comprehensive search of seven databases-PubMed, Embase, PsycINFO, Cochrane Library, CINAHL, Web of Science, and Sedentary Behavior Research Database-was performed. Two reviewers independently carried out the study selection, data extraction, risk of bias assessment, and quality of evidence evaluation. Meta-analyses were performed where feasible; otherwise, narrative summaries were performed.

RESULTS

A total of 13 randomized controlled trials with 980 participants met the inclusion criteria. Overall, DBCIs could significantly increase steps and the number of breaks in sedentary time. The subgroup analyses exhibited significant effects in DBCIs with over 10 behavior change techniques (BCTs) in improving steps, the time spent in light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). The subgroup analyses showed a significant step increment in DBCIs of moderate and long durations, with over 4 BCT clusters, or in conjunction with a face-to-face component. The subgroup analyses also indicated significant effects in studies with ≥ 2 DBCI components in improving steps, the time spent in LPA and MVPA, and reducing sedentary time.

CONCLUSION

There is some evidence that DBCI may increase PA and reduce SB in adults with type 2 diabetes. However, more high-quality studies are required. Future studies are needed to examine the potential of DBCIs in adults with type 1 diabetes.

Effects of E-health-based interventions on glycemic control for patients with type 2 diabetes: a Bayesian network meta-analysis

The high disease burden of type 2 diabetes seriously affects the quality of life of patients, and with the deep integration of the Internet and healthcare, the application of electronic tools and information technology to has become a trend for disease management. The aim of this study was to evaluate the effectiveness of different forms and durations of E-health interventions in achieving glycemic control in type 2 diabetes patients. PubMed, Embase, Cochrane, and Clinical Trials.gov were searched for randomized controlled trials reporting different forms of E-health intervention for glycemic control in type 2 diabetes patients, including comprehensive measures (CM), smartphone applications (SA), phone calls (PC), short message service (SMS), websites (W), wearable devices (WD), and usual care. The inclusion criteria were as follows: (1) adults (age≥18) with type 2 diabetes mellitus; (2) intervention period ≥1 month; (3) outcome HbA1c (%); and (4) randomized control of E-health based approaches. Cochrane tools were used to assess the risk of bias. R 4.1.2 was used to conduct the Bayesian network meta-analysis. A total of 88 studies with 13,972 type 2 diabetes patients were included. Compared to the usual care group, the SMS-based intervention was superior in reducing HbA1c levels (mean difference (MD)-0.56, 95% confidence interval (CI): -0.82 to -0.31), followed by SA (MD-0.45, 95% CI: -0.61 to -0.30), CM (MD-0.41, 95% CI: -0.57 to -0.25), W (MD-0.39, 95% CI: -0.60 to -0.18) and PC (MD-0.32, 95% CI: -0.50 to -0.14) (p < 0.05). Subgroup analysis revealed that intervention durations of ≤6 months were most effective. All type of E-health based approaches can improve glycemic control in patients with type 2 diabetes. SMS is a high-frequency, low-barrier technology that achieves the best effect in lowering HbA1c, with ≤6 months being the optimal intervention duration.

Systematic review registration

https://www.crd.york.ac.uk/prospero, identifier CRD42022299896.

Personal Goals, Barriers to Self-Management and Desired mHealth Application Features to Improve Self-Care in Multi-Ethnic Asian Patients with Type 2 Diabetes: A Qualitative Study

(1) Introduction: The ubiquity of mobile phones suggests the potential of mobile health applications to reach patients with type 2 diabetes and engage them to improve self-care. This study aimed to explore personal goals, barriers to self-management and desired mobile health application features to improve self-care among multi-ethnic Asian patients with type 2 diabetes. (2) Methods: We conducted semi-structured interviews with patients with type 2 diabetes (n = 29). Patients were recruited from a multi-disciplinary center for diabetes and metabolism in Singapore, using a purposive sampling strategy. Various visual materials, collated from existing mobile health application features, were used to facilitate the discussion. Interviews were transcribed verbatim and thematically analyzed. (3) Results: A total of 29 patients participated in 11 focus group discussions or one-on-one interviews. Personal goals for self-management were centered around short-term outcome expectancy, such as better glucose control and a reduced number of medications. Self-management was hampered by competing priorities and limited healthy food options when at work, while a lack of tailored advice from healthcare providers further diminished competence. The desired mobile health app features to improve self-care behaviors included quantifiable goal-setting, personalized nudges based on tracked data, built-in resources from credible sources, in-app social support through virtual interaction with peers and healthcare providers, technology-driven novel data logging and user-defined nudges. (4) Conclusions: We identified a set of app features that may foster motivation to engage in lifestyle modification for patients with T2DM. The findings serve to inform the design of artificial intelligence-enabled mobile health application intervention aimed at improving diabetes self-care.