A Mobile App to Improve Self-Management of Individuals With Type 2 Diabetes: Qualitative Realist Evaluation

User Engagement With mHealth Interventions to Promote Treatment Adherence and Self-Management in People With Chronic Health Conditions: Systematic Review

BACKGROUND

There are numerous mobile health (mHealth) interventions for treatment adherence and self-management; yet, little is known about user engagement or interaction with these technologies.

OBJECTIVE

This systematic review aimed to answer the following questions: (1) How is user engagement defined and measured in studies of mHealth interventions to promote adherence to prescribed medical or health regimens or self-management among people living with a health condition? (2) To what degree are patients engaging with these mHealth interventions? (3) What is the association between user engagement with mHealth interventions and adherence or self-management outcomes? (4) How often is user engagement a research end point?

METHODS

Scientific database (Ovid MEDLINE, Embase, Web of Science, PsycINFO, and CINAHL) search results (2016-2021) were screened for inclusion and exclusion criteria. Data were extracted in a standardized electronic form. No risk-of-bias assessment was conducted because this review aimed to characterize user engagement measurement rather than certainty in primary study results. The results were synthesized descriptively and thematically.

RESULTS

A total of 292 studies were included for data extraction. The median number of participants per study was 77 (IQR 34-164). Most of the mHealth interventions were evaluated in nonrandomized studies (157/292, 53.8%), involved people with diabetes (51/292, 17.5%), targeted medication adherence (98/292, 33.6%), and comprised apps (220/292, 75.3%). The principal findings were as follows: (1) >60 unique terms were used to define user engagement; "use" (102/292, 34.9%) and "engagement" (94/292, 32.2%) were the most common; (2) a total of 11 distinct user engagement measurement approaches were identified; the use of objective user log-in data from an app or web portal (160/292, 54.8%) was the most common; (3) although engagement was inconsistently evaluated, most of the studies (99/195, 50.8%) reported >1 level of engagement due to the use of multiple measurement methods or analyses, decreased engagement across time (76/99, 77%), and results and conclusions suggesting that higher engagement was associated with positive adherence or self-management (60/103, 58.3%); and (4) user engagement was a research end point in only 19.2% (56/292) of the studies.

CONCLUSIONS

The results revealed major limitations in the literature reviewed, including significant variability in how user engagement is defined, a tendency to rely on user log-in data over other measurements, and critical gaps in how user engagement is evaluated (infrequently evaluated over time or in relation to adherence or self-management outcomes and rarely considered a research end point). Recommendations are outlined in response to our findings with the goal of improving research rigor in this area.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022289693; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022289693.

Perspectives and Needs of Malaysian Patients With Diabetes for a Mobile Health App Support on Self-Management of Diabetes: Qualitative Study

BACKGROUND

Effective self-management of diabetes is crucial for improving clinical outcomes by maintaining glucose levels and preventing the exacerbation of the condition. Mobile health (mHealth) has demonstrated its significance in enhancing self-management practices. However, only 20% of Malaysians are familiar with mHealth technologies and use them for health management.

OBJECTIVE

This study aims to explore the perceived benefits and challenges, needs and preferences, and willingness of patients with diabetes to use mHealth apps for self-management of diabetes.

METHODS

The study involved one-on-one semistructured online interviews with a total of 15 participants, all of whom were aged 18 years or older and had been diagnosed with diabetes for more than 6 months. An interview guide was developed based on the constructs of the Technology Acceptance Model (TAM), the Health Information Technology Acceptance Model (HITAM), and the aesthetics factor derived from the Mobile Application Rating Scale. All interviews were recorded in audio format and transcribed verbatim. The interview content was then organized and coded using ATLAS.ti version 8. Thematic analysis was conducted in accordance with the recommended guidelines for analyzing the data.

RESULTS

From the interviews with participants, 3 key themes emerged regarding the perceived benefits of using mHealth app support in diabetes self-management. These themes were the ability to track and monitor diabetes control, assistance in making lifestyle modifications, and the facilitation of more informed treatment decision-making for health care professionals. The interviews with participants revealed 4 prominent themes regarding the perceived barriers to using mHealth app support for diabetes self-management. These themes were a lack of awareness about the availability of mHealth support, insufficient support in using mHealth apps, the perception that current mHealth apps do not align with users' specific needs, and limited digital literacy among users. The interviews with participants unveiled 4 key themes related to their needs and preferences concerning mHealth app support for diabetes self-management. These themes were the desire for educational information, user-friendly design features, carbohydrate-counting functionality, and the ability to engage socially with both peers and health care professionals. The majority of participants expressed their willingness to use mHealth apps if they received recommendations and guidance from health care professionals.

CONCLUSIONS

Patients generally perceive mHealth app support as beneficial for diabetes self-management and are willing to use these apps, particularly if recommended by health care professionals. However, several barriers may hinder the utilization of mHealth apps, including a lack of awareness and recommendations regarding these apps from health care professionals. To ensure the effective development of mHealth app support systems for diabetes self-management, it is crucial to implement user-centered design processes that consider the specific needs and preferences of patients. This approach will help create apps that are tailored to the requirements of individuals managing diabetes.

Understanding Whether and How a Digital Health Intervention Improves Transition Care for Emerging Adults Living With Type 1 Diabetes: Protocol for a Mixed Methods Realist Evaluation

BACKGROUND

Emerging adults living with type 1 diabetes (T1D) face a series of challenges with self-management and decreased health system engagement, leading to an increased risk of acute complications and hospital admissions. Effective and scalable strategies are needed to support this population to transfer seamlessly from pediatric to adult care with sufficient self-management capability. While digital health interventions for T1D self-management are a promising strategy, it remains unclear which elements work, how, and for which groups of individuals.

OBJECTIVE

This study aims to evaluate the design and implementation of a multicomponent SMS text message-based digital health intervention to support emerging adults living with T1D in real-world settings. The objectives are to identify the intervention components and associated mechanisms that support user engagement and T1D health care transition experiences and determine the individual characteristics that influence the implementation process.

METHODS

We used a realist evaluation embedded alongside a randomized controlled trial, which uses a sequential mixed methods design to analyze data from multiple sources, including intervention usage data, patient-reported outcomes, and realist interviews. In step 1, we conducted a document analysis to develop a program theory that outlines the hypothesized relationships among "individual-level contextual factors, intervention components and features, mechanisms, and outcomes," with special attention paid to user engagement. Among them, intervention components and features depict 10 core characteristics such as transition support information, problem-solving information, and real-time interactivity. The proximal outcomes of interest include user engagement, self-efficacy, and negative emotions, whereas the distal outcomes of interest include transition readiness, self-blood glucose monitoring behaviors, and blood glucose. In step 2, we plan to conduct semistructured realist interviews with the randomized controlled trial's intervention-arm participants to test the hypothesized "context-intervention-mechanism-outcome" configurations. In step 3, we plan to triangulate all sources of data using a coincidence analysis to identify the necessary combinations of factors that determine whether and how the desired outcomes are achieved and use these insights to consolidate the program theory.

RESULTS

For step 1 analysis, we have developed the initial program theory and the corresponding data collection plan. For step 2 analysis, participant enrollment for the randomized controlled trial started in January 2023. Participant enrollment for this realist evaluation was anticipated to start in July 2023 and continue until we reached thematic saturation or achieved informational power.

CONCLUSIONS

Beyond contributing to knowledge on the multiple pathways that lead to successful engagement with a digital health intervention as well as target outcomes in T1D care transitions, embedding the realist evaluation alongside the trial may inform real-time intervention refinement to improve user engagement and transition experiences. The knowledge gained from this study may inform the design, implementation, and evaluation of future digital health interventions that aim to improve transition experiences.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/46115.

Promoting Self-Management and Independent Living of Older Individuals with Chronic Diseases through Technology: A Study of Self-Reported Needs, Priorities, and Preferences

Background and Objectives: Older patients' needs are rarely examined beforehand, and thus, although technology-based tools can enhance self-management, acceptability rates are still low. This study aimed to examine and compare self-reported needs, priorities, and preferences of older patients with heart failure (HF), diabetes mellitus type II (DM2), and chronic obstructive pulmonary disease (COPD) toward technology use to enhance self-management. Materials and Methods: A convenience sample of 473 participants over 60 s (60.5% females), diagnosed with HF (n= 156), DM2 (n = 164), or COPD (n = 153) was recruited. They were administered a questionnaire about the usefulness of technology in general and in specific areas of disease management. Results: Most participants (84.7%) admitted that technology is needed for better disease management. This was equally recognized across the three groups both for the overall and specific areas of disease management (in order of priority: "Information", "Communication with Physicians and Caregivers", and "Quality of Life and Wellbeing"). Sociodemographic differences were found. Cell phones and PCs were the devices of preference. The four common features prioritized by all three groups were related to 'information about disease management' (i.e., monitoring symptoms, reminders for medication intake, management and prevention of complications), whereas the fifth one was related to 'communication with physicians and caregivers (i.e., in case of abnormal or critical signs). The top disease-specific feature was also monitoring systems (of respiratory rate or blood sugar or blood pressure, and oxygen), whereas other disease-specific features followed (i.e., maintaining normal weight for HF patients, adjusting insulin dose for DM2 patients, and training on breathing exercises for COPD patients). Conclusions: Older individuals in these three groups seem receptive to technology in disease management. mHealth tools, incorporating both common and disease-specific features and addressing different chronic patients, and also being personalized at the same time, could be cost-saving and useful adjuncts in routine clinical care to improve self-management.

Methods in realist evaluation: A mapping review

Realist evaluation is becoming increasingly popular as an evaluation methodology. Its main objective is to uncover the mechanisms that lead to observed outcomes following an intervention and the contextual conditions that enabled this. The focus is on explaining why, for whom and in what circumstances an intervention works. It is a theory-driven approach and is explicitly method neutral, meaning that both quantitative and qualitative data collection methods can be used to unearth the underlying mechanisms that cause the intervention outcomes. In this review, we aim to map the methods used in realist evaluation studies, to draw lessons from the findings and to reflect on ways forward. We found that qualitative methods and interviews specifically are most commonly used in realist evaluations; that theory is often absent behind the methods and sampling techniques used; and that more innovative methods remain underexplored. We conclude the review by proposing four ways forward: (1) developing realist surveys, (2) exploring the relevance of innovative methods, (3) increasing the attention paid to sampling procedures and (4) strengthening the theory-driven nature of method. We believe that these four action points can strengthen the practice of realist evaluation and its outcomes.

How Frequently and for How Long Do Adults With Type 2 Diabetes Use Management Apps? The REALL Study

OBJECTIVE

The objective of the study is to identify predictors of utilization of a type 2 diabetes (T2D) management App over time for insulin users (IUs) and noninsulin users (NIUs).

RESEARCH DESIGN AND METHODS

We followed over 16 weeks a national sample of unselected T2D adults who independently elected to download and pair a CONTOUR DIABETES App with their CONTOUR NEXT ONE glucose meter. App use and frequency of glucose testing were recorded. Baseline surveys recorded participant demographic, disease status, distress, medication taking, and views of technology to predict utilization.

RESULTS

Mean age was 51.6 years (108 IUs; 353 NIUs), 48% were female, time with diabetes was 6.9 years, and self-reported HbA1c was 8.1% (36.3 mmol/mol). Mean duration of App use was 85.4 days and 40% stopped using the App before 16 weeks. Continuous users were older and reported higher distress, better medication taking, and more positive attitudes toward technology (all P < .01). IUs tested more frequently than NIUs, but frequency and intensity of testing decreased markedly for both groups over time. More predictors of App use frequency and testing occurred for NIUs than IUs: older age, higher HbA1c, lower distress, more medication taking (all P < .05).

CONCLUSIONS

App use and testing decreased markedly over time. Variations in the predictors of frequency of App use suggest that the utilization of mobile technologies requires a tailored approach that addresses the specific needs of individual users, compared with adopting a one-size-fits-all strategy, and that IUs and NIUs may require very different strategies of customization.

First-time Mothers' Understanding and Use of a Pregnancy and Parenting Mobile App (The Baby Buddy App): Qualitative Study Using Appreciative Inquiry

BACKGROUND

Internationally, there is increasing emphasis on early support for pregnant women to optimize the health and development of mothers and newborns. To increase intervention reach, digital and app-based interventions have been advocated. There are growing numbers of pregnancy health care apps with great variation in style, function, and objectives, but evidence about impact on pregnancy well-being and behavior change following app interaction is lacking. This paper reports on the qualitative arm of the independent multicomponent study exploring the use and outcomes of first-time mothers using the Baby Buddy app, a pregnancy and parenting support app, available in the National Health Service App Library and developed by a UK child health and well-being charity, Best Beginnings.

OBJECTIVE

This study aims to understand when, why, and how first-time mothers use the Baby Buddy app and the perceived benefits and challenges.

METHODS

This paper reports on the qualitative arm of an independent, longitudinal, mixed methods study. An Appreciative Inquiry qualitative approach was used with semistructured interviews (17/60, 28%) conducted with new mothers, either by telephone or in a focus group setting. First-time mothers were recruited from 3 study sites from across the United Kingdom. Consistent with the Appreciative Inquiry approach, mothers were prompted to discuss what worked well and what could have been better regarding their interactions with the app during pregnancy. Thematic analysis was used, and findings are presented as themes with perceived benefits and challenges.

RESULTS

The main benefit, or what worked well, for first-time mothers when using the app was being able to access new information, which they felt was reliable and easy to find. This led to a feeling of increased confidence in the information they accessed, thus supporting family and professional communication. The main challenge was the preference for face-to-face information with a health care professional, particularly around specific issues that they wished to discuss in depth. What could have been improved included that there were some topics that some mothers would have preferred in more detail, but in other areas, they felt well-informed and thus did not feel a need to seek additional information via an app.

CONCLUSIONS

Although this study included a small sample, it elicited rich data and insights into first-time mothers' app interactions. The findings suggest that easily accessible pregnancy information, which is perceived as reliable, can support first-time mothers in communicating with health care professionals. Face-to-face contact with professionals was preferred, particularly to discuss specific and personalized needs. Further studies on maternal and professional digital support preferences after the COVID-19 global pandemic and how they facilitate antenatal education and informed decision-making are recommended, particularly because digital solutions remain as a key element in pregnancy and early parenting care.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1017/S1463423618000294.

Diabetes Self-management Apps: Systematic Review of Adoption Determinants and Future Research Agenda

BACKGROUND

Most diabetes management involves self-management. Effective self-management of the condition improves diabetes control, reduces the risk of complications, and improves patient outcomes. Mobile apps for diabetes self-management (DSM) can enhance patients' self-management activities. However, they are only effective if clinicians recommend them, and patients use them.

OBJECTIVE

This study aimed to explore the determinants of DSM apps' use by patients and their recommendations by health care professionals (HCPs). It also outlines the future research agenda for using DSM apps in diabetes care.

METHODS

We systematically reviewed the factors affecting the adoption of DSM apps by both patients and HCPs. Searches were performed using PubMed, Scopus, CINAHL, Cochrane Central, ACM, and Xplore digital libraries for articles published from 2008 to 2020. The search terms were diabetes, mobile apps, and self-management. Relevant data were extracted from the included studies and analyzed using a thematic synthesis approach.

RESULTS

A total of 28 studies met the inclusion criteria. We identified a range of determinants related to patients' and HCPs' characteristics, experiences, and preferences. Young female patients were more likely to adopt DSM apps. Patients' perceptions of the benefits of apps, ease of use, and recommendations by patients and other HCPs strongly affect their intention to use DSM apps. HCPs are less likely to recommend these apps if they do not perceive their benefits and may not recommend their use if they are unaware of their existence or credibility. Young and technology-savvy HCPs were more likely to recommend DSM apps.

CONCLUSIONS

Despite the potential of DSM apps to improve patients' self-care activities and diabetes outcomes, HCPs and patients remain hesitant to use them. However, the COVID-19 pandemic may hasten the integration of technology into diabetes care. The use of DSM apps may become a part of the new normal.

Sociotechnical Factors Affecting Patients' Adoption of Mobile Health Tools: Systematic Literature Review and Narrative Synthesis

BACKGROUND

Mobile health (mHealth) tools have emerged as a promising health care technology that may contribute to cost savings, better access to care, and enhanced clinical outcomes; however, it is important to ensure their acceptance and adoption to harness this potential. Patient adoption has been recognized as a key challenge that requires further exploration.

OBJECTIVE

The aim of this review was to systematically investigate the literature to understand the factors affecting patients' adoption of mHealth tools by considering sociotechnical factors (from technical, social, and health perspectives).

METHODS

A structured search was completed following the participants, intervention, comparators, and outcomes framework. We searched the MEDLINE, PubMed, Cochrane Library, and SAGE databases for studies published between January 2011 and July 2021 in the English language, yielding 5873 results, of which 147 studies met the inclusion criteria. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and the Cochrane Handbook were followed to ensure a systematic process. Extracted data were analyzed using NVivo (QSR International), with thematic analysis and narrative synthesis of emergent themes.

RESULTS

The technical factors affecting patients' adoption of mHealth tools were categorized into six key themes, which in turn were divided into 20 subthemes: usefulness, ease of use, data-related, monetary factors, technical issues, and user experience. Health-related factors were categorized into six key themes: the disease or health condition, the care team's role, health consciousness and literacy, health behavior, relation to other therapies, integration into patient journey, and the patients' insurance status. Social and personal factors were divided into three key clusters: demographic factors, personal characteristics, and social and cultural aspects; these were divided into 19 subthemes, highlighting the importance of considering these factors when addressing potential barriers to mHealth adoption and how to overcome them.

CONCLUSIONS

This review builds on the growing body of research that investigates patients' adoption of mHealth services and highlights the complexity of the factors affecting adoption, including personal, social, technical, organizational, and health care aspects. We recommend a more patient-centered approach by ensuring the tools' fit into the overall patient journey and treatment plan, emphasizing inclusive design, and warranting comprehensive patient education and support. Moreover, empowering and mobilizing clinicians and care teams, addressing ethical data management issues, and focusing on health care policies may facilitate adoption.

A qualitative evidence synthesis of users' experience of mobile health applications in the self-management of type 2 diabetes

AIM

The aim of this qualitative evidence synthesis was to identify and synthesise qualitative research relating to experiences of using mobile health (mHealth) applications to aid self-management of Type 2 Diabetes.

METHODS

Using a systematic search strategy, 11 databases were searched (Medline, CINAHL, PsychInfo, PubMed, Web of Science, Embase, Cochrane Library, Scopus, ProQuest A&1, ProQuest UK & Ireland, Mednar). "Best fit" framework synthesis was used guided by the Health Information Technology Acceptance Model (HITAM). Assessment of methodological limitations was conducted using Critical Appraisal Skills Programme (CASP) and confidence in the review findings were guided by GRADE-CERQual.

RESULTS

Fourteen eligible studies were included in the synthesis (7 qualitative and 5 mixed methods). Key themes identified under the health, information and technology zones of the HITAM revealed the benefits of mHealth apps, barriers to their use, their perceived usefulness and ease of use.

DISCUSSION

Most people used the apps for feedback on their self-management and found them helpful in their communication with health care providers. Some embraced the technology and found it easy to use while others found mHealth apps to be counterintuitive.

Complementarity of Digital Health and Peer Support: “This Is What’s Coming”

Purpose

This study examined integration of peer support and a Food and Drug Administration-cleared, diabetes management app (DMA) in diabetes self-management support as a scalable model for those with type 2 diabetes mellitus (T2DM).

Methods

Two lay health Coaches delivered telephone-based self-management support to adults (N = 43) with T2DM recruited through a primary group practice. Those eligible were offered no-cost access to DMA for the entire 6-month study. Coaches introduced DMA and contacted individuals by phone and text with frequency dependent on participant needs/preferences. DMA supported monitoring of blood glucose, carbohydrate intake, and medication use, as well as messaging personalized to participants’ medication regimens. Clinical data were extracted from DMA, electronic medical records, and Coaches’ records. Structured interviews of 12 participants, 2 Coaches, and 5 project staff were analyzed using deductive pre-identified codes (regarding adoptability, patterns of use, value added, complementarity, and sustainability) utilizing standard procedures for qualitative analysis.

Results

Of the 43 participants, 38 (88.4%) enrolled in DMA. In general, participants used both DMA and lay health coaches, averaging 144.14 DMA entries (structured, e.g., medications, and free form, e.g., “ate at a restaurant” and “stressed”) and 5.86 coach contacts over the 6-month intervention. Correlation between DMA entries and coach contacts (r = .613, p &lt; 0.001) was consistent with complementarity as were participants’ and coaches’ observations that (a) DMA facilitated recognition of patterns and provided reminders and suggestions to achieve self-management plans, whereas (b) coaching provided motivation and addressed challenges that emerged. Mean hemoglobin A1c (A1c) declined from 9.93% to 8.86% (p &lt; 0.001), with no pattern of coaching or DMA use significantly related to reductions. Staff identified resources to coordinate coach/DMA interventions as a major sustainability challenge.

Conclusions

DMA and peer support for diabetes management are compatible and complementary. Additional practice integration research is needed for adoption and scale-up.

Closing the Virtual Gap in Health Care: A Series of Case Studies Illustrating the Impact of Embedding Evaluation Alongside System Initiatives

Early decisions relating to the implementation of virtual care relied on necessity and clinical judgement, but there is a growing need for the generation of evidence to inform policy and practice designs. The need for stronger partnerships between researchers and decision-makers is well recognized, but how these partnerships can be structured and how research can be embedded alongside existing virtual care initiatives remain unclear. We present a series of case studies that illustrate how embedded research can inform policy decisions related to the implementation of virtual care, where decisions are either to (1) discontinue (red light), (2) redesign (yellow light), or (3) scale up existing initiatives (green light). Data were collected through document review and informal interviews with key study personnel. Case 1 involved an evaluation of a mobile diabetes platform that demonstrated a mismatch between the setting and the technology (decision outcome: discontinue). Case 2 involved an evaluation of a mental health support platform that suggested evidence-based modifications to the delivery model (decision outcome: redesign). Case 3 involved an evaluation of video visits that generated evidence to inform the ideal model of implementation at scale (decision outcome: scale up). In this paper, we highlight the characteristics of the partnership and the process that enabled success and use the cases to illustrate how these characteristics were operationalized. Structured communication included monthly check-ins and iterative report development. We also outline key characteristics of the partnership (ie, trust and shared purpose) and the process (ie, timeliness, tailored reporting, and adaptability) that drove the uptake of evidence in decision-making. Across each case, the evaluation was designed to address policy questions articulated by our partners. Furthermore, structured communication provided opportunities for knowledge mobilization. Structured communication was operationalized through monthly meetings as well as the delivery of interim and final reports. These case studies demonstrate the importance of partnering with health system decision-makers to generate and mobilize scientific evidence. Embedded research partnerships founded on a shared purpose of system service provided an effective strategy to bridge the oft-cited gap between science and policy. Structured communication provided a mechanism for collaborative problem-solving and real-time feedback, and it helped contextualize emerging insights.

Factors Associated With Intention to Adopt mHealth Apps Among Dementia Caregivers With a Chronic Condition: Cross-sectional, Correlational Study

Background

In the United States, nearly 80% of family caregivers of people with dementia have at least one chronic condition. Dementia caregivers experience high stress and burden that adversely affect their health and self-management. mHealth apps can improve health and self-management among dementia caregivers with a chronic condition. However, mHealth app adoption by dementia caregivers is low, and reasons for this are not well understood.

Objective

The purpose of this study is to explore factors associated with dementia caregivers’ intention to adopt mHealth apps for chronic disease self-management.

Methods

We conducted a cross-sectional, correlational study and recruited a convenience sample of dementia caregivers. We created a survey using validated instruments and collected data through computer-assisted telephone interviews and web-based surveys. Before the COVID-19 pandemic, we recruited dementia caregivers through community-based strategies, such as attending community events. After nationwide closures due to the pandemic, the team focused on web-based recruitment. Multiple logistic regression analyses were used to test the relationships between the independent and dependent variables.

Results

Our sample of 117 caregivers had an average age of 53 (SD 17.4) years, 16 (SD 3.3) years of education, and 4 (SD 2.5) chronic conditions. The caregivers were predominantly women (92/117, 78.6%) and minorities (63/117, 53.8%), experienced some to extreme income difficulties (64/117, 54.7%), and were the child or child-in-law (53/117, 45.3%) of the person with dementia. In logistic regression models adjusting for the control variables, caregiver burden (odds ratio [OR] 1.3, 95% CI 0.57-2.8; P=.57), time spent caregiving per week (OR 1.7, 95% CI 0.77-3.9; P=.18), and burden of chronic disease and treatment (OR 2.3, 95% CI 0.91-5.7; P=.08) were not significantly associated with the intention to adopt mHealth apps. In the final multiple logistic regression model, only perceived usefulness (OR 23, 95% CI 5.6-97; P<.001) and the interaction term for caregivers’ education and burden of chronic disease and treatment (OR 31, 95% CI 2.2-430; P=.01) were significantly associated with their intention to adopt mHealth apps. Perceived ease of use (OR 2.4, 95% CI 0.67-8.7; P=.18) and social influence (OR 1.8, 95% CI 0.58-5.7; P=.31) were not significantly associated with the intention to adopt mHealth apps.

Conclusions

When designing mHealth app interventions for dementia caregivers with a chronic condition, it is important to consider caregivers’ perceptions about how well mHealth apps can help their self-management and which app features would be most useful for self-management. Caregiving factors may not be relevant to caregivers’ intention to adopt mHealth apps. This is promising because mHealth strategies may overcome barriers to caregivers’ self-management. Future research should investigate reasons why caregivers with a low education level and low burden of chronic disease and treatment have significantly lower intention to adopt mHealth apps for self-management.

Identifying features of a mobile-based application for self-care of people living with T2DM

INTRODUCTION

Diabetes self-care requires support to empower patients to improve self-monitoring and maintain the necessary self-care behaviors. We aimed to identify features of a mobile-based application as a technology-based device for self-care of people living with T2DM.

METHOD

This study was conducted in two main phases in 2020. In the first phase, a literature review study was performed to identify the data elements and technical features of the T2DM self-care application. In the second phase, using the information obtained from the review of similar articles, a questionnaire was designed to validate identified requirements. The statistical population of the present study consisted of 22 endocrinologists and metabolic specialists.

RESULTS

Identification of 55 data elements and technical features for mobile-based self-care application for people with T2DM, and according to the statistical population, 15data elements for demographic requirements, 16 data elements for clinical requirements, and 17 features for the technical capability of this app were selected.

CONCLUSION

Blood sugar monitoring, exercise, nutrition, weight monitoring, and educational capabilities were the most highlighted technical features of the T2DM self-care application. Software designers can use these requirements to design a self-care app for people with type-2 diabetes that can help manage and improve patients' health status.

A Mobile App for Diabetes Management: Impact on Self-Efficacy Among Patients with Type 2 Diabetes at a Community Hospital

Background

Patients with type 2 diabetes upload and review blood glucose data between clinic visits. Many mobile phone applications (apps) that receive data from a “connected” glucometer and that support pattern management are available and have the capacity to make data upload and review less burdensome.

The objective of this study was to assess whether the diabetic management app could improve glycemic control and diabetes self-efficacy in a Chinese community hospital by a randomized controlled trial.

Material/Methods

One-hundred twenty patients with type 2 diabetes registered at the Community Health Service Center of Zhangjiawo Town, Xiqing District, Tianjin City, China were recruited and volunteered to participate in the project. They were randomly divided into the mobile app intervention group (n=60) and the control group (n=60) for a 6-month observation. The control group was given conventional diabetic treatment and the app group was given the mobile app and conventional care. Self-efficacy was measured by the Diabetes Self-Efficacy Scale questionnaire. The differences between the 2 groups in hemoglobin A1c (Hb_A1c) and diabetes self-efficacy were evaluated at the third and sixth months.

Results

At the sixth month, patients in the app group showed better Hb_A1c control (6.71±1.06 vs. 7.22±1.02, P<0.05) and improved self-efficacy score (119.20±9.88 vs. 102.09±10.67, P<0.05).

Conclusions

The mobile app helped patients with type 2 diabetes in a community hospital improve therapeutic outcome and self-management behavior. It also provided experiences for prevention and management of other chronic diseases in community hospitals.

Strategies to Overcome Therapeutic Inertia in Type 2 Diabetes Mellitus: A Scoping Review

The objectives of this review were to: 1) examine recent strategies and component interventions used to overcome therapeutic inertia in type 2 diabetes mellitus (T2DM), 2) map strategies to the causes of therapeutic inertia they target and 3) identify causes of therapeutic inertia in T2DM that have not been targeted by recent strategies. A systematic search of the literature published from January 2014 to December 2019 was conducted to identify strategies targeting therapeutic inertia in T2DM, and key strategy characteristics were extracted and summarized. The search identified 46 articles, employing a total of 50 strategies aimed at overcoming therapeutic inertia. Strategies were composed of an average of 3.3 interventions (range, 1 to 10) aimed at an average of 3.6 causes (range, 1 to 9); most (78%) included a type of educational strategy. Most strategies targeted causes of inertia at the patient (38%) or health-care professional (26%) levels only and 8% targeted health-care-system-level causes, whereas 28% targeted causes at multiple levels. No strategies focused on patients' attitudes toward disease or lack of trust in health-care professionals; none addressed health-care professionals' concerns over costs or lack of information on side effects/fear of causing harm, or the lack of a health-care-system-level disease registry. Strategies to overcome therapeutic inertia in T2DM commonly employed multiple interventions, but novel strategies with interventions that simultaneously target multiple levels warrant further study. Although educational interventions are commonly used to address therapeutic inertia, future strategies may benefit from addressing a wider range of determinants of behaviour change to overcome therapeutic inertia.

A realist evaluation approach to explaining the role of context in the impact of a complex eHealth intervention for improving prevention of cardiovascular disease

Background

Reduction of cardiovascular disease (CVD) is a worldwide health priority and innovative uses of technology-based interventions may assist patients with improving prevention behaviours. Targeting these interventions to recipients most likely to benefit requires understanding how contexts of use influence responsiveness to the intervention, and how this interaction favours or discourages health behaviour. Using a realist evaluation approach, the aim of this study was to examine the contextual factors influencing behaviour change within a multi-feature eHealth intervention with personalised data integration from the primary care electronic health record (EHR).

Methods

Realist evaluation of qualitative data from the Consumer Navigation of Electronic Cardiovascular Tools (CONNECT) randomised trial (N = 934). Thirty-six participants from the intervention group (N = 486) who had completed 12 months of study follow-up were interviewed. Coding of transcripts was structured around configurations of contexts, mechanisms, and outcomes of intervention use. Contextual narratives were derived from thematic analysis of the interviews.

Results

Mechanisms favouring positive health behaviour occurred when participants responded to four interactive features of the intervention. Facilitating mechanisms included greater cognitive engagement whereby participants perceived value and benefit, and felt motivated, confident and incentivised. Participants moved from being unconcerned (or unaware) to more task-oriented engagement with personal CVD risk profile and prevention. Increased personalisation occurred when modifiable CVD risk factors became relatable to lifestyle behaviour; and experiences of feeling greater agency/self-efficacy emerged. Use and non-use of the intervention were influenced by four overarching narratives within the individual’s micro-level and meso-level environments: illness experiences; receptiveness to risk and prevention information; history of the doctor-patient relationship; and relationship with technology.

Conclusions

Intervention-context interactions are central to understanding how change mechanisms activate within complex interventions to exert their impact on recipients. Intervention use and non-use were context-dependent, underscoring the need for further research to target eHealth innovations to those most likely to benefit.

Patients’ and healthcare professionals’ perspectives towards technology-assisted diabetes self-management education. A qualitative systematic review

Introduction

Diabetes self-management education is a key aspect in the long-term management of type 2 diabetes. The patient and healthcare professional (HCP) perspective on the use of technology-assisted DSME has yet to be studied. Hence, the objective of this study was to better understand the factors that facilitate or hinder the adoptions of such education by adults with type 2 diabetes and their HCPs.

Methods

We systematically searched five databases (Medline, Embase, CINAHL, Web of Science Core Collection, and PsycINFO) until August 2019. The search included qualitative and mixed-method studies that reported the views of patients and HCPs regarding features, uses, and implementations of technology-assisted DSME. Data were synthesized through an inductive thematic analysis.

Results

A total of 13 articles were included, involving 242 patients, ranging from 18 to 81 years and included web-based, mobile application, digital versatile disc (DVD), virtual reality or telehealth interventions. Patients and HCPs had mixed views towards features of the technology-assisted interventions, with patients’ personal qualities and HCPs’ concerns affecting uses of the interventions. Patients generally preferred technologies that were easy to access, use, and apply and that had reliable information. Patients’ ambitions motivated them, and personal attributes such as poor competence with technology, poor literacy, and language barriers acted as barriers. Patients especially liked the peer support that they received but did not like it when there was no regulation of advice on these platforms. HCPs believed that while the interventions were useful to patients, they faced difficulties with integration into their clinical workflows.

Conclusion

This review explored the features of technology-assisted diabetes self-management education interventions that enhanced positive patient engagements and the negative aspects of both the platforms and the target groups. Technical support and training will be effective in managing these concerns and ensuring meaningful use of these platforms.

User Experiences With a Type 2 Diabetes Coaching App: Qualitative Study

BACKGROUND

Diabetes self-management apps have the potential to improve self-management in people with type 2 diabetes (T2D). Although efficacy trials provide evidence of health benefits, premature disengagement from apps is common. Therefore, it is important to understand the factors that influence engagement in real-world settings.

OBJECTIVE

This study aims to explore users' real-world experiences with the My Diabetes Coach (MDC) self-management app.

METHODS

We conducted telephone-based interviews with participants who had accessed the MDC self-management app via their smartphone for up to 12 months. Interviews focused on user characteristics; the context within which the app was used; barriers and facilitators of app use; and the design, content, and delivery of support within the app.

RESULTS

A total of 19 adults with T2D (8/19, 42% women; mean age 60, SD 14 years) were interviewed. Of the 19 interviewees, 8 (42%) had T2D for <5 years, 42% (n=8) had T2D for 5-10 years, and 16% (n=3) had T2D for >10 years. In total, 2 themes were constructed from interview data: (1) the moderating effect of diabetes self-management styles on needs, preferences, and expectations and (2) factors influencing users' engagement with the app: one size does not fit all.

CONCLUSIONS

User characteristics, the context of use, and features of the app interact and influence engagement. Promoting engagement is vital if diabetes self-management apps are to become a useful complement to clinical care in supporting optimal self-management.

TRIAL REGISTRATION

Australia New Zealand Clinical Trials Registry CTRN126140012296; URL https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366925&isReview=true.

Methods and Evaluation Criteria for Apps and Digital Interventions for Diabetes Self-Management: Systematic Review

BACKGROUND

There is growing evidence that apps and digital interventions have a positive impact on diabetes self-management. Standard self-management for patients with diabetes could therefore be supplemented by apps and digital interventions to increase patients' skills. Several initiatives, models, and frameworks suggest how health apps and digital interventions could be evaluated, but there are few standards for this. And although there are many methods for evaluating apps and digital interventions, a more specific approach might be needed for assessing digital diabetes self-management interventions.

OBJECTIVE

This review aims to identify which methods and criteria are used to evaluate apps and digital interventions for diabetes self-management, and to describe how patients were involved in these evaluations.

METHODS

We searched CINAHL, EMBASE, MEDLINE, and Web of Science for articles published from 2015 that referred to the evaluation of apps and digital interventions for diabetes self-management and involved patients in the evaluation. We then conducted a narrative qualitative synthesis of the findings, structured around the included studies' quality, methods of evaluation, and evaluation criteria.

RESULTS

Of 1681 articles identified, 31 fulfilled the inclusion criteria. A total of 7 articles were considered of high confidence in the evidence. Apps were the most commonly used platform for diabetes self-management (18/31, 58%), and type 2 diabetes (T2D) was the targeted health condition most studies focused on (12/31, 38%). Questionnaires, interviews, and user-group meetings were the most common methods of evaluation. Furthermore, the most evaluated criteria for apps and digital diabetes self-management interventions were cognitive impact, clinical impact, and usability. Feasibility and security and privacy were not evaluated by studies considered of high confidence in the evidence.

CONCLUSIONS

There were few studies with high confidence in the evidence that involved patients in the evaluation of apps and digital interventions for diabetes self-management. Additional evaluation criteria, such as sustainability and interoperability, should be focused on more in future studies to provide a better understanding of the effects and potential of apps and digital interventions for diabetes self-management.

Characterizing the US Population by Patterns of Mobile Health Use for Health and Behavioral Tracking: Analysis of the National Cancer Institute's Health Information National Trends Survey Data

BACKGROUND

Multiple types of mobile health (mHealth) technologies are available, such as smartphone health apps, fitness trackers, and digital medical devices. However, despite their availability, some individuals do not own, do not realize they own, or own but do not use these technologies. Others may use mHealth devices, but their use varies in tracking health, behaviors, and goals. Examining patterns of mHealth use at the population level can advance our understanding of technology use for health and behavioral tracking. Moreover, investigating sociodemographic and health-related correlates of these patterns can provide direction to researchers about how to target mHealth interventions for diverse audiences.

OBJECTIVE

The aim of this study was to identify patterns of mHealth use for health and behavioral tracking in the US adult population and to characterize the population according to those patterns.

METHODS

We combined data from the 2017 and 2018 National Cancer Institute Health Information National Trends Survey (N=6789) to characterize respondents according to 5 mutually exclusive reported patterns of mHealth use for health and behavioral tracking: (1) mHealth nonowners and nonusers report not owning or using devices to track health, behaviors, or goals; (2) supertrackers track health or behaviors and goals using a smartphone or tablet plus other devices (eg, Fitbit); (3) app trackers use only a smartphone or tablet; (4) device trackers use only nonsmartphone or nontablet devices and do not track goals; and (5) nontrackers report having smartphone or tablet health apps but do not track health, behaviors, or goals.

RESULTS

Being in the mHealth nonowners and nonusers category (vs all mHealth owners and users) is associated with males, older age, lower income, and not being a health information seeker. Among mHealth owners and users, characteristics of device trackers and supertrackers were most distinctive. Compared with supertrackers, device trackers have higher odds of being male (odds ratio [OR] 2.22, 95% CI 1.55-3.19), older age (vs 18-34 years; 50-64 years: OR 2.83, 95% CI 1.52-5.30; 65+ years: OR 6.28, 95% CI 3.35-11.79), have an annual household income of US $20,000 to US $49,999 (vs US $75,000+: OR 2.31, 95% CI 1.36-3.91), and have a chronic condition (OR 1.69, 95% CI 1.14-2.49). Device trackers also have higher odds of not being health information seekers than supertrackers (OR 2.98, 95% CI 1.66-5.33).

CONCLUSIONS

Findings revealed distinctive sociodemographic and health-related characteristics of the population by pattern of mHealth use, with notable contrasts between those who do and do not use devices to track goals. Several characteristics of individuals who track health or behaviors but not goals (device trackers) are similar to those of mHealth nonowners and nonusers. Our results suggest patterns of mHealth use may inform how to target mHealth interventions to enhance reach and facilitate healthy behaviors.

A Mobile-Based Intervention for Glycemic Control in Patients With Type 2 Diabetes: Retrospective, Propensity Score-Matched Cohort Study

Background

Mobile-based interventions appear to be promising in ameliorating huge burdens experienced by patients with type 2 diabetes. However, it is unclear how effective mobile-based interventions are in glycemic management of patients with type 2 diabetes based on real-world evidence.

Objective

This study aimed to evaluate the effectiveness of a mobile-based intervention on glycemic control in patients with type 2 diabetes based on real-world population data.

Methods

This retrospective, propensity score-matched cohort study analyzed longitudinal data from a clinical electronic health database. The study population included 37,913 patients with type 2 diabetes at cohort entry between October 1, 2016, and July 31, 2018. A total of 2400 patients were matched 1:1, using propensity score matching, into the usual care and mobile health (mHealth) groups. The primary outcomes of glycemic control included control rates of glycated hemoglobin (HbA_1c), fasting blood glucose (FBG), and postprandial 2-hour blood glucose (P2BG). Mean values and variation trends of difference with 95% CI were the secondary outcomes. The general linear model was used to calculate repeated-measures analyses of variance to examine the differences between the two groups. Subgroup and sensitivity analyses were performed.

Results

Of the 2400 patients included in the analysis, 1440 (60.00%) were male and the mean age was 52.24 years (SD 11.56). At baseline, the control rates of HbA_1c, FBG, and P2BG in the mHealth and usual care groups were 45.75% versus 47.00% (P=.57), 38.03% versus 32.76% (P=.07), and 47.32% versus 47.89% (P=.83), respectively. At the 3-, 6-, 9-, and 12-month follow-ups, the mHealth group reported higher control rates of HbA_1c than did the usual care group: 69.97% versus 46.06% (P<.001), 71.89% versus 61.24% (P=.004), 75.38% versus 53.44% (P<.001), and 72.31% versus 46.70% (P<.001), respectively. At the four follow-up sessions, the control rates of FBG in the mHealth and usual care groups were statistically different: 59.24% versus 34.21% (P<.001), 56.61% versus 35.14% (P<.001), 59.54% versus 34.99% (P<.001), and 59.77% versus 32.83% (P<.001), respectively. At the four follow-up sessions, the control rates of P2BG in the mHealth group were statistically higher than in the usual care group: 79.72% versus 48.75% (P<.001), 80.20% versus 57.45% (P<.001), 81.97% versus 54.07% (P<.001), and 76.19% versus 54.21% (P=.001), respectively. At the four follow-up sessions, the percentages of HbA_1c reduction in the mHealth group were 8.66% (95% CI 6.69-10.63), 10.60% (95% CI 8.66-12.54), 10.64% (95% CI 8.70-12.58), and 8.11% (95% CI 6.08-10.14), respectively. At the four follow-up sessions, the percentages of P2BG reduction in the mHealth group were 8.44% (95% CI 7.41-10.73), 17.77% (95% CI 14.98-20.23), 16.23% (95% CI 13.05-19.35), and 16.91% (95% CI 13.17-19.84), respectively. Starting from the sixth month, the mean HbA_1c and P2BG values in the two groups increased slightly.

Conclusions

This mobile-based intervention delivered by a multidisciplinary team can better improve glycemic control rates of patients with type 2 diabetes than usual care. These effects were best sustained within the first 6 months. Starting from the sixth month, intensive management needs to be conducted to maintain long-term effectiveness of the mobile-based intervention.

m-SFT: A Novel Mobile Health System to Assess the Elderly Physical Condition

The development of innovative solutions that allow the aging population to remain healthier and independent longer is essential to alleviate the burden that this increasing segment of the population supposes for the long term sustainability of the public health systems. It has been claimed that promoting physical activity could prevent functional decline. However, given the vulnerability of this population, the activity prescription requires to be tailored to the individual's physical condition. We propose mobile Senior Fitness Test (m-SFT), a novel m-health system, that allows the health practitioner to determine the elderly physical condition by implementing a smartphone-based version of the senior fitness test (SFT). The technical reliability of m-SFT has been tested by carrying out a comparative study in seven volunteers (53-61 years) between the original SFT and the proposed m-health system obtaining high agreement (intra-class correlation coefficient (ICC) between 0.93 and 0.99). The system usability has been evaluated by 34 independent health experts (mean = 36.64 years; standard deviation = 6.26 years) by means of the System Usability Scale (SUS) obtaining an average SUS score of 84.4 out of 100. Both results point out that m-SFT is a reliable and easy to use m-health system for the evaluation of the elderly physical condition, also useful in intervention programs to follow-up the patient's evolution.

mHealth Apps as Effective Persuasive Health Technology: Contextualizing the "Necessary" Functionalities

Persuasive health technology (PHT) is any technology purposely designed to influence, reinforce, change, or shape health-related attitudes or behaviors. Behavioral interventions can be developed for the purpose of maintaining or improving a person's health status. Delivering behavioral interventions via PHTs is a promising approach for encouraging healthy behaviors among individuals and populations. Important attributes of all PHTs include their functionalities. A functionality refers to any useful features, functions, capabilities, or technologies associated with computer hardware or software. Creating effective PHTs requires a deliberate selection of appropriate functionalities for supporting specific behavioral interventions. The number and types of functionalities necessary to create an effective PHT will be specific to the context of each project, influenced by project objectives, stakeholder goals, behavioral interventions, and a variety of real-world constraints. Selecting appropriate functionalities can be challenging. Fortunately, there are frameworks and models developed specifically for guiding the design of PHTs. The Persuasive Systems Design model describes 4 categories, and 28 design principles for creating effective persuasive interventions. These same design principles could also be useful for guiding the selection of appropriate functionalities.

Identifying and Overcoming Policy-Level Barriers to the Implementation of Digital Health Innovation: Qualitative Study

Background

High-level policy barriers impede widespread adoption for even the most well-positioned innovations. Most of the work in this field assumes rather than analyzes the driving forces of health innovation. Objective: The aim of this study was to explore the challenges and opportunities experienced by health system stakeholders in the implementation of digital health innovation in Ontario.

Objective

The aim of this study was to explore the challenges and opportunities experienced by health system stakeholders in the implementation of digital health innovation in Ontario.

Methods

We completed semistructured interviews with 10 members of senior leadership across key organizations that are engaged in health care–related digital health activities. Data were analyzed using qualitative description.

Results

A total of 6 key policy priorities emerged, including the need for (1) a system-level definition of innovation, (2) a clear overarching mission, and (3) clearly defined organizational roles. Operationally, there is a need to (4) standardize processes, (5) shift the emphasis to change management, and (6) align funding structures.

Conclusions

These findings emphasize the critical role of the government in developing a vision and creating the foundation upon which innovation activities will be modeled.

Evaluation of Heart Failure Apps to Promote Self-Care: Systematic App Search

Background

Heart failure (HF) is a chronic disease that affects over 1% of Canadians and at least 26 million people worldwide. With the continued rise in disease prevalence and an aging population, HF-related costs are expected to create a significant economic burden. Many mobile health (mHealth) apps have been developed to help support patients’ self-care in the home setting, but it is unclear if they are suited to the needs or capabilities of older adults.

Objective

This study aimed to identify HF apps and evaluate whether they met the criteria for optimal HF self-care.

Methods

We conducted a systematic search of all apps available exclusively for HF self-care across Google Play and the App Store. We then evaluated the apps according to a list of 25 major functions pivotal to promoting HF self-care for older adults.

Results

A total of 74 apps for HF self-care were identified, but only 21 apps were listed as being both HF and self-care specific. None of the apps had all 25 of the listed features for an adequate HF self-care app, and only 41% (31/74) apps had the key weight management feature present. HF Storylines received the highest functionality score (18/25, 72%).

Conclusions

Our findings suggest that currently available apps are not adequate for use by older adults with HF. This highlights the need for mHealth apps to refine their development process so that user needs and capabilities are identified during the design stage to ensure the usability of the app.

Patients' Perceptions of mHealth Apps: Meta-Ethnographic Review of Qualitative Studies

BACKGROUND

Mobile phones and tablets are being increasingly integrated into the daily lives of many people worldwide. Mobile health (mHealth) apps have promising possibilities for optimizing health systems, improving care and health, and reducing health disparities. However, health care apps often seem to be underused after being downloaded.

OBJECTIVE

The aim of this paper is to reach a better understanding of people's perceptions, beliefs, and experience of mHealth apps as well as to determine how highly they appreciate these tools.

METHODS

A systematic review was carried out on qualitative studies published in English, on patients' perception of mHealth apps between January 2013 and June 2018. Data extracted from these articles were synthesized using a meta-ethnographic approach and an interpretative method.

RESULTS

A total of 356 articles were selected for screening, and 43 of them met the inclusion criteria. Most of the articles included populations inhabiting developed countries and were published during the last 2 years, and most of the apps on which they focused were designed to help patients with chronic diseases. In this review, we present the strengths and weaknesses of using mHealth apps from the patients' point of view. The strengths can be categorized into two main aspects: engaging patients in their own health care and increasing patient empowerment. The weaknesses pointed out by the participants focus on four main topics: trustworthiness, appropriateness, personalization, and accessibility of these tools.

CONCLUSIONS

Although many of the patients included in the studies reviewed considered mHealth apps as a useful complementary tool, some major problems arise in their optimal use, including the need for more closely tailored designs, the cost of these apps, the validity of the information delivered, and security and privacy issues. Many of these issues could be resolved with more support from health providers. In addition, it would be worth developing standards to ensure that these apps provide patients accurate evidence-based information.

A Digital-First Model of Diabetes Care

If we were to create the diabetes care experience anew, there is little doubt that it would not resemble the current bricks-and-mortar way we do things currently. For however a future model of care is designed, it would assume a digital-first approach, whereby the modern conveniences of digitally-mediated services we have experienced in other industries would be reflected in our diabetes care. To this end, our diabetes data would be liberated, transparent to those that need it, but safe and secure otherwise. We would have access to new tools that create insights that lower the burden, not add to it. And access to care would be just in time, convenient, and from a distance when needed. What is stopping a digital-first model is complex and deeply seated, but not insurmountable with engagement from industry, regulators, and care providers that are all willing to modernize the way care is delivered. Personal human interaction will continue to play an important part in the care for millions of people living with diabetes, no matter the sophistication of these digital services. What these technologies will provide is the human capacity to deal with the higher need, vulnerable people for whom access to timely care is an issue. Moreover, it will provide choice for an increasingly diverse population that seeks options for the form, and the delivery, of their personalized care.

Assessment of Rwandan diabetic patients' needs and expectations to develop their first diabetes self-management smartphone application (Kir'App)

BACKGROUND

Knowledge of and coping with diabetes is still poor in some communities in Rwanda. While smartphone applications (or apps) have demonstrated improving diabetes self-care, there is no current study on the use of smartphones in the self-management of diabetes in Rwanda.

METHODS

The main objective of this study was to assess the needs and expectations of Rwandan diabetic patients for mobile-health-supported diabetes self-management in order to develop a patient-centred smartphone application (Kir'App).

RESULTS

Convenience sampling was used to recruit study participants at the Rwanda Diabetes Association. Twenty-one patients participated in semi-structured, in-depth, face-to-face interviews. Thematic analysis was performed using Mayring's method of qualitative content analysis.

CONCLUSIONS

The study included 21 participants with either type 1 (female = 5, male = 6) or type 2 (female = 6, male = 4) diabetes. Participants' age ranged from 18 to 69 years with a mean age of 35 and 29 years, respectively. Eight main themes were identified. These were (a) diabetes education and desired information provision; (b) lack of diabetes knowledge and awareness; (c) need for information in crisis situations; (d) required monitoring and reminder functions; (e) information on nutrition and alcohol consumption; (f) information on physical activity; (g) coping with burden of disease, through social support and network; (h) app features. This study provides recommendations that will be used to design the features of the first Rwandan diabetes self-management smartphone application (Kir'App). The future impact of the application on the Rwandan diabetic patients' self-management capacity and quality of life will be evaluated afterwards.

A Noninvasive, Economical, and Instant-Result Method to Diagnose and Monitor Type 2 Diabetes Using Pulse Wave: Case-Control Study

Background

We should pay more attention to the long-term monitoring and early warning of type 2 diabetes and its complications. The traditional blood glucose tests are traumatic and cannot effectively monitor the development of diabetic complications. The development of mobile health is changing rapidly. Therefore, we are interested in developing a new noninvasive, economical, and instant-result method to accurately diagnose and monitor type 2 diabetes and its complications.

Objective

We aimed to determine whether type 2 diabetes and its complications, including hypertension and hyperlipidemia, could be diagnosed and monitored by using pulse wave.

Methods

We collected the pulse wave parameters from 50 healthy people, 139 diabetic patients without hypertension and hyperlipidemia, 133 diabetic patients with hypertension, 70 diabetic patients with hyperlipidemia, and 75 diabetic patients with hypertension and hyperlipidemia. The pulse wave parameters showing significant differences among these groups were identified. Various machine learning models such as linear discriminant analysis, support vector machines (SVMs), and random forests were applied to classify the control group, diabetic patients, and diabetic patients with complications.

Results

There were significant differences in several pulse wave parameters among the 5 groups. The parameters height of tidal wave (h₃), time distance between the start point of pulse wave and dominant wave (t₁), and width of percussion wave in its one-third height position (W) increase and the height of dicrotic wave (h₅) decreases when people develop diabetes. The parameters height of dominant wave (h₁), h₃, and height of dicrotic notch (h₄) are found to be higher in diabetic patients with hypertension, whereas h₅ is lower in diabetic patients with hyperlipidemia. For detecting diabetes, the method with the highest out-of-sample prediction accuracy is SVM with polynomial kernel. The algorithm can detect diabetes with 96.35% accuracy. However, all the algorithms have a low accuracy when predicting diabetic patients with hypertension and hyperlipidemia (below 70%).

Conclusions

The results demonstrated that the noninvasive and convenient pulse-taking diagnosis described in this paper has the potential to become a low-cost and accurate method to monitor the development of diabetes. We are collecting more data to improve the accuracy for detecting hypertension and hyperlipidemia among diabetic patients. Mobile devices such as sport bands, smart watches, and other diagnostic tools are being developed based on the pulse wave method to improve the diagnosis and monitoring of diabetes, hypertension, and hyperlipidemia.

Mobile phone applications and their use in the self-management of Type 2 Diabetes Mellitus: a qualitative study among app users and non-app users

BACKGROUND

Mobile phone applications (apps) have been shown to successfully facilitate the self-management of chronic disease. This study aims to evaluate firstly the experiences, barriers and facilitators to app usage among people with Type 2 Diabetes Mellitus (T2DM) and secondly determine recommendations to improve usage of diabetes apps.

METHODS

Participants were aged ≥ 18 years with a diagnosis of T2DM for ≥ 6 months. Semi-structured phone-interviews were conducted with 16 app and 14 non-app users. Interviews were based on the Technology Acceptance Model, Health Information Technology Acceptance Model (HITAM) and the Mobile Application Rating Scale. Data were analysed using deductive content analysis.

RESULTS

Most app-users found apps improved their T2DM self-management and health. The recommendation of apps by health professionals, as well as positive interactions with them, improved satisfaction; however, only a minority of patients had practitioners involved in their app use. All non-app users had never had the concept discussed with them by a health professional. Facilitators to app use included the visual representation of trends, intuitive navigation and convenience (for example, discretion and portability). Barriers to app use were participant's lack of knowledge and awareness of apps as healthcare tools, perceptions of disease severity, technological and health literacy or practical limitations such as rural connectivity. Factors contributing to app use were classified into a framework based on the Health Belief Model and HITAM. Recommendations for future app design centred on educational features, which were currently lacking (e.g. diabetes complications, including organ damage and hypoglycaemic episodes), monitoring and tracking features (e.g. blood glucose level monitoring with trends and dynamic tips and comorbidities) and nutritional features (e.g. carbohydrate counters). Medication reminders were not used by participants. Lastly, participants felt that receiving weekly text-messaging relating to their self-management would be appropriate.

CONCLUSIONS

The incorporation of user-centred features, which engage T2DM consumers in self-management tasks, can improve health outcomes. The findings may guide app developers and entrepreneurs in improving app design and usability. Given self-management is a significant factor in glycaemic control, these findings are significant for GPs, nurse practitioners and allied health professionals who may integrate apps into a holistic management plan which considers strategies outside the clinical environment.

Unveiling the Black Box of Diagnostic and Clinical Decision Support Systems for Antenatal Care: Realist Evaluation

BACKGROUND

Digital innovations have shown promise for improving maternal health service delivery. However, low- and middle-income countries are still at the adoption-utilization stage. Evidence on mobile health has been described as a black box, with gaps in theoretical explanations that account for the ecosystem of health care and their effect on adoption mechanisms. Bliss4Midwives, a modular integrated diagnostic kit to support antenatal care service delivery, was piloted for 1 year in Northern Ghana. Although both users and beneficiaries valued Bliss4Midwives, results from the pilot showed wide variations in usage behavior and duration of use across project sites.

OBJECTIVE

To strengthen the design and implementation of an improved prototype, the study objectives were two-fold: to identify causal factors underlying the variation in Bliss4Midwives usage behavior and understand how to overcome or leverage these in subsequent implementation cycles.

METHODS

Using a multiple case study design, a realist evaluation of Bliss4Midwives was conducted. A total of 3 candidate program theories were developed and empirically tested in 6 health facilities grouped into low and moderate usage clusters. Quantitative and qualitative data were collected and analyzed using realist thinking to build configurations that link intervention, context, actors, and mechanisms to program outcomes, by employing inductive and deductive reasoning. Nonparametric t test was used to compare the perceived usefulness and perceived ease of use of Bliss4Midwives between usage clusters.

RESULTS

We found no statistically significant differences between the 2 usage clusters. Low to moderate adoption of Bliss4Midwives was better explained by fear, enthusiasm, and high expectations for service delivery, especially in the absence of alternatives. Recognition from pregnant women, peers, supervisors, and the program itself was a crucial mechanism for device utilization. Other supportive mechanisms included ownership, empowerment, motivation, and adaptive responses to the device, such as realignment and negotiation. Champion users displayed high adoption-utilization behavior in contexts of participative or authoritative supervision, yet used the device inconsistently. Intervention-related (technical challenges, device rotation, lack of performance feedback, and refresher training), context-related (staff turnover, competing priorities, and workload), and individual factors (low technological self-efficacy, baseline knowledge, and internal motivation) suppressed utilization mechanisms.

CONCLUSIONS

This study shed light on optimal conditions necessary for Bliss4Midwives to thrive in a complex social and organizational setting. Beyond usability and viability studies, advocates of innovative technologies for maternal care need to consider how implementation strategies and contextual factors, such as existing collaborations and supervision styles, trigger mechanisms that influence program outcomes. In addition to informing scale-up of the Bliss4Midwives prototype, our results highlight the need for interventions that are guided by research methods that account for complexity.