Promoting Engagement With a Digital Health Intervention (HeLP-Diabetes) Using Email and Text Message Prompts: Mixed-Methods Study

Uptake of Digital Health Interventions for Cardiometabolic Disease in British South Asian Individuals: Think Aloud Study

Background

Digital health interventions (DHIs) could support prevention and management of cardiometabolic disease. However, those who may benefit most often experience barriers to awareness and adoption of these interventions.

Objective

Among South Asian individuals, we evaluated user experience of DHIs for prevention and management of cardiometabolic disease, aiming to understand barriers and facilitators to initial and ongoing use.

Methods

Among South Asian individuals recruited via primary care, community organizations, and snowball methods (n=18), we conducted "think-aloud" interviews using a reflective and reactive approach. Participants included nonusers, as well as those that used a range of DHIs as part of monitoring and improving their health. Participants were asked to think aloud while completing a task they routinely do in a familiar DHI, as well as while setting up and completing a search task in a novel DHI; they were encouraged to behave as if unobserved.

Results

Lack of cultural specificity was highlighted as reducing relevance and usability, particularly relating to dietary change. Preferred features reflected individual health beliefs and behaviors, digital skills, and trust in DHIs. For example, tracking blood glucose was considered by some to be positive, while for others it caused distress and anxiety. Similarly, some users found the novel DHI to be extremely simple to set up and use, and others grew frustrated navigating through initial interfaces. Many participants raised concerns about data privacy and needing to agree to terms and conditions that they did not understand. Participants expressed that with information and support from trusted sources, they would be interested in using DHIs as part of self-management.

Conclusions

DHIs may support South Asians to prevent and manage cardiometabolic disease, but it is important to consider the needs of specific user groups in DHI development, design, and implementation. Despite motivation to make health changes, digital barriers are common. Cultural appropriateness and trusted sources (such as health care providers and community organizations) have roles in increasing awareness and enabling individuals to access and use DHIs.

Understanding Engagement With Forensic Smartphone Apps: The Service Design Engagement Model

Justice services have begun to integrate the use of mobile applications into treatment, support, and rehabilitative programs for forensic clients. One such application that been adopted to support forensic clients is "eRecovery": a smartphone application that provides clients recovering from a substance addiction with support for managing relapse. In this article, we report on evaluation findings from a trial of eRecovery in an Australian Community Justice Centre, and reflect on several issues relating to fostering and sustaining client engagement with similar applications within forensic and justice settings. We propose the Service Design Engagement Model to organize, visualize, and describe the stages and factors important to adoption, appropriation, and on-going routine use of the software by forensic clients. The model recognizes the role of contextual and environmental factors in supporting users through the early stages of engagement, and the importance of user agency in longer-term engagement with therapeutic apps.

Digital health technologies for high-risk pregnancy management: three case studies using Digilego framework

Objective

High-risk pregnancy (HRP) conditions such as gestational diabetes mellitus (GDM), hypertension (HTN), and peripartum depression (PPD) affect maternal and neonatal health. Patient engagement is critical for effective HRP management (HRPM). While digital technologies and analytics hold promise, emerging research indicates limited and suboptimal support offered by the highly prevalent pregnancy digital solutions within the commercial marketplace. In this article, we describe our efforts to develop a portfolio of digital products leveraging advances in social computing, data science, and digital health.

Methods

We describe three studies that leverage core methods from Digilego digital health development framework to (1) conduct large-scale social media analysis (n = 55 301 posts) to understand population-level patterns in women's needs, (2) architect a digital repository to enable women curate HRP related information, and (3) develop a digital platform to support PPD prevention. We applied a combination of qualitative coding, machine learning, theory-mapping, and programmatic implementation of theory-linked digital features. Further, we conducted preliminary testing of the resulting products for acceptance with sample of pregnant women for GDM/HTN information management (n = 10) and PPD prevention (n = 30).

Results

Scalable social computing models using deep learning classifiers with reasonable accuracy have allowed us to capture and examine psychosociobehavioral drivers associated with HRPM. Our work resulted in two digital health solutions, MyPregnancyChart and MomMind are developed. Initial evaluation of both tools indicates positive acceptance from potential end users. Further evaluation with MomMind revealed statistically significant improvements (P < .05) in PPD recognition and knowledge on how to seek PPD information.

Discussion

Digilego framework provides an integrative methodological lens to gain micro-macro perspective on women's needs, theory integration, engagement optimization, as well as subsequent feature and content engineering, which can be organized into core and specialized digital pathways for women engagement in disease management.

Conclusion

Future works should focus on implementation and testing of digital solutions that facilitate women to capture, aggregate, preserve, and utilize, otherwise siloed, prenatal information artifacts for enhanced self-management of their high-risk conditions, ultimately leading to improved health outcomes.

The Goldilocks Dilemma on Balancing User Response and Reflection in mHealth Interventions: Observational Study

Background

Mobile health (mHealth) has the potential to radically improve health behaviors and quality of life; however, there are still key gaps in understanding how to optimize mHealth engagement. Most engagement research reports only on system use without consideration of whether the user is reflecting on the content cognitively. Although interactions with mHealth are critical, cognitive investment may also be important for meaningful behavior change. Notably, content that is designed to request too much reflection could result in users' disengagement. Understanding how to strike the balance between response burden and reflection burden has critical implications for achieving effective engagement to impact intended outcomes.

Objective

In this observational study, we sought to understand the interplay between response burden and reflection burden and how they impact mHealth engagement. Specifically, we explored how varying the response and reflection burdens of mHealth content would impact users' text message response rates in an mHealth intervention.

Methods

We recruited support persons of people with diabetes for a randomized controlled trial that evaluated an mHealth intervention for diabetes management. Support person participants assigned to the intervention (n=148) completed a survey and received text messages for 9 months. During the 2-year randomized controlled trial, we sent 4 versions of a weekly, two-way text message that varied in both reflection burden (level of cognitive reflection requested relative to that of other messages) and response burden (level of information requested for the response relative to that of other messages). We quantified engagement by using participant-level response rates. We compared the odds of responding to each text and used Poisson regression to estimate associations between participant characteristics and response rates.

Results

The texts requesting the most reflection had the lowest response rates regardless of response burden (high reflection and low response burdens: median 10%, IQR 0%-40%; high reflection and high response burdens: median 23%, IQR 0%-51%). The response rate was highest for the text requesting the least reflection (low reflection and low response burdens: median 90%, IQR 61%-100%) yet still relatively high for the text requesting medium reflection (medium reflection and low response burdens: median 75%, IQR 38%-96%). Lower odds of responding were associated with higher reflection burden (P<.001). Younger participants and participants who had a lower socioeconomic status had lower response rates to texts with more reflection burden, relative to those of their counterparts (all P values were <.05).

Conclusions

As reflection burden increased, engagement decreased, and we found more disparities in engagement across participants' characteristics. Content encouraging moderate levels of reflection may be ideal for achieving both cognitive investment and system use. Our findings provide insights into mHealth design and the optimization of both engagement and effectiveness.

The Report of Access and Engagement With Digital Health Interventions Among Children and Young People: Systematic Review

BACKGROUND

Digital health interventions are increasingly used to deliver health-related interventions for children and young people to change health behaviors and improve health outcomes. Digital health interventions have the potential to enhance access to and engagement with children and young people; however, they may also increase the divide between those who can access technology and are supported to engage and those who are not. This review included studies that reported on the access to or engagement with digital health interventions among children and young people.

OBJECTIVE

This review aims to identify and report on access and engagement in studies involving digital health interventions among children and young people.

METHODS

A systematic review following the Joanna Briggs Institute methods for conducting systematic reviews was conducted. An electronic literature search was conducted for all studies published between January 1, 2010, and August 2022, across sources, including MEDLINE, CINAHL, and PsycINFO. Studies were included if they examined any aspect of access or engagement in relation to interventions among children and young people. The quality of the included papers was assessed, and data were extracted. Data were considered for meta-analysis, where possible.

RESULTS

A total of 3292 references were identified using search terms. Following the exclusion of duplicates and review by inclusion criteria, 40 studies were independently appraised for their methodological quality. A total of 16 studies were excluded owing to their low assessed quality and flawed critical elements in the study design. The studies focused on a variety of health conditions; type 1 diabetes, weight management and obesity, mental health issues, and sexual health were the predominant conditions. Most studies were conducted in developed countries, with most of them being conducted in the United States. Two studies reported data related to access and considered ethnicity and social determinants. No studies used strategies to enhance or increase access. All studies included in the review reported on at least 1 aspect of engagement. Engagement with interventions was measured in relation to frequency of engagement, with no reference to the concept of effective engagement.

CONCLUSIONS

Most digital health interventions do not consider the factors that can affect access and engagement. Of those studies that measured either access or engagement or both, few sought to implement strategies to improve access or engagement to address potential disparities between groups. Although the literature to date provides some insight into access and engagement and how these are addressed in digital health interventions, there are major limitations in understanding how both can be enhanced to promote equity. Consideration of both access and engagement is vital to ensure that children and young people have the ability to participate in studies.

TRIAL REGISTRATION

PROSPERO CRD42020170874; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=170874.

The Effectiveness of Strategies to Improve User Engagement With Digital Health Interventions Targeting Nutrition, Physical Activity, and Overweight and Obesity: Systematic Review and Meta-Analysis

BACKGROUND

Digital health interventions (DHIs) are effective in improving poor nutrition, physical inactivity, overweight and obesity. There is evidence suggesting that the impact of DHIs may be enhanced by improving user engagement. However, little is known about the overall effectiveness of strategies on engagement with DHIs.

OBJECTIVE

This study aims to assess the overall effectiveness of strategies to improve engagement with DHIs targeting nutrition, physical activity, and overweight or obesity and explore associations between strategies and engagement outcomes. The secondary aim was to explore the impact of these strategies on health risk outcomes.

METHODS

The MEDLINE, Embase, PsycINFO, CINAHL, CENTRAL, Scopus, and Academic Source Complete databases were searched up to July 24, 2023. Eligible studies were randomized controlled trials that evaluated strategies to improve engagement with DHIs and reported on outcomes related to DHI engagement (use or user experience). Strategies were classified according to behavior change techniques (BCTs) and design features (eg, supplementary emails). Multiple-variable meta-analyses of the primary outcomes (usage and user experience) were undertaken to assess the overall effectiveness of strategies. Meta-regressions were conducted to assess associations between strategies and use and user experience outcomes. Synthesis of secondary outcomes followed the "Synthesis Without Meta-Analysis" guidelines. The methodological quality and evidence was assessed using the Cochrane risk-of-bias tool, and the Grading of Recommendations Assessment, Development, and Evaluation tool respectively.

RESULTS

Overall, 54 studies (across 62 publications) were included. Pooled analysis found very low-certainty evidence of a small-to-moderate positive effect of the use of strategies to improve DHI use (standardized mean difference=0.33, 95% CI 0.20-0.46; P<.001) and very low-certainty evidence of a small-to-moderate positive effect on user experience (standardized mean difference=0.29, 95% CI 0.07-0.52; P=.01). A significant positive association was found between the BCTs social support (effect size [ES]=0.40, 95% CI 0.14-0.66; P<.001) and shaping knowledge (ES=0.39, 95% CI 0.03-0.74; P=.03) and DHI use. A significant positive association was found among the BCTs social support (ES=0.70, 95% CI 0.18-1.22; P=.01), repetition and substitution (ES=0.29, 95% CI 0.05-0.53; P=.03), and natural consequences (ES=0.29, 95% CI 0.05-0.53; P=.02); the design features email (ES=0.29, 95% CI 0.05-0.53; P=.02) and SMS text messages (ES=0.34, 95% CI 0.11-0.57; P=.01); and DHI user experience. For secondary outcomes, 47% (7/15) of nutrition-related, 73% (24/33) of physical activity-related, and 41% (14/34) of overweight- and obesity-related outcomes reported an improvement in health outcomes.

CONCLUSIONS

Although findings suggest that the use of strategies may improve engagement with DHIs targeting such health outcomes, the true effect is unknown because of the low quality of evidence. Future research exploring whether specific forms of social support, repetition and substitution, natural consequences, emails, and SMS text messages have a greater impact on DHI engagement is warranted.

TRIAL REGISTRATION

PROSPERO CRD42018077333; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=77333.

Design and Early Use of the Nationally Implemented Healthier You National Health Service Digital Diabetes Prevention Programme: Mixed Methods Study

BACKGROUND

The Healthier You National Health Service Digital Diabetes Prevention Programme (NHS-digital-DPP) is a 9-month digital behavior change intervention delivered by 4 independent providers that is implemented nationally across England. No studies have explored the design features included by service providers of digital diabetes prevention programs to promote engagement, and little is known about how participants of nationally implemented digital diabetes prevention programs such as this one make use of them.

OBJECTIVE

This study aimed to understand engagement with the NHS-digital-DPP. The specific objectives were to describe how engagement with the NHS-digital-DPP is promoted via design features and strategies and describe participants' early engagement with the NHS-digital-DPP apps.

METHODS

Mixed methods were used. The qualitative study was a secondary analysis of documents detailing the NHS-digital-DPP intervention design and interviews with program developers (n=6). Data were deductively coded according to an established framework of engagement with digital health interventions. For the quantitative study, anonymous use data collected over 9 months for each provider representing participants' first 30 days of use of the apps were obtained for participants enrolled in the NHS-digital-DPP. Use data fields were categorized into 4 intervention features (Track, Learn, Coach Interactions, and Peer Support). The amount of engagement with the intervention features was calculated for the entire cohort, and the differences between providers were explored statistically.

RESULTS

Data were available for 12,857 participants who enrolled in the NHS-digital-DPP during the data collection phase. Overall, 94.37% (12,133/12,857) of those enrolled engaged with the apps in the first 30 days. The median (IQR) number of days of use was 11 (2-25). Track features were engaged with the most (number of tracking events: median 46, IQR 3-22), and Peer Support features were the least engaged with, a median value of 0 (IQR 0-0). Differences in engagement with features were observed across providers. Qualitative findings offer explanations for the variations, including suggesting the importance of health coaches, reminders, and regular content updates to facilitate early engagement.

CONCLUSIONS

Almost all participants in the NHS-digital-DPP started using the apps. Differences across providers identified by the mixed methods analysis provide the opportunity to identify features that are important for engagement with digital health interventions and could inform the design of other digital behavior change interventions.

Participants' and Health Care Providers' Insights Regarding a Web-Based and Mobile-Delivered Healthy Eating Program for Disadvantaged People With Type 2 Diabetes: Descriptive Qualitative Study

BACKGROUND

Healthy eating is a key element of type 2 diabetes (T2D) self-management. Digital interventions offer new avenues to reach broad audiences to promote healthy eating behaviors. However, acceptance of these interventions by socioeconomically disadvantaged people (eg, those with lower levels of education and income or from ethnic minority groups) has not yet been fully evaluated.

OBJECTIVE

This study aimed to investigate the acceptability and usability of EatSmart, a 12-week web-based and mobile-delivered healthy eating behavior change support program, from the perspective of intervention participants living with T2D and health care providers (HCPs) involved in diabetes care.

METHODS

This study used a qualitative descriptive design. Overall, 60 disadvantaged adults with T2D, as determined by receipt of either a HealthCare Card or a pension or benefit as the main source of income, were recruited. Data from participants regarding their experiences with and perceptions of the program and longer-term maintenance of any behavior or attitudinal changes were collected through a web-based self-report survey with open-ended questions administered 12 weeks after baseline (54/60, 90%) and semistructured telephone interviews administered 36 weeks after baseline (16/60, 27%). Supplementary semistructured interviews with 6 HCPs involved in diabetes care (endocrinologists, accredited practicing dietitians, and diabetes nurse educators) were also conducted 36 weeks after baseline. These interviews aimed to understand HCPs' views on successful and unsuccessful elements of EatSmart as a technology-delivered intervention; any concerns or barriers regarding the use of these types of interventions; and feedback from their interactions with patients on the intervention's content, impact, or observed benefits. All data from the surveys and interviews were pooled and thematically analyzed.

RESULTS

In total, 5 key themes emerged from the data: program impact on food-related behaviors and routines, satisfaction with the program, reasons for low engagement and suggestions for future programs, benefits and challenges of digital interventions, and cultural considerations. Results showed that EatSmart was acceptable to participants and contributed positively to improving food-related behaviors. Most participants (27/43, 63%) mentioned that they enjoyed their experience with EatSmart and expressed high satisfaction with its content and delivery. The educational and motivational content was considered the most useful part of the program. Benefits discussed by intervention participants included gaining health knowledge and skills, positive changes in their food purchasing and cooking, and eating greater quantities and varieties of fruits and vegetables. HCPs also described the intervention as beneficial and persuasive for the target audience and had specific suggestions for future tailoring of such programs.

CONCLUSIONS

The findings suggested that this digitally delivered intervention with supportive educational modules and SMS text messages was generally appealing for both participants and HCPs. This intervention medium shows promise and could feasibly be rolled out on a broader scale to augment usual diabetes care.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/19488.

Exploring engagement with a web-based dietary intervention for adults with type 2 diabetes: A mixed methods evaluation of the T2Diet study

BACKGROUND

Improved understanding of participant engagement in web-based dietary interventions is needed. Engagement is a complex construct that may be best explored through mixed methods to gain comprehensive insight. To our knowledge, no web-based dietary intervention in people with type 2 diabetes (T2D) has previously used a mixed methods approach. The aim of this study was to explore factors that may contribute to effective engagement in a web-based dietary program for people with T2D.

METHODS

This study employed a mixed methods intervention design, with a convergent design embedded for post-intervention evaluation. The convergent design collected and analyzed quantitative and qualitative data independent of each other, with the two datasets merged/compared during results/interpretation. Quantitative data collected from intervention group participants (n = 40) were self-administered questionnaires and usage data with average values summarized. Qualitative data were participant semi-structured interviews (n = 15) incorporating a deductive-inductive thematic analysis approach.

RESULTS

The results from the quantitative and qualitative data indicated positive overall engagement with the web-based dietary program. Factors that contributed to effective engagement were sustained frequency and intensity of engagement; structured weekly program delivery; participants affective engagement prior to and during the intervention, with positive affective states enhancing cognitive and behavioral engagement; and participants experience of value and reward. In addition, the user-centered development process employed prior to intervention delivery played an important role in facilitating positive engagement outcomes.

CONCLUSION

This study yielded novel findings by integrating qualitative and quantitative data to explore engagement with a web-based dietary program involving people with T2D. Effective engagement occurred in this intervention through a combination of factors related to usage and participants' affective, cognitive and behavioral states. The engagement outcomes that emerged will be useful to current and future researchers using digital technologies to deliver lifestyle interventions for T2D or other chronic health conditions.

Can behavior change techniques be delivered via short text messages?

Despite significant advancements in behavioral science it is unclear whether behavior change techniques (or BCTs) can be delivered to large numbers of people in a cost-effective and reliable way. The current study investigated whether it is possible to reliably deliver BCTs using short text messages. Short text messages were designed to deliver each of the 93 BCTs specified in the BCT taxonomy v1. Following initial coding and refinement by the team, a Delphi study with a panel of 15 experts coded which BCT each short text message was designed to deliver and also rated whether they were likely to be understood by recipients and easily converted to target different behaviors. After two iterations, the experts correctly assigned 66 of the 93 messages to the BCT that they were designed to deliver and indicated that these messages were likely to be easy to apply to a range of behaviors and understood by recipients. Experts were not able to identify which BCT 27 of the messages were designed to deliver and it was notable that some clusters of BCTs (e.g., "Goals and planning") were easier to deliver via short text messages than other clusters (e.g., "Scheduled consequences"). The findings suggest that short text messages can be a reliable way to deliver many, but not all, BCTs. The implications of the current study are discussed with respect to the delivery of specific BCTs and clusters of the taxonomy, as well as the need to test the acceptability of interventions delivered via short messages and the impact of messages on behavior.

Web-Based Structured Education for Type 2 Diabetes: Interdisciplinary User-Centered Design Approach

BACKGROUND

Digital health research encompasses methods from human-computer interaction and health research.

OBJECTIVE

This paper aims to describe how these methods were combined to develop HeLP-Diabetes: Starting Out, a web-based structured education program for people newly diagnosed with type 2 diabetes.

METHODS

The development process consisted of three phases: initial design for effectiveness, optimization for usability, and in the wild testing in the National Health Service with people newly diagnosed with type 2 diabetes, and further revisions. We adopted an iterative user-centered approach and followed steps from the human-computer interaction design life cycle and the Medical Research Council guidelines on developing and evaluating complex interventions.

RESULTS

The initial design process resulted in an 8-session program containing information and behavior change techniques targeting weight loss, being more active, and taking medication. The usability testing was highlighted at an early stage, where changes needed to be made to the language and layout of the program. The in the wild testing provided data on uptake of and barriers to use. The study suggested low uptake and completion of the program, but those who used it seemed to benefit from it. The qualitative findings suggested that barriers to use included an expectation that the program would take too long. This informed refinements to the program.

CONCLUSIONS

The use of interdisciplinary methods resulted in an iterative development process and refinements to the program that were based on user needs and data on uptake. The final intervention was more suitable for a definitive evaluation than the initial version. The description of our approach informs other digital health researchers on how to make interventions more sensitive to user needs.

Engagement in Digital Mental Health Interventions: Can Monetary Incentives Help?

Digital mental health interventions (DMHI) are scalable and cost-effective strategies for increasing access to mental health care; however, dropout rates associated with digital interventions are high, particularly for open-access digital interventions. While some studies have focused on predictors of dropout from digital mental health programs, few studies have focused on engagement features that might improve engagement. In this perspective article, we discuss whether monetary incentives (MI) are one avenue to increasing user engagement in DMHI. We begin by reviewing the literature on the effects of MI for behavior change in health domains (e.g., dietary behaviors, substance use, and medication adherence). Then, drawing on a pilot study we conducted to test the effects of different levels of MI on usage and improvement in subjective well-being among users of a DMHI (Happify), we discuss the potential applications of MI for DMHI, the potential drawbacks of financial incentives in this context, and open questions for future research.

Text Message Analysis Using Machine Learning to Assess Predictors of Engagement With Mobile Health Chronic Disease Prevention Programs: Content Analysis

BACKGROUND

SMS text messages as a form of mobile health are increasingly being used to support individuals with chronic diseases in novel ways that leverage the mobility and capabilities of mobile phones. However, there are knowledge gaps in mobile health, including how to maximize engagement.

OBJECTIVE

This study aims to categorize program SMS text messages and participant replies using machine learning (ML) and to examine whether message characteristics are associated with premature program stopping and engagement.

METHODS

We assessed communication logs from SMS text message-based chronic disease prevention studies that encouraged 1-way (SupportMe/ITM) and 2-way (TEXTMEDS [Text Messages to Improve Medication Adherence and Secondary Prevention]) communication. Outgoing messages were manually categorized into 5 message intents (informative, instructional, motivational, supportive, and notification) and replies into 7 groups (stop, thanks, questions, reporting healthy, reporting struggle, general comment, and other). Grid search with 10-fold cross-validation was implemented to identify the best-performing ML models and evaluated using nested cross-validation. Regression models with interaction terms were used to compare the association of message intent with premature program stopping and engagement (replied at least 3 times and did not prematurely stop) in SupportMe/ITM and TEXTMEDS.

RESULTS

We analyzed 1550 messages and 4071 participant replies. Approximately 5.49% (145/2642) of participants responded with stop, and 11.7% (309/2642) of participants were engaged. Our optimal ML model correctly classified program message intent with 76.6% (95% CI 63.5%-89.8%) and replies with 77.8% (95% CI 74.1%-81.4%) balanced accuracy (average area under the curve was 0.95 and 0.96, respectively). Overall, supportive (odds ratio [OR] 0.53, 95% CI 0.35-0.81) messages were associated with reduced chance of stopping, as were informative messages in SupportMe/ITM (OR 0.35, 95% CI 0.20-0.60) but not in TEXTMEDS (for interaction, P<.001). Notification messages were associated with a higher chance of stopping in SupportMe/ITM (OR 5.76, 95% CI 3.66-9.06) but not TEXTMEDS (for interaction, P=.01). Overall, informative (OR 1.76, 95% CI 1.46-2.12) and instructional (OR 1.47, 95% CI 1.21-1.80) messages were associated with higher engagement but not motivational messages (OR 1.18, 95% CI 0.82-1.70; P=.37). For supportive messages, the association with engagement was opposite with SupportMe/ITM (OR 1.77, 95% CI 1.21-2.58) compared with TEXTMEDS (OR 0.77, 95% CI 0.60-0.98; for interaction, P<.001). Notification messages were associated with reduced engagement in SupportMe/ITM (OR 0.07, 95% CI 0.05-0.10) and TEXTMEDS (OR 0.28, 95% CI 0.20-0.39); however, the strength of the association was greater in SupportMe/ITM (for interaction P<.001).

CONCLUSIONS

ML models enable monitoring and detailed characterization of program messages and participant replies. Outgoing message intent may influence premature program stopping and engagement, although the strength and direction of association appear to vary by program type. Future studies will need to examine whether modifying message characteristics can optimize engagement and whether this leads to behavior change.

Reducing sedentary time using an innovative mHealth intervention among patients with total knee replacement: Rationale and study protocol

INTRODUCTION

Although knee replacement is effective for improving pain and physical function, subsequent improvements in physical activity typically do not follow. As a result, many patients spend most of their day engaged in sedentary behavior, which may put them at higher risk of experiencing poor function and disability. Intervening on sedentary time, rather than physical activity, may be a more feasible first-step approach for modifying activity-related behaviors in adults who received knee replacement.

OBJECTIVE

The purpose of this study is to examine the use of a mobile health (mHealth) intervention to reduce sedentary time among adults who received a knee replacement at 3 and 6 months after surgery.

METHODS

Patients (n = 92) scheduled for knee replacement will be recruited and at 4 weeks after surgery, they will be randomized to either NEAT!2 or Control. NEAT!2 participants will use the NEAT!2 smartphone app, which provides a vibration and/or audible tone to interrupt prolonged bouts of sitting detected from the smartphone's internal accelerometer, until 3 months after surgery. NEAT!2 participants will receive biweekly coaching calls between 4 and 12 weeks after surgery. Control participants will receive an education control app and receive non-intervention calls to assess general surgery recovery. Both groups will receive 3 retention calls between 3 and 6 months. Data collection will occur pre-operatively and at 3 and 6 months after surgery.

DISCUSSION

The results of this study will help to determine whether an innovative remotely-delivered, mHealth sedentary reduction intervention can decrease sedentary time in adults after knee replacement.

Evaluating Glycemic Control in Patients of South Asian Origin With Type 2 Diabetes Using a Digital Therapeutic Platform: Analysis of Real-World Data

Background

Digital therapeutics are evidence-based therapeutic interventions driven by high-quality software programs for the treatment, prevention, or management of a medical disorder or disease. Many studies in the western population have shown the effectiveness of mobile app–based digital therapeutics for improving glycemic control in patients with type 2 diabetes (T2D). However, few studies have assessed similar outcomes in the South Asian population.

Objective

This study aims to investigate the real-world effectiveness of the Wellthy CARE digital therapeutic for improving glycemic control among the South Asian population of Indian origin.

Methods

We analyzed deidentified data from 102 patients with T2D from India enrolled in a 16-week structured self-management program delivered using the Wellthy CARE mobile app. Patients recorded their meals, weight, physical activity, and blood sugar in the app, and they received lessons on self-care behaviors (healthy eating, being active, monitoring, medication adherence, problem solving, healthy coping, and reducing risks); feedback provided by an artificial intelligence–powered chatbot; and periodic interactions with certified diabetes educators via voice calls and chats. The primary outcome of the program was a change in glycated hemoglobin A_1c (HbA_1c). Secondary outcomes included the difference between preintervention and postintervention fasting blood glucose (FBG) and postprandial blood glucose (PPBG) levels; changes in BMI and weight at the completion of 16 weeks; and the association between program engagement and the changes in HbA_1c, FBG, and PPBG levels.

Results

At the end of 16 weeks, the average change in HbA_1c was –0.49% (n=102; 95% CI −0.73 to 0.25; P<.001). Of all the patients, 63.7% (65/102) had improved HbA_1c levels, with a mean change of −1.16% (n=65; 95% CI −1.40 to −0.92; P<.001). The mean preintervention and postintervention FBG levels were 145 mg/dL (n=51; 95% CI 135-155) and 134 mg/dL (n=51; 95% CI 122-146; P=.02) and PPBG levels were 188 mg/dL (n=51; 95% CI 172-203) and 166 mg/dL (n=51; 95% CI 153-180; P=.03), respectively. The mean changes in BMI and weight were –0.47 kg/m² (n=59; 95% CI −0.22 to −0.71; P<.001) and –1.32 kg (n=59; 95% CI −0.63 to −2.01; P<.001), respectively. There was a stepwise decrease in HbA_1c, FBG, and PPBG levels as the program engagement increased. Patients in the highest tertile of program engagement had a significantly higher reduction in HbA_1c (−0.84% vs −0.06%; P=.02), FBG (−21.4 mg/dL vs −0.18 mg/dL; P=.02), and PPBG levels (−22.03 mg/dL vs 2.35 mg/dL; P=.002) than those in the lowest tertile.

Conclusions

The use of the Wellthy CARE digital therapeutic for patients with T2D showed a significant reduction in the levels of HbA_1c, FBG, and PPBG after 16 weeks. A higher level of participation showed improved glycemic control, suggesting the potential of the Wellthy CARE platform for better management of the disease.

Exploring Beliefs and Preferences for Reducing Sedentary Behavior Among Adults With Symptomatic Knee Osteoarthritis or Knee Replacement

Objective

Physical activity has numerous benefits for those with symptomatic knee osteoarthritis (KOA) or knee replacement, yet many individuals engage in insufficient activity. The purpose of this study was to explore beliefs about sedentary behavior, barriers to standing, and program preferences for adults with symptomatic KOA or knee replacement.

Methods

Forty‐two individuals ≥50 years with symptomatic KOA or knee replacement completed an online survey assessing current knee pain and function, sitting time, physical activity participation, beliefs about sedentary behavior, and preferences for a sedentary reduction program.

Results

Participants indicated barriers to standing were pain, discomfort, or working on a computer. Most participants shared interest to participate in a program to reduce sitting time. Participants chose education, self‐monitoring, and activity tracking as most preferable components for an intervention design.

Conclusion

Future interventions to reduce sedentary time may utilize these results to tailor programs for those with symptomatic KOA or knee replacement.

Toward a Digital Platform for the Self-Management of Noncommunicable Disease: Systematic Review of Platform-Like Interventions

BACKGROUND

Digital interventions are effective for health behavior change, as they enable the self-management of chronic, noncommunicable diseases (NCDs). However, they often fail to facilitate the specific or current needs and preferences of the individual. A proposed alternative is a digital platform that hosts a suite of discrete, already existing digital health interventions. A platform architecture would allow users to explore a range of evidence-based solutions over time to optimize their self-management and health behavior change.

OBJECTIVE

This review aims to identify digital platform-like interventions and examine their potential for supporting self-management of NCDs and health behavior change.

METHODS

A literature search was conducted in January 2020 using EBSCOhost, PubMed, Scopus, and EMBASE. No digital platforms were identified, so criteria were broadened to include digital platform-like interventions. Eligible platform-like interventions offered a suite of discrete, evidence-based health behavior change features to optimize self-management of NCDs in an adult population and provided digitally supported guidance for the user toward the features best suited to their needs and preferences. Data collected on interventions were guided by the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and Online Telehealth) checklist, including evaluation data on effectiveness and process outcomes. The quality of the included literature was assessed using the Mixed Methods Appraisal Tool.

RESULTS

A total of 7 studies were included for review. Targeted NCDs included cardiovascular diseases (CVD; n=3), diabetes (n=3), and chronic obstructive pulmonary disease (n=1). The mean adherence (based on the number of follow-up responders) was 69% (SD 20%). Of the 7 studies, 4 with the highest adherence rates (80%) were also guided by behavior change theories and took an iterative, user-centered approach to development, optimizing intervention relevance. All 7 interventions presented algorithm-supported user guidance tools, including electronic decision support, smart features that interact with patterns of use, and behavior change stage-matching tools. Of the 7 studies, 6 assessed changes in behavior. Significant effects in moderate-to-vigorous physical activity were reported, but for no other specific health behaviors. However, positive behavior change was observed in studies that focused on comprehensive behavior change measures, such as self-care and self-management, each of which addresses several key lifestyle risk factors (eg, medication adherence). No significant difference was found for psychosocial outcomes (eg, quality of life). Significant changes in clinical outcomes were predominately related to disease-specific, multifaceted measures such as clinical disease control and cardiovascular risk score.

CONCLUSIONS

Iterative, user-centered development of digital platform structures could optimize user engagement with self-management support through existing, evidence-based digital interventions. Offering a palette of interventions with an appropriate degree of guidance has the potential to facilitate disease-specific health behavior change and effective self-management among a myriad of users, conditions, or stages of care.

Adherence to Electronic Health Tools Among Vulnerable Groups: Systematic Literature Review and Meta-Analysis

Background

Electronic health (eHealth) tools are increasingly being applied in health care. They are expected to improve access to health care, quality of health care, and health outcomes. Although the advantages of using these tools in health care are well described, it is unknown to what extent eHealth tools are effective when used by vulnerable population groups, such as the elderly, people with low socioeconomic status, single parents, minorities, or immigrants.

Objective

This study aimed to examine whether the design and implementation characteristics of eHealth tools contribute to better use of these tools among vulnerable groups.

Methods

In this systematic review, we assessed the design and implementation characteristics of eHealth tools that are used by vulnerable groups. In the meta-analysis, we used the adherence rate as an effect size measure. The adherence rate is defined as the number of people who are repetitive users (ie, use the eHealth tool more than once). We also performed a meta-regression analysis to examine how different design and implementation characteristics influenced the adherence rate.

Results

Currently, eHealth tools are continuously used by vulnerable groups but to a small extent. eHealth tools that use multimodal content (such as videos) and have the possibility for direct communication with providers show improved adherence among vulnerable groups.

Conclusions

eHealth tools that use multimodal content and provide the possibility for direct communication with providers have a higher adherence among vulnerable groups. However, most of the eHealth tools are not embedded within the health care system. They are usually focused on specific problems, such as diabetes or obesity. Hence, they do not provide comprehensive services for patients. This limits the use of eHealth tools as a replacement for existing health care services.

A digital self-management intervention for adults with type 2 diabetes: Combining theory, data and participatory design to develop HeLP-Diabetes

BACKGROUND

Digital health interventions have potential to contribute to better health outcomes, better healthcare and lower costs. However, evidence for their effectiveness is variable. The development and content of digital health interventions are often not described in enough detail to enable others to replicate the research or improve on previous interventions. This has led to a call for transparent reporting of intervention content and development.

PURPOSE

To describe the development process and content of a digital self-management intervention for people with type 2 diabetes (HeLP-Diabetes) that has been found to achieve its target clinical outcome, the reduction of HbA1c, a measure of glycaemic control.

METHOD

We synthesised theory, data from existing research evidence and international guidelines, and new qualitative data from target users to identify the determinants of self-management and the content to be included in HeLP-Diabetes. Using an ongoing iterative participatory design approach the content of the intervention was written, produced, reviewed and changed.

CONCLUSION

It is possible to develop and transparently report self-management programmes for long-term conditions, which reflect current best evidence, theoretical underpinning and user involvement. We intend that reporting the development process and content will inform future digital intervention development.

Measuring Engagement in eHealth and mHealth Behavior Change Interventions: Viewpoint of Methodologies

Engagement in electronic health (eHealth) and mobile health (mHealth) behavior change interventions is thought to be important for intervention effectiveness, though what constitutes engagement and how it enhances efficacy has been somewhat unclear in the literature. Recently published detailed definitions and conceptual models of engagement have helped to build consensus around a definition of engagement and improve our understanding of how engagement may influence effectiveness. This work has helped to establish a clearer research agenda. However, to test the hypotheses generated by the conceptual modules, we need to know how to measure engagement in a valid and reliable way. The aim of this viewpoint is to provide an overview of engagement measurement options that can be employed in eHealth and mHealth behavior change intervention evaluations, discuss methodological considerations, and provide direction for future research. To identify measures, we used snowball sampling, starting from systematic reviews of engagement research as well as those utilized in studies known to the authors. A wide range of methods to measure engagement were identified, including qualitative measures, self-report questionnaires, ecological momentary assessments, system usage data, sensor data, social media data, and psychophysiological measures. Each measurement method is appraised and examples are provided to illustrate possible use in eHealth and mHealth behavior change research. Recommendations for future research are provided, based on the limitations of current methods and the heavy reliance on system usage data as the sole assessment of engagement. The validation and adoption of a wider range of engagement measurements and their thoughtful application to the study of engagement are encouraged.

Insights From a Text Messaging-Based Sexual and Reproductive Health Information Program in Tanzania (m4RH): Retrospective Analysis

BACKGROUND

Many mobile health (mHealth) interventions have the potential to generate and store vast amounts of system-generated participant interaction data that could provide insight into user engagement, programmatic strengths, and areas that need improvement to maximize efficacy. However, despite the popularity of mHealth interventions, there is little documentation on how to use these data to monitor and improve programming or to evaluate impact.

OBJECTIVE

This study aimed to better understand how users of the Mobile for Reproductive Health (m4RH) mHealth intervention engaged with the program in Tanzania from September 2013 to August 2016.

METHODS

We conducted secondary data analysis of longitudinal data captured by system logs of participant interactions with the m4RH program from 127 districts in Tanzania from September 2013 to August 2016. Data cleaning and analysis was conducted using Stata 13. The data were examined for completeness and "correctness." No missing data was imputed; respondents with missing or incorrect values were dropped from the analyses.

RESULTS

The total population for analysis included 3,673,702 queries among 409,768 unique visitors. New users represented roughly 11.15% (409,768/3,673,702) of all queries. Among all system queries for new users, 46.10% (188,904/409,768) users accessed the m4RH main menu. Among these users, 89.58% (169,218/188,904) accessed specific m4RH content on family planning, contraceptive methods, adolescent-specific and youth-specific information, and clinic locations after first accessing the m4RH main menu. The majority of these users (216,422/409,768, 52.82%) requested information on contraceptive methods; fewer users (23,236/409,768, 5.67%) requested information on clinic location. The conversion rate was highest during the first and second years of the program when nearly all users (11,246/11,470, 98.05%, and 33,551/34,830, 96.33%, respectively) who accessed m4RH continued on to query more specific content from the system. The rate of users that accessed m4RH and became active users declined slightly from 98.05% (11,246/11,470) in 2013 to 87.54% (56,696/64,765) in 2016. Overall, slightly more than one-third of all new users accessing m4RH sent queries at least once per month for 2 or more months, and 67.86% (278,088/409,768) of new and returning users requested information multiple times per month. Promotional periods were present for 15 of 36 months during the study period.

CONCLUSIONS

The analysis of the rich data captured provides a useful framework with which to measure the degree and nature of user engagement utilizing routine system-generated data. It also contributes to knowledge of how users engage with text messaging (short message service)-based health promotion interventions and demonstrates how data generated on user interactions could inform improvements to the design and delivery of a service, thereby enhancing its effectiveness.

A web-based self-management programme for people with type 2 diabetes: the HeLP-Diabetes research programme including RCT

Background

In the UK, 6% of the UK population have diabetes mellitus, 90% of whom have type 2 diabetes mellitus (T2DM). Diabetes mellitus accounts for 10% of NHS expenditure (£14B annually). Good self-management may improve health outcomes. NHS policy is to refer all people with T2DM to structured education, on diagnosis, to improve their self-management skills, with annual reinforcement thereafter. However, uptake remains low (5.6% in 2014–15). Almost all structured education is group based, which may not suit people who work, who have family or other caring commitments or who simply do not like group-based formats. Moreover, patient needs vary with time and a single education session at diagnosis is unlikely to meet these evolving needs. A web-based programme may increase uptake.

Objectives

Our aim was to develop, evaluate and implement a web-based self-management programme for people with T2DM at any stage of their illness journey, with the goal of improving access to, and uptake of, self-management support, thereby improving health outcomes in a cost-effective manner. Specific objectives were to (1) develop an evidence-based theoretically informed programme that was acceptable to patients and health-care professionals (HCPs) and that could be readily implemented within routine NHS care, (2) determine the clinical effectiveness and cost-effectiveness of the programme compared with usual care and (3) determine how best to integrate the programme into routine care.

Design

There were five linked work packages (WPs). WP A determined patient requirements and WP B determined HCP requirements for the self-management programme. WP C developed and user-tested the Healthy Living for People with type 2 Diabetes (HeLP-Diabetes) programme. WP D was an individually randomised controlled trial in primary care with a health economic analysis. WP E used a mixed-methods and case-study design to study the potential for implementing the HeLP-Diabetes programme within routine NHS practice.

Setting

English primary care.

Participants

People with T2DM (WPs A, D and E) or HCPs caring for people with T2DM (WPs B, C and E).

Intervention

The HeLP-Diabetes programme; an evidence-based theoretically informed web-based self-management programme for people with T2DM at all stages of their illness journey, developed using participatory design principles.

Main outcome measures

WPs A and B provided data on user ‘wants and needs’, including factors that would improve the uptake and accessibility of the HeLP-Diabetes programme. The outcome for WP C was the HeLP-Diabetes programme itself. The trial (WP D) had two outcomes measures: glycated haemoglobin (HbA1c) level and diabetes mellitus-related distress, as measured with the Problem Areas in Diabetes (PAID) scale. The implementation outcomes (WP E) were the adoption and uptake at clinical commissioning group, general practice and patient levels and the identification of key barriers and facilitators.

Results

Data from WPs A and B supported our holistic approach and addressed all areas of self-management (medical, emotional and role management). HCPs voiced concerns about linkage with the electronic medical records (EMRs) and supporting patients to use the programme. The HeLP-Diabetes programme was developed and user-tested in WP C. The trial (WP D) recruited to target (n = 374), achieved follow-up rates of over 80% and the intention-to-treat analysis showed that there was an additional improvement in HbA1c levels at 12 months in the intervention group [mean difference –0.24%, 95% confidence interval (CI) –0.44% to –0.049%]. There was no difference in overall PAID score levels (mean difference –1.5 points, 95% CI –3.9 to 0.9 points). The within-trial health economic analysis found that incremental costs were lower in the intervention group than in the control group (mean difference –£111, 95% CI –£384 to £136) and the quality-adjusted life-years (QALYs) were higher (mean difference 0.02 QALYs, 95% CI 0.000 to 0.044 QALYs), meaning that the HeLP-Diabetes programme group dominated the control group. In WP E, we found that the HeLP-Diabetes programme could be successfully implemented in primary care. General practices that supported people in registering for the HeLP-Diabetes programme had better uptake and registered patients from a wider demographic than those relying on patient self-registration. Some HCPs were reluctant to do this, as they did not see it as part of their professional role.

Limitations

We were unable to link the HeLP-Diabetes programme with the EMRs or to determine the effects of the HeLP-Diabetes programme on users in the implementation study.

Conclusions

The HeLP-Diabetes programme is an effective self-management support programme that is implementable in primary care.

Future work

The HeLP-Diabetes research team will explore the following in future work: research to determine how to improve patient uptake of self-management support; develop and evaluate a structured digital educational pathway for newly diagnosed people; develop and evaluate a digital T2DM prevention programme; and the national implementation of the HeLP-Diabetes programme.

Trial registration

Research Ethics Committee reference number 10/H0722/86 for WPs A–C; Research Ethics Committee reference number 12/LO/1571 and UK Clinical Research Network/National Institute for Health Research (NIHR) Portfolio 13563 for WP D; and Research Ethics Committee 13/EM/0033 for WP E. In addition, for WP D, the study was registered with the International Standard Randomised Controlled Trial Register as reference number ISRCTN02123133.

Funding details

This project was funded by the NIHR Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 6, No. 5. See the NIHR Journals Library website for further project information.

If we build it, will they come? Issues of engagement with digital health interventions for trauma recovery

Exposure to traumatic events is extremely common with nearly 75% reported to have experienced one or more traumatic events worldwide. A significant number of those exposed will develop posttraumatic stress disorder (PTSD) along with depression, anxiety, and substance use disorders. Globally, trauma-related mental health disorders are the leading cause of global disability burden, and many of these disorders are caused, or worsened, by exposure to wars, natural and human-caused disasters, and other traumatic events. Significant barriers to treatment exist including logistical, geographical, financial, stigma, and other attitudinal challenges. One opportune approach to overcoming these barriers is the provision of mental health interventions via technology that can be readily standardized for wide dissemination of evidence-based care. However, engagement with technology-based interventions is a concern and limited participation and high attrition rates are common. This may be especially true for trauma survivors who often experience symptoms of avoidance and hyperarousal. Engagement is regarded as an essential component of intervention efficacy and has been demonstrated to be associated with more positive clinical outcomes, yet theoretically based research in this area is sparse. This review focuses on the complex issue of engagement with digital health interventions (DHIs). Specifically, we review the conceptualization and measurement of engagement, predictors of engagement, and importantly, the relationship of engagement with intervention effectiveness. Finally, a theoretically based model of engagement is proposed that considers the unique challenges of trauma recovery. This review is not intended to provide a systematic or exhaustive set of recommendations, rather it is intended to highlight the challenges of engagement research including its definition, measurement, and modeling. Future engagement research that includes valid and reliable measures of engagement will enable consistent exploration of engagement predictors that can then inform methods for increasing engagement and, ultimately, intervention effectiveness.

Examining Factors of Engagement With Digital Interventions for Weight Management: Rapid Review

BACKGROUND

Digital interventions for weight management provide a unique opportunity to target daily lifestyle choices and eating behaviors over a sustained period of time. However, recent evidence has demonstrated a lack of user engagement with digital health interventions, impacting on the levels of intervention effectiveness. Thus, it is critical to identify the factors that may facilitate user engagement with digital health interventions to encourage behavior change and weight management.

OBJECTIVE

The aim of this study was to identify and synthesize the available evidence to gain insights about users' perspectives on factors that affect engagement with digital interventions for weight management.

METHODS

A rapid review methodology was adopted. The search strategy was executed in the following databases: Web of Science, PsycINFO, and PubMed. Studies were eligible for inclusion if they investigated users' engagement with a digital weight management intervention and were published from 2000 onwards. A narrative synthesis of data was performed on all included studies.

RESULTS

A total of 11 studies were included in the review. The studies were qualitative, mixed-methods, or randomized controlled trials. Some of the studies explored features influencing engagement when using a Web-based digital intervention, others specifically explored engagement when accessing a mobile phone app, and some looked at engagement after text message (short message service, SMS) reminders. Factors influencing engagement with digital weight management interventions were found to be both user-related (eg, perceived health benefits) and digital intervention-related (eg, ease of use and the provision of personalized information).

CONCLUSIONS

The findings highlight the importance of incorporating user perspectives during the digital intervention development process to encourage engagement. The review contributes to our understanding of what facilitates user engagement and points toward a coproduction approach for developing digital interventions for weight management. Particularly, it highlights the importance of thinking about user-related and digital tool-related factors from the very early stages of the intervention development process.