User Engagement With Smartphone Apps and Cardiovascular Disease Risk Factor Outcomes: Systematic Review

Smartphone Applications to Prevent Type 2 Diabetes: A Systematic Review and Meta-Analysis

INTRODUCTION

Evidence supporting the use of apps for lifestyle behavior change and diabetes prevention in people at high risk of diabetes is lacking. The aim of this systematic review was to determine the acceptability and effectiveness of smartphone applications (apps) for the prevention of type 2 diabetes.

METHODS

PubMed, Embase, CINAHL and PsychInfo were searched from 2008 to 2023. Included studies involved adults at high risk of developing diabetes evaluating an app intervention with the aim of preventing type 2 diabetes. Random-effects meta-analyses were conducted for weight loss, body mass index (BMI), glycated hemoglobin, and waist circumference. Narrative synthesis was conducted for all studies, including qualitative studies exploring user perspectives.

RESULTS

Twenty-four studies (n=2,378) were included in this systematic review, including 9 randomized controlled trials (RCTs) with an average duration of 6 months, 10 quasi-experimental and 7 qualitative studies. Socially disadvantaged groups were poorly represented. Six RCTs were combined in meta-analyses. Apps were effective at promoting weight loss [mean difference (MD) -1.85; 95% CI -2.90 to -0.80] and decreasing BMI [MD -0.90, 95% CI -1.53 to -0.27], with no effect on glycated hemoglobin and waist circumference. No studies reported on diabetes incidence. Qualitative studies highlighted the need for app personalization.

DISCUSSION

Smartphone apps have a promising effect on preventing type 2 diabetes by supporting weight loss. Future robust trials should include diverse populations in co-design and evaluation of apps and explore the role of artificial intelligence in further personalizing interventions for higher engagement and effectiveness.

Effectiveness of mobile health applications on clinical outcomes and health behaviors in patients with coronary heart disease: A systematic review and meta-analysis

Objective

Mobile health applications (apps) have gained significant popularity and widespread utilization among patients with coronary heart disease (CHD). The objective of this study is to evaluate the effects of mHealth apps on clinical outcomes and health behaviors in patients with CHD.

Methods

Databases were searched from inception until December 2023, including Cochrane Library, PubMed, EMBASE, Web of Science, CINAHL, China National Knowledge Infrastructure (CNKI), Chinese BioMedical Literature Service System (SinoMed), Wanfang Data, China Science and Technology Journal Database (VIP), for randomized controlled trials (RCTs) regarding the effectiveness of mHealth apps in patients with CHD. Two researchers conducted a comprehensive review of the literature, extracting relevant data and evaluating each study's methodological quality separately. The meta-analysis was performed utilizing Review Manager v5.4 software.

Results

A total of 34 RCTs were included, with 5,319 participants. The findings demonstrated that using mHealth apps could decrease the incidence of major adverse cardiac events (RR = 0.68, P = 0.03), readmission rate (RR = 0.56, P < 0.001), total cholesterol (WMD = -0.19, P = 0.03), total triglycerides (WMD = -0.24, P < 0.001), waist circumference (WMD = -1.92, P = 0.01), Self-Rating Anxiety Scale score (WMD = -6.70, P < 0.001), and Self-Rating Depression Scale score (WMD = -7.87, P < 0.001). They can also increase the LVEF (WMD = 6.50, P < 0.001), VO2 max (WMD = 1.89, P < 0.001), 6-min walk distance (6MWD) (WMD = 19.43, P = 0.004), Morisky Medication Adherence Scale-8 score (WMD = 0.96, P = 0.004), and medication adherence rate (RR = 1.24, P = 0.03). Nevertheless, there is no proof that mHealth apps can lower low-density lipoprote in cholesterol, blood pressure, BMI, or other indicator (P > 0.05).

Conclusion

Mobile health apps have the potential to lower the incidence of major adverse cardiac events (MACEs), readmission rates, and blood lipids in patients with CHD. They can also help enhance cardiac function, promote medication adherence, and alleviate symptoms of anxiety and depression. To further corroborate these results, larger-scale, multi-center RCTs with longer follow-up periods are needed.

Validation and verification framework and data integration of biosensors and in vitro diagnostic devices: a position statement of the IFCC Committee on Mobile Health and Bioengineering in Laboratory Medicine (C-MBHLM) and the IFCC Scientific Division

Advances in technology have transformed healthcare and laboratory medicine. Biosensors have emerged as a promising technology in healthcare, providing a way to monitor human physiological parameters in a continuous, real-time, and non-intrusive manner and offering value and benefits in a wide range of applications. This position statement aims to present the current situation around biosensors, their perspectives and importantly the need to set the framework for their validation and safe use. The development of a qualification framework for biosensors should be conceptually adopted and extended to cover digitally measured biomarkers from biosensors for advancing healthcare and achieving more individualized patient management and better patient outcome.

Engagement with mHealth Alcohol Interventions: User Perspectives on an App or Chatbot-Delivered Program to Reduce Drinking

Research suggests participant engagement is a key mediator of mHealth alcohol interventions' effectiveness in reducing alcohol consumption among users. Understanding the features that promote engagement is critical to maximizing the effectiveness of mHealth-delivered alcohol interventions. The purpose of this study was to identify facilitators and barriers to mHealth alcohol intervention utilization among hazardous-drinking participants who were randomized to use either an app (Step Away) or Artificial Intelligence (AI) chatbot-based intervention for reducing drinking (the Step Away chatbot). We conducted semi-structured interviews from December 2019 to January 2020 with 20 participants who used the app or chatbot for three months, identifying common facilitators and barriers to use. Participants of both interventions reported that tracking their drinking, receiving feedback about their drinking, feeling held accountable, notifications about high-risk drinking times, and reminders to track their drinking promoted continued engagement. Positivity, personalization, gaining insight into their drinking, and daily tips were stronger facilitator themes among bot users, indicating these may be strengths of the AI chatbot-based intervention when compared to a user-directed app. While tracking drinking was a theme among both groups, it was more salient among app users, potentially due to the option to quickly track drinks in the app that was not present with the conversational chatbot. Notification glitches, technology glitches, and difficulty with tracking drinking data were usage barriers for both groups. Lengthy setup processes were a stronger barrier for app users. Repetitiveness of the bot conversation, receipt of non-tailored daily tips, and inability to self-navigate to desired content were reported as barriers by bot users. To maximize engagement with AI interventions, future developers should include tracking to reinforce behavior change self-monitoring and be mindful of repetitive conversations, lengthy setup, and pathways that limit self-directed navigation.

Implementing a Sedentary Behavior Change Smartphone App in Cardiac Rehabilitation: A Qualitative Analysis Guided by the Theoretical Domains Framework and Capability, Opportunity, and Motivation-Behavior Model

BACKGROUND

Smartphone apps used in research offer a variety of capabilities to track and influence behavior; however, they often do not translate well into real-world use. Implementation strategies for using apps to reduce sedentary behavior in cardiac rehabilitation are currently unknown.

OBJECTIVE

The aim of this study was to explore (1) barriers and enablers for use of a behavioral smartphone app (Vire and ToDo-CR program) for reducing sedentary behavior in cardiac rehabilitation participants and (2) implementation strategies for future smartphone apps aimed at reducing sedentary behavior in this population.

METHODS

In-depth semistructured interviews were conducted with cardiac rehabilitation participants in the ToDo-CR randomized controlled trial. Participants had used the Vire app and a wearable activity tracker for 6 months. Interviews were audio recorded and transcribed. The researchers used thematic analysis and deductive mapping of themes to the Theoretical Domains Framework and the Capability, Opportunity, and Motivation-Behavior model. Sociodemographic and clinical variables were recorded.

RESULTS

Fifteen participants aged 59 ± 14 years were interviewed. Most were male, tertiary educated, and employed, and had varying experiences with smartphone apps and wearable activity trackers. Five core themes explaining the user experiences of cardiac rehabilitation participants with the Vire app were identified: (1) being tech savvy can be both an enabler and a barrier, (2) app messaging needs to be clear-set expectations from the beginning, (3) get to know me-personalization is important, (4) curious to know more instant feedback, and (5) first impression is key. The themes and subthemes mapped to 12 of the 14 Theoretical Domains Framework domains. Improving engagement and implementation of future smartphone apps for sedentary behavior may be aided by building psychological capability, physical opportunity, and reflective motivation.

CONCLUSIONS

Shifting to in-the-moment behavioral nudges, setting clear expectations, assisting participants to monitor their sitting time, increasing the frequency of tailoring, and understanding more about the participant as well as their experiences and needs for reducing sedentary behavior in cardiac rehabilitation are important future directions.

User-centered development of an mHealth app for cardiovascular prevention

Background

Mobile health (mHealth) apps can be used for cardiovascular disease (CVD) prevention. User-centered design, evidence-based content and user testing can be applied to ensure a high level of usability and adequate app access.

Objective

To develop and evaluate an mHealth app (HerzFit) for CVD prevention.

Methods

HerzFit´s development included a user-centered design approach and guideline-based content creation based on the identified requirements of the target group. Beta testing and a preliminary usability evaluation of the HerzFit prototype were performed. For evaluation, German versions of the System Usability Scale (SUS) and the mHealth App Usability Questionnaire (GER-MAUQ) as well as free text feedback were applied.

Results

User-centered design thinking led to the definition of four personas. Based on their requirements, HerzFit enables users to individually assess, monitor, and optimize their cardiovascular risk profile. Users are also provided with a variety of evidence-based information on CVD and their risk factors. The user interface and system design followed the identified functional requirements. Beta-testers provided feedback on the structure and functionality and rated the usability of HerzFit´s prototype as slightly above average both in SUS and GER-MAUQ rating. Participants positively noted the variety of functions and information presented in HerzFit, while negative feedback mostly concerned wearable synchronization.

Conclusions

The present study demonstrates the user-centered development of a guideline-based mHealth app for CVD prevention. Beta-testing and a preliminary usability study were used to further improve the HerzFit app until its official release.

Precision Recruitment and Engagement of Individuals at Risk for Diabetes and Hypertension in Clinical Trials (PREDHICT): A Randomized Trial for an E-Persuasive Mobile Application to Inform Decision Making about Clinical Trials

The primary objective of this randomized trial was to test the effectiveness of the PREDHiCT digital application, which provides educational and supportive navigation to increase willingness to participate in a future clinical trial. The second objective was to test whether PREDHiCT increased clinical trial literacy or enhanced psychological facilitators of clinical trial participation, such as altruism. To test these two objectives, we conducted a 1-month remote decentralized trial with 100 participants who either have a personal or family history of cardiometabolic health conditions, such as hypertension, diabetes, and obesity. Results indicated significant changes in altruism (mean: -2.94 vs. 0.83; p-value = 0.011) and clinical trial literacy (mean: 0.55 vs. 2.59; p-value = 0.001) from baseline to 1-month follow-up between the control and intervention groups. Additionally, participants exposed to personalized clinical trial navigation had greater clinical trial literacy at the end of the study relative to the individuals in the control arm of the study. Our findings indicate that tailored education, navigation, and access to clinical trials-three unique features of our PREDHiCT app-increased altruism and clinical trial literacy but not willingness to participate in a trial.

Association of Generation and Group Size With the Usage of a Mobile Health App in Thailand: Secondary Analysis of the ThaiSook Cohort Study

BACKGROUND

In Thailand, The National Science and Technology Development Agency developed ThaiSook, a behavior-tracking app, to promote healthy lifestyles. The Faculty of Medicine, Prince of Songkla University (MED PSU)×ThaiSook Healthier Challenge encouraged employees to use the app over a 28-day period (from July 11 to August 7, 2022). Until recently, no previous studies have examined the association of generations and group sizes with mobile health (mHealth) app use. Understanding these relationships can inform the design of effective mHealth interventions and facilitate targeted interventions.

OBJECTIVE

This study aimed to (1) compare the overall app usage and logging function across different generations and group sizes and (2) describe the demographic characteristics of the participants of the MED PSU×ThaiSook Healthier Challenge.

METHODS

We conducted a secondary data analysis of the data from the ThaiSook prospective cohort study. Data were collected through the app and comprised demographic characteristics (ie, age, sex, weight, height, and group size) and behaviors (ie, water consumption, fruit and vegetable consumption, sleep hours, and exercise). The outcomes consisted of users who used the app for at least 80% of the participation period (≥23 days). Bivariate tests (Pearson chi-square test for categorical variables and Mann-Whitney U and Kruskal-Wallis tests for continuous variables) were conducted over sex, generations, initial BMI, and group size. Finally, multiple logistic regression models were used to examine the relationship between the independent variables used by the ThaiSook app and consistent users who had used the app for at least 80% of the participation period.

RESULTS

Of the 827 participants, most were female (734/827, 88.8%), belonged to a medium-sized group of 6-10 members (479/827, 57.9%), and belonged to generation Y (377/761, 49.5%). Multivariate analysis revealed that the overall app usage was 2.09 times higher in women than in men (adjusted odds ratio [AOR] 2.09, 95% CI 1.27-3.44). The older generations used all logging functions more frequently than did generation Y (baby boomers AOR 2.54, 95% CI 1.31-4.92; generation X AOR 1.96, 95% CI 1.42-2.72). The use of all logging functions was higher among participants belonging to larger groups than among those belonging to smaller groups (large groups AOR 2.85, 95% CI 1.58-5.16; medium groups AOR 2.06, 95% CI 1.47-2.88). Water logging was most used (806/827, 97.5% participants), followed by food, sleep, and workout logging.

CONCLUSIONS

The MED PSU×ThaiSook Healthier Challenge participants were mostly females from generation Y and medium-sized groups. Water logging was most frequently used, followed by fruit and vegetable logging. The results indicate that generation and group size were significantly associated with consistent and daily usage (P<.05). Older generations and larger groups engaged with the app more consistently than younger generations and smaller groups and individuals.

The effectiveness of mobile application for monitoring diabetes mellitus and hypertension in the adult and elderly population: systematic review and meta-analysis

CONTEXT

Arterial Hypertension (AH) and Diabetes Mellitus (DM) are diseases that are getting worse all over the world. Linked to this advance, is the growing digital health market with numerous mobile health applications, which aim to help patients and professionals in the proper management of chronic diseases. The aim of this study was to analyze, through a systematic review and meta-analysis, the effectiveness of using mobile health applications in monitoring AH and/or DM in the adult and elderly population.

METHODS

The systematic review and meta-analysis was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Metanalyses guidelines and involved searching five databases - Medline/PubMed, Embase, CINAHL, Virtual Library in Health and Cochrane Library. The review included randomized and cohort clinical trials testing the effects of the intervention on changing biochemical parameters and clinical efficacy in people treated for AH and/or DM. The quality of the selected studies was assessed based on the evaluation criteria of the Joanna Briggs Institute tool. The random effects meta-analysis method was used to explain effect distribution between studies, by Stata® software (version 11.0) and publication bias was examined by visual inspection of graphs and Egger test.

RESULTS

We included 26 studies in the systematic review and 17 in the meta-analysis. These studies were published between 2014 to 2022 in 14 countries. Were reported improvement in knowledge and self-management of AH and DM, social motivation with treatment and behavioral change, reduction in glycated hemoglobin values, fasting glucose and blood pressure, improvement in adherence to drug treatment, among others. The result of the meta-analysis showed that there is evidence that the use of mobile applications can help reduce glycated hemoglobin by 0.39% compared to the usual care group.

CONCLUSIONS

Monitoring and self-monitoring of behaviors and health care related to AH and DM in adults and the elderly through mobile applications, has clinically significant effectiveness in reducing glycated hemoglobin levels. Future studies should provide more evidence and recommendations for best practices and development of digital health interventions.

TRIAL REGISTRATION

PROSPERO. International Prospective Registry of Systematic Reviews. CRD42022361928.

The impact of dietary education and counselling with a smartphone application on secondary prevention of coronary artery disease: A randomised controlled study (the TeleDiet study)

Objective: In a secondary prevention of coronary artery disease (CAD), nutritional management is an integral part of lifestyle optimisation. However, few studies have investigated the potential of remote nutritional follow-up using digital solutions. This study investigates the effectiveness of a smartphone application for nutrition education and feedback with pictures of meals by a dietitian for patients with CAD. Methods: Sixty participants with CAD were randomised to either a TeleDiet group or a control group. Participants in the TeleDiet group participated in dietary education using a messaging application. The primary outcome was the change of the Mediterranean diet score (MedDietScore). The Nutrition-Score, a modification of the MedDietScore, blood tests (blood lipids, blood glucose and kidney function), body mass index, self-efficacy, medication adherence and health-related quality of life during the observation period were analysed as secondary outcomes. Results: Sixty participants participated in the study. The difference in the MedDietScore in the TeleDiet group was greater than in the control group, but not significant (2.0 [-1.0, 4.0] vs. 0.0 [-3.0, 1.5], p = 0.066). The difference in the Nutrition-Score in the TeleDiet group was significantly greater than in the control group (3.0 [1.0, 3.5] vs. 0.0 [-3.0, 2.0], p = 0.029). Nutrition knowledge of the TeleDiet group improved significantly compared to the control group (1.9 ± 1.7 vs. 0.8 ± 2.1, p = 0.048). Conclusions: A feedback system using a simple messaging application that allows patients with CAD to simply send a picture of their food has a positive effect on nutrition knowledge. It could be a hint for the implementation of the Mediterranean diet.

Implementation of a mobile application for outpatient care after liver transplantation

Background

In the face of the Covid-19 pandemic and the need for social distancing new therapeutic tools like mobile health applications might gain in importance for outpatient care. Objective of the present study was to assess if and to what extent the implementation of a free available transplant application in a cohort of liver transplant recipients was possible.

Methods

Patients of the aftercare program at the Department of Transplant Surgery Graz in June 2016 were first asked to complete a survey concerning knowledge about mobile health and their management of everyday life. After using the application for 2 months a second survey evaluated whether the implementation of the application in the daily routine was achievable.

Results

Among 135 patients, 124 (91.9%) agreed to participate. Seventy-one (57.3%) owned a mobile device with which they could use the application, 42 patients (33.8%) decided to try it out for 2 months. The majority stated that the application supported them for therapy management and surveillance of vital parameters. Successful implementation of the application has been reached in 57.1% of patients after 2 months testing period.

Conclusion

The technical prerequisites are only partially met and should be improved. Older patients need extensive support and motivation.

Effect of psychosocial motivations and technology on physical activity behaviours among community older men and women

BACKGROUND

Implementation of physical activity strategies in older populations may be influenced by underlying psychosocial and gender-based factors to physical activity. We explored associations between these factors and physical activity behaviors and technology among older men and women.

METHODS

Community older adults underwent echocardiography and interviewer administered questionnaires that collected physical activity habits, self-motivation, self-empowerment and smartphone usage patterns associated with physical activity. Aerobic capacity was denoted by VO₂max (High VO₂ was defined as VO₂ > 35 (ml/kg/min) for men or VO₂ > 27 (ml/kg/min) for women).

RESULTS

Among 180 participants (mean age 77 (71-80) years; 43% females), 101 (56.1%) had a low VO₂max. Barriers to activity were lack of time (27.8%), tiredness (26.7%), affordability (12.8%) and pain while exercising (12.2%). Compared to participants with high VO₂max, those with low VO₂max were less likely to report feeling good post-exercise (70.3% vs 86.1%, adjusted p = 0.041) and express barriers to exercise (72.3% vs 88.6%, adjusted p = 0.017). Compared to men, women were more likely to express motivation for exercise if they were guided by an instructor (20.5% vs 1.96%, adjusted p = 0.027), less likely to prefer control over exercise type and difficulty (57.7% vs 82.4%, adjusted p = 0.001), express interest in smartphone apps (7.84% vs 24.4%, adjusted p = 0.01) and participate in apps-guided exercise (10.3% vs 29.4%, adjusted p = 0.001). Major factors that motivated the use of smartphone applications to manage individual health were financial incentives (23.9%) and guidance on exercise routines (21.1%) while the reveal of personal information was a major deterrent (28.3%).

CONCLUSIONS

We observed differences in physical activity motivation, empowerment and technology use based on gender and functional status. Tailoring physical activity strategies, including digital health strategies, that target psychosocial and gender-based factors may improve activity participation in older adults.

Patterns of Engagement With an Application-Based Dietary Self-Monitoring Tool Within a Randomized Controlled Feasibility Trial

Introduction

The Dietary Approaches to Stop Hypertension dietary pattern is a proven way to manage hypertension, but adherence remains low. Dietary tracking applications offer a highly disseminable way to self-monitor intake on the pathway to reaching dietary goals but require consistent engagement to support behavior change. Few studies use longitudinal dietary self-monitoring data to assess trajectories and predictors of engagement. We used dietary self-monitoring data from participants in Dietary Approaches to Stop Hypertension Cloud (N=59), a feasibility trial to improve diet quality among women with hypertension, to identify trajectories of engagement and explore associations between participant characteristics.

Methods

We used latent class growth modeling to identify trajectories of engagement with a publicly available diet tracking application and used bivariate and regression analyses to assess the associations of classifications of engagement with participant characteristics.

Results

We identified 2 latent classes of engagement: consistent engagers and disengagers. Consistent engagers were more likely to be older, more educated, and married or living with a partner. Although consistent engagers exhibited slightly greater changes in Dietary Approaches to Stop Hypertension score, the difference was not significant.

Conclusions

This study highlights an important yet underutilized methodologic approach for uncovering dietary self-monitoring engagement patterns. Understanding how certain individuals engage with digital technologies is an important step toward designing cost-effective behavior change interventions.

Trial registration

This study is registered at www.clinicaltrials.gov NCT03215472.

The effect of a game-based mobile app 'MyHeartMate' to promote lifestyle change in coronary disease patients: a randomized controlled trial

Aims

Secondary prevention reduces coronary heart disease (CHD) progression. Traditional prevention programs including cardiac rehabilitation are under-accessed, which smartphone apps may overcome. To evaluate the effect of a game-based mobile app intervention (MyHeartMate) to improve cardiovascular risk factors and lifestyle behaviours.

Methods and results

Single-blind randomized trial of CHD patients in Sydney, 2017-2021. Intervention group were provided the MyHeartMate app for 6 months. Co-designed features included an avatar of the patient's heart and tokens earned by risk factor work (tracking, challenges, and quizzes). The control group received usual care. Primary outcome was self-reported physical activity [metabolic equivalents (METs), Global Physical Activity Questionnaire] and secondary outcomes included lipid levels, blood pressure (BP), body mass index, and smoking. Pre-specified sample size was achieved (n = 390), age 61.2 ± 11.5 years; 82.5% men and 9.2% current smokers. At 6 months, adjusted for baseline levels, the intervention group achieved more physical activity than control (median difference 329 MET mins/wk), which was not statistically significant (95% CI -37.4, 696; P = 0.064). No differences occurred between groups on secondary outcomes except for lower triglyceride levels in the intervention [mean difference -0.3 (95% CI -0.5, -0.1 mmoL/L, P = 0.004)]. Acceptability was high: 94.8% of intervention participants engaged by tracking exercise or BP and completing missions; 26.8% continued to engage for ≥30 days. Participants (n = 14) reported the app supported tracking behaviours and risk factors, reinforcing and improving self-care confidence, and decreasing anxiety.

Conclusion

A game-based app proved highly acceptable for patients with CHD but did not improve risk factors or lifestyle behaviours other than triglyceride levels.

Smoking Cessation Smartphone App Use Over Time: Predicting 12-Month Cessation Outcomes in a 2-Arm Randomized Trial

BACKGROUND

Little is known about how individuals engage over time with smartphone app interventions and whether this engagement predicts health outcomes.

OBJECTIVE

In the context of a randomized trial comparing 2 smartphone apps for smoking cessation, this study aimed to determine distinct groups of smartphone app log-in trajectories over a 6-month period, their association with smoking cessation outcomes at 12 months, and baseline user characteristics that predict data-driven trajectory group membership.

METHODS

Functional clustering of 182 consecutive days of smoothed log-in data from both arms of a large (N=2415) randomized trial of 2 smartphone apps for smoking cessation (iCanQuit and QuitGuide) was used to identify distinct trajectory groups. Logistic regression was used to determine the association of group membership with the primary outcome of 30-day point prevalence of smoking abstinence at 12 months. Finally, the baseline characteristics associated with group membership were examined using logistic and multinomial logistic regression. The analyses were conducted separately for each app.

RESULTS

For iCanQuit, participants were clustered into 3 groups: "1-week users" (610/1069, 57.06%), "4-week users" (303/1069, 28.34%), and "26-week users" (156/1069, 14.59%). For smoking cessation rates at the 12-month follow-up, compared with 1-week users, 4-week users had 50% higher odds of cessation (30% vs 23%; odds ratio [OR] 1.50, 95% CI 1.05-2.14; P=.03), whereas 26-week users had 397% higher odds (56% vs 23%; OR 4.97, 95% CI 3.31-7.52; P<.001). For QuitGuide, participants were clustered into 2 groups: "1-week users" (695/1064, 65.32%) and "3-week users" (369/1064, 34.68%). The difference in the odds of being abstinent at 12 months for 3-week users versus 1-week users was minimal (23% vs 21%; OR 1.16, 95% CI 0.84-1.62; P=.37). Different baseline characteristics predicted the trajectory group membership for each app.

CONCLUSIONS

Patterns of 1-, 3-, and 4-week smartphone app use for smoking cessation may be common in how people engage in digital health interventions. There were significantly higher odds of quitting smoking among 4-week users and especially among 26-week users of the iCanQuit app. To improve study outcomes, strategies for detecting users who disengage early from these interventions (1-week users) and proactively offering them a more intensive intervention could be fruitful.

User engagement in relation to effectiveness of a digital lifestyle intervention (the HealthyMoms app) in pregnancy

Although user engagement is generally considered important for the effectiveness of digital behavior change interventions, there is a lack of such data in pregnancy. The aim of this study was therefore to examine the associations of user engagement with the HealthyMoms app with gestational weight gain, diet quality and physical activity in pregnancy. The study involved secondary analyses of participant data from the intervention group (n = 134) in a randomized controlled trial to determine the effectiveness of a 6-month mHealth intervention (the HealthyMoms app) on gestational weight gain, diet quality and physical activity. In adjusted regression models, the total number of registrations from three self-monitoring features (i.e., for weight-, diet- and physical activity) was associated with lower gestational weight gain (β =  − 0.18, P = 0.043) and improved diet quality (β = 0.17, P = 0.019). These findings were mainly attributable to the associations of physical activity registrations with lower gestational weight gain (β =  − 0.20, P = 0.026) and improved diet quality (β = 0.20, P = 0.006). However, the number of app sessions and page views were not associated with any of the outcomes. Our results may motivate efforts to increase user engagement in digital lifestyle interventions in pregnancy. However, additional studies are needed to further elucidate the influence of different types of user engagement in digital pregnancy interventions on their effectiveness.

Trial registration: ClinicalTrials.gov (NCT03298555); https://clinicaltrials.gov/ct2/show/NCT03298555 (date of registration: October 2, 2017; date of first enrolled participant: October 24, 2017).

The Association Between Smartphone App–Based Self-monitoring of Hypertension-Related Behaviors and Reductions in High Blood Pressure: Systematic Review and Meta-analysis

Background

Self-monitoring of behavior can support lifestyle modifications; however, we do not know whether such interventions are effective in supporting positive changes in hypertension-related health behaviors and thus in reducing blood pressure in patients treated for hypertension.

Objective

This systematic literature review evaluates the extent to which smartphone app–based self-monitoring of health behavior supports reductions in blood pressure and changes in hypertension-related behaviors. It also explores the behavioral components that might explain intervention effectiveness.

Methods

A systematic search of 7 databases was conducted in August 2021. Article screening, study and intervention coding, and data extraction were completed independently by reviewers. The search strategy was developed using keywords from previous reviews and relevant literature. Trials involving adults, published after the year 2000, and in the English language were considered for inclusion. The random-effects meta-analysis method was used to account for the distribution of the effect across the studies.

Results

We identified 4638 articles, of which 227 were included for full-text screening. A total of 15 randomized controlled trials were included in the review. In total, 7415 patients with hypertension were included in the meta-analysis. The results indicate that app-based behavioral self-monitoring interventions had a small but significant effect in reducing systolic blood pressure (SBP), on average, by 1.64 mmHg (95% CI 2.73-0.55, n=7301; odds ratio [OR] 1.60, 95% CI 0.74-3.42, n=114) and in improving changes in medication adherence behavior (standardized mean difference [SMD] 0.78, 95% CI 0.22-1.34) compared to usual care or minimal intervention. The review found the intervention had a small effect on supporting improvements in healthy diet by changing habits related to high sodium food (SMD –0.44, 95% CI –0.79 to –0.08) and a trend, although insignificant, toward supporting smoking cessation, low alcohol consumption, and better physical activity behaviors. A subgroup analysis found that behavioral self-monitoring interventions combined with tailored advice resulted in higher and significant changes in both SBP and diastolic blood pressure (DBP) in comparison to those not providing tailored advice (SBP: –2.92 mmHg, 95% CI –3.94 to –1.90, n=3102 vs –0.72 mmHg, 95% CI –1.67 to 0.23, n=4199, χ²=9.65, P=.002; DBP: –2.05 mmHg, 95% CI –3.10 to –1.01, n=968 vs 1.54 mmHg, 95% CI –0.53 to 3.61, n=400, χ²=9.19, P=.002).

Conclusions

Self-monitoring of hypertension-related behaviors via smartphone apps combined with tailored advice has a modest but potentially clinically significant effect on blood pressure reduction. Future studies could use rigorous methods to explore its effects on supporting changes in both blood pressure and hypertension-related health behaviors to inform recommendations for policy making and service provision.

Trial Registration

PROSPERO CRD42019136158; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=136158

A Mobile Health-Based Disease Management Program Improves Blood Pressure in People With Multiple Lifestyle-Related Diseases at Risk of Developing Vascular Disease ― A Retrospective Observational Study ―

Background: The overlap of multiple lifestyle-related diseases increases the risk of vascular diseases. This study investigated the effects of a mobile health (mHealth)-based disease management program on blood pressure and the safety of this program in people with multiple lifestyle-related diseases at risk of developing vascular disease.

Methods and Results: This retrospective observational study was conducted using secondary data collected by PREVENT Inc. People with a full history of hypertension, diabetes, and dyslipidemia and who participated in a 6-month mHealth-based disease management program were included in the study. The primary outcome was blood pressure. Adverse events during the program were investigated to evaluate safety. In total, 125 participants (mean [±SD] age 55.3±6.2 years) were examined. Systolic and diastolic blood pressure were significantly lower after the intervention than at baseline (systolic blood pressure, 128.0±12.3 vs. 131.9±12.7 mmHg [P<0.001]; diastolic blood pressure, 81.2±9.3 vs. 83.6±8.9 mmHg; P=0.003). No serious adverse events occurred during the program.

Conclusions: The present results indicate that the mHealth-based disease management program may reduce blood pressure in people with multiple lifestyle-related diseases at risk of developing vascular disease and that the program is safe. These findings will help shape future health instructions using mHealth-based interventions.

Big Data in Cardiology: State-of-Art and Future Prospects

Cardiological disorders contribute to a significant portion of the global burden of disease. Cardiology can benefit from Big Data, which are generated and released by different sources and channels, like epidemiological surveys, national registries, electronic clinical records, claims-based databases (epidemiological Big Data), wet-lab, and next-generation sequencing (molecular Big Data), smartphones, smartwatches, and other mobile devices, sensors and wearable technologies, imaging techniques (computational Big Data), non-conventional data streams such as social networks, and web queries (digital Big Data), among others. Big Data is increasingly having a more and more relevant role, being highly ubiquitous and pervasive in contemporary society and paving the way for new, unprecedented perspectives in biomedicine, including cardiology. Big Data can be a real paradigm shift that revolutionizes cardiological practice and clinical research. However, some methodological issues should be properly addressed (like recording and association biases) and some ethical issues should be considered (such as privacy). Therefore, further research in the field is warranted.

Remote Healthcare for Elderly People Using Wearables: A Review

The growth of health care spending on older adults with chronic diseases faces major concerns that require effective measures to be adopted worldwide. Among the main concerns is whether recent technological advances now offer the possibility of providing remote health care for the aging population. The benefits of suitable prevention and adequate monitoring of chronic diseases by using emerging technological paradigms such as wearable devices and the Internet of Things (IoT) can increase the detection rates of health risks to raise the quality of life for the elderly. Specifically, on the subject of remote health monitoring in older adults, a first approach is required to review devices, sensors, and wearables that serve as tools for obtaining and measuring physiological parameters in order to identify progress, limitations, and areas of opportunity in the development of health monitoring schemes. For these reasons, a review of articles on wearable devices was presented in the first instance to identify whether the selected articles addressed the needs of aged adults. Subsequently, the direct review of commercial and prototype wearable devices with the capability to read physiological parameters was presented to identify whether they are optimal or usable for health monitoring in older adults.

The Relationship Between Weight Loss Outcomes and Engagement in a Mobile Behavioral Change Intervention: Retrospective Analysis

Background

There is large variance in weight loss outcomes of digital behavior change interventions (DBCIs). It has been suggested that different patterns of engagement in the program could be responsible for this variance in outcomes. Previous studies have found that the amount of engagement on DBCIs, such as the number of meals logged or articles read, is positively associated with weight loss.

Objective

This retrospective study extends previous research by observing how important weight loss outcomes (high weight loss: 10% or greater body weight loss; moderate weight loss: between 5% to 10%; stable weight: 0 plus or minus 1%) are associated with engagement on a publicly available mobile DBCI (Noom) from 9 to 52 weeks.

Methods

Engagement and weight data for eligible participants (N=11,252) were extracted from the Noom database. Engagement measures included the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week. Weight was self-reported on the program. Multiple linear regressions examined how weight loss outcome (moderate and high vs stable) was associated with each engagement measure across 3 study time periods: 9-16 weeks, 17-32 weeks, and 33-52 weeks.

Results

At 9-16 weeks, among the 11,252 participants, 2594 (23.05%) had stable weight, 6440 (57.23%) had moderate weight loss, and 2218 (19.71%) had high weight loss. By 33-52 weeks, 525 (18.21%) had stable weight, 1214 (42.11%) had moderate weight loss, and 1144 (39.68%) had high weight loss. Regression results showed that moderate weight loss and high weight loss outcomes were associated with all engagement measures to a significantly greater degree than was stable weight (all P values <.001). These differences held across all time periods with the exception of exercise for the moderate weight loss category at 1 time period of 33-52 weeks. Exercise logging increased from 9 to 52 weeks regardless of the weight loss group.

Conclusions

Our results suggest that these clinically important weight loss outcomes are related to the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week both in the short-term and long-term (ie, 1 year) on Noom. This provides valuable data on engagement patterns over time on a self-directed mobile DBCI, can help inform how interventions tailor recommendations for engagement depending on how much weight individuals have lost, and raises important questions for future research on engagement in DBCIs.

Effects of Mobile Application Program (App)-Assisted Health Education on Preventive Behaviors and Cancer Literacy among Women with Cervical Intraepithelial Neoplasia

Objective: This study aimed (1) to study the effects of health education on preventive behaviors and cancer literacy among women with cervical intraepithelial neoplasia (CIN); (2) to compare the effects of mobile application program (App)-assisted health education with traditional book-form health education. Participants: A total of 132 women ages 20 to 69 years women. Methods: This prospective longitudinal study enrolled 132 CIN women who were evaluated three times. Propensity score matching was used by controlling subjects’ age strata, body mass index, education level, occupation, and type of surgery. Results: The influences of various educational tools were investigated. Four domains were assessed, including health behavior, attitude towards behavior change, self-efficacy of behavior, and cervical cancer (CCa) literacy. Significant improvements in behavior change and CCa literacy due to a health education program were observed (p ≤ 0.002). The App combined with a traditional booklet had the highest score for behavior change and was significantly greater than the booklet-only learning (p = 0.002). The App-assisted form, either App alone or combined with booklet, had a significantly better impact on health promotion when compared to the booklet alone (p = 0.045 and 0.005, respectively). App-only learning had the highest score of CCa literacy (p = 0.004). Conclusion: Health education interventions can have positive effects in terms of change of behavior and CCa literacy. App-assisted learning could be used as a supportive technology, and App learning alone or combined with a traditional booklet may be an innovative model of clinical health promotion for women with CIN.

Use of mobile applications in heart failure self-management: a qualitative study exploring the patient and primary care clinician perspective (Preprint)

Background

Mobile apps have the potential to support patients with heart failure and facilitate disease self-management, but this area of research is recent and rapidly evolving, with inconsistent results for efficacy. So far, most of the published studies evaluated the feasibility of a specific app or assessed the quality of apps available in app stores. Research is needed to explore patients’ and clinicians’ perspectives to guide app development, evaluation, and implementation into models of care.

Objective

This study aims to explore the patient and primary care clinician perspective on the facilitators and barriers to using mobile apps, as well as desired features, to support heart failure self-management.

Methods

This is a qualitative phenomenological study involving face-to-face semistructured interviews. Interviews were conducted in a general practice clinic in Sydney, Australia. Eligible participants were adult patients with heart failure and health care professionals who provided care to these patients at the clinic. Patients did not need to have previous experience using heart failure mobile apps to be eligible for this study. The interviews were audio-recorded, transcribed, and analyzed using inductive thematic data analysis in NVivo 12.

Results

A total of 12 participants were interviewed: 6 patients (mean age 69 [SD 7.9] years) and 6 clinicians. The interviews lasted from 25 to 45 minutes. The main facilitators to the use of apps to support heart failure self-management were communication ability, personalized feedback and education, and automated self-monitoring. Patients mentioned that chat-like features and ability to share audio-visual information can be helpful for getting support outside of clinical appointments. Clinicians considered helpful to send motivational messages to patients and ask them about signs and symptoms of heart failure decompensation. Overall, participants highlighted the importance of personalization, particularly in terms of feedback and educational content. Automated self-monitoring with wireless devices was seen to alleviate the burden of tracking measures such as weight and blood pressure. Other desired features included tools to monitor patient-reported outcomes and support patients’ mental health and well-being. The main barriers identified were the patients’ unwillingness to engage in a new strategy to manage their condition using an app, particularly in the case of low digital literacy. However, clinicians mentioned this barrier could potentially be overcome by introducing the app soon after an exacerbation, when patients might be more willing to improve their self-management and avoid rehospitalization.

Conclusions

The use of mobile apps to support heart failure self-management may be facilitated by features that increase the usefulness and utility of the app, such as communication ability in-between consultations and personalized feedback. Also important is facilitating ease of use by supporting automated self-monitoring through integration with wireless devices. Future research should consider these features in the co-design and testing of heart failure mobile apps with patients and clinicians.

Contrasting a Mobile App with a Conversational Chatbot for Reducing Alcohol Consumption: A Pilot Trial (Preprint)

Background

Mobile apps have shown considerable promise for reducing alcohol consumption among problem drinkers, but like many mobile health apps, they frequently report low utilization, which is an important limitation, as research suggests that effectiveness is related to higher utilization. Interactive chatbots have the ability to provide a conversational interface with users and may be more engaging and result in higher utilization and effectiveness, but there is limited research into this possibility.

Objective

This study aimed to develop a chatbot alcohol intervention based on an empirically supported app (Step Away) for reducing drinking and to conduct a pilot trial of the 2 interventions. Included participants met the criteria for hazardous drinking and were interested in reducing alcohol consumption. The study assessed utilization patterns and alcohol outcomes across the 2 technology conditions, and a waitlist control group.

Methods

Participants were recruited using Facebook advertisements. Those who met the criteria for hazardous consumption and expressed an interest in changing their drinking habits were randomly assigned to three conditions: the Step Away app, Step Away chatbot, and waitlist control condition. Participants were assessed on the web using the Alcohol Use Disorders Identification Test, Adapted for Use in the United States, Readiness to Change Questionnaire, Short Inventory of Problems-Revised, and Timeline Followback at baseline and at 12 weeks follow-up.

Results

A total of 150 participants who completed the baseline and follow-up assessments were included in the final analysis. ANOVA results indicated that participants in the 3 conditions changed their drinking from baseline to follow-up, with large effect sizes noted (ie, η²=0.34 for change in drinks per day across conditions). However, the differences between groups were not significant across the alcohol outcome variables. The only significant difference between conditions was in the readiness to change variable, with the bot group showing the greatest improvement in readiness (F_2,147=5.6; P=.004; η²=0.07). The results suggested that the app group used the app for a longer duration (mean 50.71, SD 49.02 days) than the bot group (mean 27.16, SD 30.54 days; P=.02). Use of the interventions was shown to predict reduced drinking in a multiple regression analysis (β=.25, 95% CI 0.00-0.01; P=.04).

Conclusions

Results indicated that all groups in this study reduced their drinking considerably from baseline to the 12-week follow-up, but no differences were found in the alcohol outcome variables between the groups, possibly because of a combination of small sample size and methodological issues. The app group reported greater use and slightly higher usability scores than the bot group, but the bot group demonstrated improved readiness to change scores over the app group. The strengths and limitations of the app and bot interventions as well as directions for future research are discussed.

Trial Registration

ClinicalTrials.gov NCT04447794; https://clinicaltrials.gov/ct2/show/NCT04447794