Behaviour change techniques in cardiovascular disease smartphone apps to improve physical activity and sedentary behaviour: Systematic review and meta-regression

Feasibility study of rehabilitation for cardiac patients aided by an artificial intelligence web-based programme: a randomised controlled trial (RECAP trial)-a study protocol

INTRODUCTION

Cardiac rehabilitation (CR) delivered by rehabilitation specialists in a healthcare setting is effective in improving functional capacity and reducing readmission rates after cardiac surgery. It is also associated with a reduction in cardiac mortality and recurrent myocardial infarction. This trial assesses the feasibility of a home-based CR programme delivered using a mobile application (app).

METHODS

The Rehabilitation through Exercise prescription for Cardiac patients using an Artificial intelligence web-based Programme (RECAP) randomised controlled feasibility trial is a single-centre prospective study, in which patients will be allocated on a 1:1 ratio to a home-based CR programme delivered using a mobile app with accelerometers or standard hospital-based rehabilitation classes. The home-based CR programme will employ artificial intelligence to prescribe exercise goals to the participants on a weekly basis. The trial will recruit 70 patients in total. The primary objectives are to evaluate participant recruitment and dropout rates, assess the feasibility of randomisation, determine acceptability to participants and staff, assess the rates of potential outcome measures and determine hospital resource allocation to inform the design of a larger randomised controlled trial for clinical efficacy and health economic evaluation. Secondary objectives include evaluation of health-related quality of life and 6 minute walk distance.

ETHICS AND DISSEMINATION

RECAP trial received a favourable outcome from the Berkshire research ethics committee in September 2022 (IRAS 315483).Trial results will be made available through publication in peer-reviewed journals and presented at relevant scientific meetings.

TRIAL REGISTRATION NUMBER

ISRCTN97352737.

Mining User Reviews From Hypertension Management Mobile Health Apps to Explore Factors Influencing User Satisfaction and Their Asymmetry: Comparative Study

BACKGROUND

Hypertension significantly impacts the well-being and health of individuals globally. Hypertension management apps (HMAs) have been shown to assist patients in controlling blood pressure (BP), with their efficacy validated in clinical trials. However, the utilization of HMAs continues to be suboptimal. Presently, there is a dearth of real-world research based on big data and exploratory mining that compares Chinese and American HMAs.

OBJECTIVE

This study aims to systematically gather HMAs and their user reviews from both China and the United States. Subsequently, using data mining techniques, the study aims to compare the user experience, satisfaction levels, influencing factors, and asymmetry between Chinese and American users of HMAs. In addition, the study seeks to assess the disparities in satisfaction and its determinants while delving into the asymmetry of these factors.

METHODS

The study sourced HMAs and user reviews from 10 prominent Chinese and American app stores globally. Using the latent Dirichlet allocation (LDA) topic model, the research identified various topics within user reviews. Subsequently, the Tobit model was used to investigate the impact and distinctions of each topic on user satisfaction. The Wald test was applied to analyze differences in effects across various factors.

RESULTS

We examined a total of 261 HMAs along with their associated user reviews, amounting to 116,686 reviews in total. In terms of quantity and overall satisfaction levels, Chinese HMAs (n=91) and corresponding reviews (n=16,561) were notably fewer compared with their American counterparts (n=220 HMAs and n=100,125 reviews). The overall satisfaction rate among HMA users was 75.22% (87,773/116,686), with Chinese HMAs demonstrating a higher satisfaction rate (13,866/16,561, 83.73%) compared with that for American HMAs (73,907/100,125, 73.81%). Chinese users primarily focus on reliability (2165/16,561, 13.07%) and measurement accuracy (2091/16,561, 12.63%) when considering HMAs, whereas American users prioritize BP tracking (17,285/100,125, 17.26%) and data synchronization (12,837/100,125, 12.82%). Seven factors (easy to use: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; heart rate detection function: P=.02; blood pressure tracking function: P<.001; and interface design: P=.01) significantly influenced the positive deviation (PD) of Chinese HMA user satisfaction, while 8 factors (easy to use: P<.001; reliability: P<.001; measurement accuracy: P<.001; compatibility: P<.001; cost: P<.001; interface design: P<.001; real-time: P<.001; and data privacy: P=.001) affected the negative deviation (ND). Notably, BP tracking had the greatest effect on PD (β=.354, P<.001), while cost had the most significant impact on ND (β=3.703, P<.001). All 12 factors (easy to use: P<.001; blood pressure tracking function: P<.001; data synchronization: P<.001; blood pressure management effect: P<.001; heart rate detection function: P<.001; data sharing: P<.001; reliability: P<.001; compatibility: P<.001; interface design: P<.001; advertisement distribution: P<.001; measurement accuracy: P<.001; and cost: P<.001) significantly influenced the PD and ND of American HMA user satisfaction. Notably, BP tracking had the greatest effect on PD (β=0.312, P<.001), while data synchronization had the most significant impact on ND (β=2.662, P<.001). In addition, the influencing factors of PD and ND in user satisfaction of HMA in China and the United States are different.

CONCLUSIONS

User satisfaction factors varied significantly between different countries, showing considerable asymmetry. For Chinese HMA users, ease of use and interface design emerged as motivational factors, while factors such as cost, measurement accuracy, and compatibility primarily contributed to user dissatisfaction. For American HMA users, motivational factors were ease of use, BP tracking, BP management effect, interface design, measurement accuracy, and cost. Moreover, users expect features such as data sharing, synchronization, software reliability, compatibility, heart rate detection, and nonintrusive advertisement distribution. Tailored experience plans should be devised for different user groups in various countries to address these diverse preferences and requirements.

Patient-reported preferences in eHealth-based cardiac rehabilitation: A qualitative investigation of behavior change techniques, barriers and facilitators

Background

Cardiac rehabilitation (CR) reduces recurrent cardiac events and mortality in patients with cardiovascular diseases (CVD). Innovative eHealth methods can facilitate CR uptake and effectiveness by addressing barriers associated with clinic-based rehabilitation. Tailoring eHealth-based CR to patient preferences is needed to further enhance CR.

Purpose

To identify preferred behavior change techniques (BCTs) as well as barriers and facilitators for the different health behaviors targeted in eHealth-based CR among patients who have been referred to CR.

Methods

Thirty-nine patients were interviewed in nine focus groups in The Netherlands, Germany, and Spain. A thematic analysis, using a combined deductive and inductive approach to coding, was conducted to identify BCTs and barriers and facilitators to behavior change. Behaviors under investigation included physical activity, medication adherence, eating a cardiac healthy-diet, stress reduction and smoking cessation.

Results

The perceived helpfulness of BCTs depended on the specific behavior targeted. Common barriers were negative emotional state and physical limitations. A desire to feel physically or mentally well and having experienced a cardiac life event were the most common facilitators across health behaviors. Specific BCTs, barriers and facilitators were found for each of the health behavior.

Conclusions

Behavior change techniques that patients preferred for each health behavior targeted in eHealth-based CR were identified. A negative emotional state, experiencing a life event, and improving physical functioning are important barriers and facilitators in multiple behaviors targeted in eHealth-based CR programs. Additional tailoring of interventions to patient preferences for BCTs and patient-specific barriers and facilitators per health behavior could lead to further improvement of eHealth-based CR.

Enhancing Behavioural Changes: A Narrative Review on the Effectiveness of a Multifactorial APP-Based Intervention Integrating Physical Activity

The rapid evolution of technologies is a key innovation in the organisation and management of physical activities (PA) and sports. The increase in benefits and opportunities related to the adoption of technologies for both the promotion of a healthy lifestyle and the management of chronic diseases is evident. In the field of telehealth, these devices provide personalised recommendations, workout monitoring and injury prevention. The study aimed to provide an overview of the landscape of technology application to PA organised to promote active lifestyles and improve chronic disease management. This review identified specific areas of focus for the selection of articles: the utilisation of mobile APPs and technological devices for enhancing weight loss, improving cardiovascular health, managing diabetes and cancer and preventing osteoporosis and cognitive decline. A multifactorial intervention delivered via mobile APPs, which integrates PA while managing diet or promoting social interaction, is unquestionably more effective than a singular intervention. The main finding related to promoting PA and a healthy lifestyle through app usage is associated with "behaviour change techniques". Even when individuals stop using the APP, they often maintain the structured or suggested lifestyle habits initially provided by the APP. Various concerns regarding the excessive use of APPs need to be addressed.

Use of behavior change techniques in physical activity programs and services for older adults: findings from a rapid review

BACKGROUND

Understanding behavior change techniques (BCTs) used in randomized controlled trials (RCTs) of physical activity programs/services for older adults can help us to guide their implementation in real-world settings.

PURPOSE

This study aims to: (a) identify the number and type of BCTs used in physical activity programs/services for older adults evaluated in large, good quality RCTs and (b) explore the impact of different BCTs on different outcome domains.

METHODS

This is a secondary data analysis of a WHO-commissioned rapid review of physical activity programs/services for older adults. Fifty-six trials testing 70 interventions were coded for the type and number of BCTs present using a published BCT taxonomy. The proportion of positive effects found from physical activity interventions using the most common BCTs was calculated for the outcomes of physical activity, intrinsic capacity, functional ability, social domain, cognitive and emotional functioning, and well-being and quality of life.

RESULTS

Thirty-nine of the 93 possible BCTs were identified in the included trials and 529 BCTs in total (mean 7.6, range 2-17). The most common BCTs were "action planning" (68/70 interventions), "instructions on how to perform a behavior" (60/70), "graded tasks" (53/70), "demonstration of behavior" (44/70), and "behavioral practice/rehearsal" (43/70). Interventions that used any of the most common BCTs showed overwhelmingly positive impacts on physical activity and social domain outcomes.

CONCLUSION

Consideration of which BCTs are included in interventions and their impact on outcomes can improve the effectiveness and implementation of future interventions. To enable this, providers can design, implement, and evaluate interventions using a BCT taxonomy.

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.

Making it transparent: A worked example of articulating programme theory for a digital health application using Intervention Mapping

Objective

Digital health interventions for behaviour change are usually complex interventions, and intervention developers should 'articulate programme theory', that is, they should offer detailed descriptions of individual intervention components and their proposed mechanisms of action. However, such detailed descriptions often remain lacking. The objective of this work was to provide a conceptual case study with an applied example of 'articulating programme theory' for a newly developed digital health intervention.

Methods

Intervention Mapping methodology was applied to arrive at a detailed description of programme theory for a newly developed digital health intervention that aims to support cardiac rehabilitation patients in establishing heart-healthy physical activity habits. Based on a Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation (PRECEDE) logic model of the problem, a logic model of change was developed. The proposed mechanisms of action were visualised in an acyclic behaviour change diagram.

Results

Programme theory for this digital health intervention includes 4 sub-behaviours of the main target behaviour (i.e. habitual heart-healthy physical activity), 8 personal determinants and 12 change objectives (i.e. changes needed at the determinant level to achieve the sub-behaviours). These are linked to 12 distinct features of the digital health intervention and 12 underlying behaviour change methods.

Conclusions

This case study offers a worked example of articulating programme theory for a digital health intervention using Intervention Mapping. Intervention developers and researchers may draw on this example to replicate the method, or to reflect on most suitable approaches for their own behaviour change interventions.

The Importance of Activating Factors in Physical Activity Interventions for Older Adults Using Information and Communication Technologies: Systematic Review

Background

In an aging population, it is important to activate older adults in taking care of their own health. Increasing physical activity is one way to avoid or lessen age-related physical and mental impairments. Interest in the use of information and communication technology (ICT) tools to promote physical activity among older adults is growing considerably. Such tools are suitable for communicating activation factors-skills, knowledge, and motivation-by integrating a variety of behavior change techniques (BCTs) to enhance physical activity. Although activation factors have been incorporated into physical activity interventions using ICT, little is known about the actual integration methods used in such interventions or about the effects of activation factors on influencing behavior change.

Objective

The first aim of this study was to identify which of the activation factors were covered in physical activity-promoting ICT interventions for older adults and which BCTs were used to address them. The second objective was to classify the user interaction interfaces and delivery modes that were used to promote these activation factors.

Methods

The search engines of PubMed, Web of Science, and ScienceDirect were used to search for and identify articles examining the effectiveness of ICT interventions for promoting physical activity in older adults. References and related data were selected, extracted, and reviewed independently by 2 reviewers. The risk of bias was assessed, and any conflict was addressed by a third separate reviewer. Selected articles included older adults aged ≥55 years without pre-existing medical diseases and other physical or mental conditions that could hinder movement.

Results

In total, 368 records were retrieved, and 13 studies met all inclusion criteria. Articles differed in terms of themes, timescales, user interaction interfaces, and outcome measures; therefore, a quantitative data synthesis was not feasible. Motivation was the most promoted activation factor among all trials (33 times). An app and a smartwatch were used in the majority of intervention groups (7/20, 35%) for tracking physical activity and receiving personalized feedback based on the individual goals. Skills (25 times) and knowledge (17 times) were the next most commonly addressed activation factors. Face-to-face interaction was the most used approach to targeting users' skills, including providing instructions on how to perform a behavior and exchanging knowledge via education on the health consequences of insufficient physical activity. Overall, integrating all 3 activation factors and using multiple user interaction interfaces with a variety of delivery modes proved the most effective in improving physical activity.

Conclusions

This study highlights commonly used BCTs and preferred modes of their delivery. So far, only a limited number of available BCTs (21/99, 21%) have been integrated. Considering their effectiveness, a larger variety of BCTs that address skills, knowledge, and motivation should be exploited in future ICT interventions.

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

BACKGROUND

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Effect of a Mobile App-Based Urinary Incontinence Self-Management Intervention Among Pregnant Women in China: Pragmatic Randomized Controlled Trial

BACKGROUND

Urinary incontinence (UI) is a highly prevalent health concern commonly observed during and after pregnancy that can substantially impact women's physical and psychological well-being and quality of life. Owing to its numerous advantages, mobile health may be a promising solution; however, it is unclear whether the app-based intervention can effectively improve UI symptoms during and after pregnancy.

OBJECTIVE

This study aimed to evaluate the effectiveness of the Urinary Incontinence for Women (UIW) app-based intervention for UI symptom improvement among pregnant women in China.

METHODS

Singleton pregnant women without incontinence before pregnancy who were aged ≥18 years and between 24 and 28 weeks of gestation were recruited from a tertiary public hospital in China and were randomly allocated (1:1) to either an experimental group (n=63) or a control group (n=63). The experimental group received the UIW app intervention and oral pelvic floor muscle training (PFMT) instructions, whereas the control group received oral PFMT instructions alone. Neither the participants nor the researchers were blinded to the intervention. The primary outcome was UI severity. The secondary outcomes included quality of life, self-efficacy with PFMT, and knowledge of UI. All data were collected at baseline, 2 months after randomization, and 6 weeks post partum through electronic questionnaires or by checking the electronic medical record system. Data analysis followed the intention-to-treat principle. A linear mixed model was used to examine the intervention effect on primary and secondary outcomes.

RESULTS

Participants in the experimental and control groups were comparable at baseline. Of the 126 overall participants, 117 (92.9%) and 103 (81.7%) women completed follow-up visits at 2 months after randomization and 6 weeks after delivery, respectively. A statistically significant difference in UI symptom severity was observed between the experimental group and control group (2 months after randomization: mean difference -2.86, 95% CI -4.09 to -1.64, P<.001; 6 weeks post partum: mean difference -2.68, 95% CI -3.87 to -1.49, P<.001). For the secondary outcomes, a statistically significant intervention effect on the quality of life, self-efficacy, and UI knowledge was found at the 2-month follow-up (all P<.05) and 6 weeks post partum (all P<.001).

CONCLUSIONS

The app-based UI self-management intervention (UIW) effectively improved UI symptom severity, quality of life, self-efficacy with PFMT, and knowledge of UI during the late pregnancy and early postnatal periods. Larger multicenter studies with a longer postpartum follow-up are required to further extend these findings.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR1800016171; http://www.chictr.org.cn/showproj.aspx?proj=27455.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/22771.

Lifestyle-related habits and factors before and after cardiovascular diagnosis: a case control study among 2,548 Swedish individuals

BACKGROUND

Healthy lifestyle habits are recommended in prevention of cardiovascular disease (CVD). However, there is limited knowledge concerning the change in lifestyle-related factors from before to after a CVD event. Thus, this study aimed to explore if and how lifestyle habits and other lifestyle-related factors changed between two health assessments in individuals experiencing a CVD event between the assessments, and if changes varied between subgroups of sex, age, educational level, duration from CVD event to second assessment and type of CVD event.

METHODS

Among 115,504 Swedish employees with data from two assessments of occupational health screenings between 1992 and 2020, a total of 637 individuals (74% men, mean age 47 ± SD 9 years) were identified having had a CVD event (ischemic heart disease, cardiac arrythmia or stroke) between the assessments. Cases were matched with controls without an event between assessments from the same database (ratio 1:3, matching with replacement) by sex, age, and time between assessment (n = 1911 controls). Lifestyle habits included smoking, active commuting, exercise, diet, alcohol intake, and were self-rated. Lifestyle-related factors included overall stress, overall health (both self-rated), physical capacity (estimated by submaximal cycling), body mass index and resting blood pressure. Differences in lifestyle habits and lifestyle-related factors between cases and controls, and changes over time, were analysed with parametric and non-parametric tests. Multiple logistic regression, OR (95% CI) was used to analyse differences in change between subgroups.

RESULTS

Cases had, in general, a higher prevalence of unhealthy lifestyle habits as well as negative life-style related factors prior to the event compared to controls. Nevertheless, cases improved their lifestyle habits and lifestyle factors to a higher degree than controls, especially their amount of active commuting (p = 0.025), exercise (p = 0.009) and non-smoking (p < 0.001). However, BMI and overall health deteriorated to a greater extent (p < 0.001) among cases, while physical capacity (p < 0.001) decreased in both groups.

CONCLUSION

The results indicate that a CVD event may increase motivation to improve lifestyle habits. Nonetheless, the prevalence of unhealthy lifestyle habits was still high, emphasizing the need to improve implementation of primary and secondary CVD prevention.

Preferences of Older Adult Veterans With Heart Failure for Engaging With Mobile Health Technology to Support Self-care: Qualitative Interview Study Among Patients With Heart Failure and Content Analysis

BACKGROUND

Heart failure (HF) affects approximately 6.5 million adults in the United States, disproportionately afflicting older adults. Mobile health (mHealth) has emerged as a promising tool to empower older adults in HF self-care. However, little is known about the use of this approach among older adult veterans.

OBJECTIVE

The goal of this study was to explore which features of an app were prioritized for older adult veterans with HF.

METHODS

Between January and July 2021, we conducted semistructured interviews with patients with heart failure aged 65 years and older at a single facility in an integrated health care system (the Veterans Health Administration). We performed content analysis and derived themes based on the middle-range theory of chronic illness, generating findings both deductively and inductively. The qualitative questions captured data on the 3 key themes of the theory: self-care maintenance, self-care monitoring, and self-care management. Qualitative responses were analyzed using a qualitative data management platform, and descriptive statistics were used to analyze demographic data.

RESULTS

Among patients interviewed (n=9), most agreed that a smartphone app for supporting HF self-care was desirable. In addition to 3 a priori themes, we identified 7 subthemes: education on daily HF care, how often to get education on HF, support of medication adherence, dietary restriction support, goal setting for exercises, stress reduction strategies, and prompts of when to call a provider. In addition, we identified 3 inductive themes related to veteran preferences for app components: simplicity, ability to share data with caregivers, and positive framing of HF language.

CONCLUSIONS

We identified educational and tracking app features that can guide the development of HF self-care for an older adult veteran population. Future research needs to be done to extend these findings and assess the feasibility of and test an app with these features.

The digital rainbow: Digital determinants of health inequities

The widely used socioecological rainbow model from Dahlgren and Whitehead specifies determinants of health inequity on multiple hierarchical levels and suggests that these determinants may interact both within and between levels. At the time of its inception, digital determinants only played a minor role in tackling inequities in public health and were therefore not specifically considered. This has dramatically changed: From today's perspective, health inequities increasingly depend on digital determinants. In this article, we suggest adapting the Dahlgren-Whitehead model to reflect these developments. We propose a model that allows formulating testable hypotheses, interpreting research findings, and developing policy implications against the background of the global spread of digital technologies. This may facilitate the development of a new line of research and logic models for public health interventions in the digital age. Using the COVID-19 pandemic as a case study, we illustrate how the digitization of all aspects of life affects the different levels of determinants of health inequities in the Dahlgren-Whitehead model. In doing so, we deliberately argue for not introducing a separate digital sphere in its own right, but for understanding digitization as a phenomenon that permeates all levels of determinants of health inequities. As a result, we present a digital rainbow model that integrates Dahlgren and Whitehead's 1991 model with digital environments to identify current health promotion and research issues without changing the rainbow model's initial structure.