Unraveling Mobile Health Exercise Interventions for Adults: Scoping Review on the Implementations and Designs of Persuasive Strategies

Feasibility and Acceptability of a Mobile Health Exercise Intervention for Inactive Adults: 3-Arm Randomized Controlled Pilot Trial

BACKGROUND

Objective monitoring of self-directed physical activity (PA) is a common approach used in both fitness and health settings to promote exercise behavior, but adherence has been poor. Newer mobile health (mHealth) technologies could be a cost-effective approach to broadening accessibility and providing support for PA behavior change; yet, the optimal method of delivery of such interventions is still unclear.

OBJECTIVE

This study aimed to determine the feasibility and acceptability of an mHealth exercise intervention delivered in combination with objective monitoring in 3 ways: health education emails, asynchronous exercise videos, or synchronous videoconference exercise classes.

METHODS

Physically inactive (<30 min/wk) adults (cisgender women aged 31.5, SD 11.3 years, cisgender men aged 34.1, SD 28.9 years, and nonbinary individuals aged 22.0, SD 0 years) were randomized (1:1:1) to 8 weeks of increasing PA behavioral support: level 1 (health education+objective monitoring, n=26), level 2 (asynchronous contact, level 1+prerecorded exercise videos, n=30), or level 3 (synchronous contact, level 1+videoconference group exercise, n=28). Participants used a heart rate monitor during exercise and a mobile app for interaction. Primary outcomes were feasibility (accrual, retention, and adherence) and acceptability (user experience survey). Secondary outcomes assessed at baseline and 8 weeks included resting heart rate, self-reported PA, and quality of life. The exercise dose was evaluated throughout the intervention.

RESULTS

Between August 2020 and August 2021, 204 adults were screened for eligibility. Out of 135 eligible participants, 84 (62%) enrolled in the study. Retention was 50% (13/26) in level 1, 60% (18/30) in level 2 and 82% (23/28) in level 3, while adherence was 31% (8/26) in level 1, 40% (12/30) in level 2 and 75% (21/28) in level 3. A total of 83% (70/84) of the study sample completed the intervention, but low response rates (64%, 54/84) were observed postintervention at week-8 assessments. Program satisfaction was highest in participants receiving exercise videos (level 2, 80%, 8/10) or exercise classes (level 3, 80%, 12/15), while only 63% (5/8) of level 1 reported the program as enjoyable. Level 3 was most likely to recommend the program (87%, 13/15), compared to 80% (8/10) in level 2 and 46% (5/8) in level 1. Self-reported PA significantly increased from baseline to intervention in level 3 (P<.001) and level 2 (P=.003), with no change in level 1. Level 3 appeared to exercise at higher doses throughout the intervention.

CONCLUSIONS

Only the videoconference exercise class intervention met feasibility criteria, although postintervention response rates were low across all groups. Both videoconference and prerecorded videos had good acceptability, while objective monitoring and health education alone were not feasible or acceptable. Future studies are needed to examine the effectiveness of videoconference exercise interventions on health-related outcomes during nonpandemic times and how asynchronous interventions might maximize adherence.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05192421; https://clinicaltrials.gov/study/NCT05192421.

Effectiveness of a Smartphone App to Promote Physical Activity Among Persons With Type 2 Diabetes: Randomized Controlled Trial

BACKGROUND

Physical activity is well known to have beneficial effects on glycemic control and to reduce risk factors for cardiovascular disease in persons with type 2 diabetes. Yet, successful implementation of lifestyle interventions targeting physical activity in primary care has shown to be difficult. Smartphone apps may provide useful tools to support physical activity. The DiaCert app was specifically designed for integration into primary care and is an automated mobile health (mHealth) solution promoting daily walking.

OBJECTIVE

This study aimed to investigate the effect of a 3-month-long intervention promoting physical activity through the use of the DiaCert app among persons with type 2 diabetes in Sweden. Our primary objective was to assess the effect on moderate to vigorous physical activity (MVPA) at 3 months of follow-up. Our secondary objective was to assess the effect on MVPA at 6 months of follow-up and on BMI, waist circumference, hemoglobin A1c, blood lipids, and blood pressure at 3 and 6 months of follow-up.

METHODS

We recruited men and women with type 2 diabetes from 5 primary health care centers and 1 specialized center. Participants were randomized 1:1 to the intervention or control group. The intervention group was administered standard care and access to the DiaCert app at baseline and 3 months onward. The control group received standard care only. Outcomes of objectively measured physical activity using accelerometers, BMI, waist circumference, biomarkers, and blood pressure were assessed at baseline and follow-ups. Linear mixed models were used to assess differences in outcomes between the groups.

RESULTS

A total of 181 study participants, 65.7% (119/181) men and 34.3% (62/181) women, were recruited into the study and randomized to the intervention (n=93) or control group (n=88). The participants' mean age and BMI were 60.0 (SD 11.4) years and 30.4 (SD 5.3) kg/m2, respectively. We found no significant effect of the intervention (group by time interaction) on MVPA at either the 3-month (β=1.51, 95% CI -5.53 to 8.55) or the 6-month (β=-3.53, 95% CI -10.97 to 3.92) follow-up. We found no effect on any of the secondary outcomes at follow-ups, except for a significant effect on BMI at 6 months (β=0.52, 95% CI 0.20 to 0.84). However, mean BMI did not differ between the groups at the 6-month follow-up.

CONCLUSIONS

We found no evidence that persons with type 2 diabetes being randomized to use an app promoting daily walking increased their levels of MVPA at 3 or 6 months' follow-up compared with controls receiving standard care. The effect of the app on BMI was unclear, and we found nothing to support an effect on secondary outcomes. Further research is needed to determine what type of mHealth intervention could be effective to increase physical activity among persons with type 2 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03053336; https://clinicaltrials.gov/study/NCT03053336.

Adoption, acceptability and sustained use of digital interventions to promote physical activity among inactive adults: a mixed-method study

Introduction

Despite the positive effects of physical activity (PA) to prevent lifestyle diseases and improve health and well-being, only one-third of Norwegian adults meet the minimum recommendations on PA. Digital interventions to promote PA in inactive adults may improve health and well-being by being available, personalized and adequate. Knowledge on users' adoption, acceptability and sustainability of digital interventions to promote PA is still limited.

Objective

To investigate the adoption, acceptability and sustained use of three digital interventions for promoting PA among inactive adults.

Design

A randomized control trial (ONWARDS) with 183 participants assigned to 3 groups and followed up for 18 months. All participants received a wearable activity tracker with the personalized metric Personal Activity Intelligence (PAI) on a mobile app, two groups received additional access to online training and one group had also access to online social support.

Methods

A mixed-methods approach was used to address the study objective. Acceptability was evaluated through the System Usability Scale (SUS) (n = 134) at 6 months. Adoption and sustained use were evaluated through a set of questions administered at 12 months (n = 109). Individual interviews were performed at 6 months with a sample of participants (n = 18). Quantitative data were analyzed with descriptive statistics, whereas qualitative data were analyzed using the Framework approach.

Results

PAI was the most successful intervention, with satisfactory usability and positive effects on motivation and behavior change, contributing to high adoption and sustained use. Online social support had a high acceptability and sustained use, but the intervention was not perceived as motivational to increase PA. Online training had low adoption, usability and sustained use. The qualitative interviews identified five main themes: (1) overall approach to physical activity, (2) motivation, (3) barriers to perform PA, (4) effects of PA, and (5) usability and acceptability of the digital interventions.

Conclusion

Personalized digital interventions integrating behavior change techniques such as individual feedback and goal setting are more likely to increase acceptability, adoption and sustained use. Future studies should investigate which digital interventions or combinations of different interventions are more successful in promoting PA among inactive adults according to the characteristics and preferences of the users.

Trial registration

Clinical trial registered at ClinicalTrials.gov: NCT04526444.

Technological features of smartphone apps for physical activity promotion in patients with COPD: A systematic review

INTRODUCTION

Low physical activity (PA) levels have a negative impact on the health status of patients with Chronic Obstructive Pulmonary Disease (COPD). Smartphone applications (apps) focused on PA promotion may mitigate this problem; however, their effectiveness depends on patient adherence, which can be influenced by the technological features of the apps. This systematic review identified the technological features of smartphone apps aiming to promote PA in patients with COPD.

METHODS

A literature search was performed in the databases ACM Digital Library, IEEE Xplore, PubMed, Scopus and Web of Science. Papers including the description of a smartphone app for PA promotion in patients with COPD were included. Two researchers independently selected studies and scored the apps features based on a previously developed framework (38 possible features).

RESULTS

Twenty-three studies were included and 19 apps identified, with an average of 10 technological features implemented. Eight apps could be connected to wearables to collect data. The categories 'Measuring and monitoring' and 'Support and Feedback' were present in all apps. Overall, the most implemented features were 'progress in visual format' (n = 13), 'advice on PA' (n = 14) and 'data in visual format' (n = 10). Only three apps included social features, and two included a web-based version of the app.

CONCLUSIONS

The existing smartphone apps include a relatively small number of features to promote PA, which are mostly related to monitoring and providing feedback. Further research is warranted to explore the relationship between the presence/absence of specific features and the impact of interventions on patients' PA levels.

A Digital Platform and Smartphone App to Increase Physical Activity in Patients With Type 2 Diabetes: Overview Of a Technical Solution

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s12889-018-5026-4.

Different Approaches to Appraising Systematic Reviews of Digital Interventions for Physical Activity Promotion Using AMSTAR 2 Tool: Cross-Sectional Study

High-quality systematic reviews (SRs) can strengthen the evidence base for prevention and health promotion. A 16-item AMSTAR 2 tool allows the appraisal of SRs by deriving a confidence rating in their results. In this cross-sectional study, we aimed to assess and compare two approaches to appraising 30 SRs of digital interventions for physical activity (PA) promotion using AMSTAR 2. Approach 1 (appraisals with 2/16 items) was used to identify SRs with critically low confidence ratings. Approach 2 (appraisals with all 16 items) was used (1) to derive the confidence ratings, (2) to identify SR strengths and weaknesses, and (3) to compare SR strengths among subgroups of SRs. The appraisal outcomes were summarized and compared using descriptive statistics. Approach 1 was quick (mean of 5 min/SR) at identifying SRs with critically low confidence ratings. Approach 2 was slower (mean of 20 min/SR), but allowed to identify SR strengths and weaknesses. Approach 2 showed that confidence ratings were low to critically low in 29/30 SRs. More strengths were identified in SRs with review protocols relative to SRs without review protocols and in newer SRs (published after AMSTAR 2 release) relative to older SRs. Only two items on AMSTAR 2 can quickly identify SRs with critical weaknesses. Although most SRs received low to critically low confidence ratings, SRs with review protocols and newer SRs tended to have more strengths. Future SRs require review protocols and better adherence to reporting guidelines to improve the confidence in their results.

Design Features Associated With Engagement in Mobile Health Physical Activity Interventions Among Youth: Systematic Review of Qualitative and Quantitative Studies

BACKGROUND

Globally, 81% of youth do not meet the physical activity (PA) guidelines. Youth of families with a low socioeconomic position are less likely to meet the recommended PA guidelines. Mobile health (mHealth) interventions are preferred by youth over traditional in-person approaches and are in line with their media preferences. Despite the promise of mHealth interventions in promoting PA, a common challenge is to engage users in the long term or effectively. Earlier reviews highlighted the association of different design features (eg, notifications and rewards) with engagement among adults. However, little is known about which design features are important for increasing engagement among youth.

OBJECTIVE

To inform the design process of future mHealth tools, it is important to investigate the design features that can yield effective user engagement. This systematic review aimed to identify which design features are associated with engagement in mHealth PA interventions among youth who were aged between 4 and 18 years.

METHODS

A systematic search was conducted in EBSCOhost (MEDLINE, APA PsycINFO, and Psychology & Behavioral Sciences Collection) and Scopus. Qualitative and quantitative studies were included if they documented design features associated with engagement. Design features and related behavior change techniques and engagement measures were extracted. Study quality was assessed according to the Mixed Method Assessment Tool, and one-third of all screening and data extraction were double coded by a second reviewer.

RESULTS

Studies (n=21) showed that various features were associated with engagement, such as a clear interface, rewards, multiplayer game mode, social interaction, variety of challenges with personalized difficulty level, self-monitoring, and variety of customization options among others, including self-set goals, personalized feedback, progress, and a narrative. In contrast, various features need to be carefully considered while designing mHealth PA interventions, such as sounds, competition, instructions, notifications, virtual maps, or self-monitoring, facilitated by manual input. In addition, technical functionality can be considered as a prerequisite for engagement. Research addressing youth from low socioeconomic position families is very limited with regard to engagement in mHealth apps.

CONCLUSIONS

Mismatches between different design features in terms of target group, study design, and content translation from behavior change techniques to design features are highlighted and set up in a design guideline and future research agenda.

TRIAL REGISTRATION

PROSPERO CRD42021254989; https://tinyurl.com/5n6ppz24.

Three levels at which the user's cognition can be represented in artificial intelligence

Artificial intelligence (AI) plays an important role in modern society. AI applications are omnipresent and assist many decisions we make in daily life. A common and important feature of such AI applications are user models. These models allow an AI application to adapt to a specific user. Here, we argue that user models in AI can be optimized by modeling these user models more closely to models of human cognition. We identify three levels at which insights from human cognition can be-and have been-integrated in user models. Such integration can be very loose with user models only being inspired by general knowledge of human cognition or very tight with user models implementing specific cognitive processes. Using AI-based applications in the context of education as a case study, we demonstrate that user models that are more deeply rooted in models of cognition offer more valid and more fine-grained adaptations to an individual user. We propose that such user models can also advance the development of explainable AI.

Preliminary Efficacy, Feasibility, and Perceived Usefulness of a Smartphone-Based Self-Management System with Personalized Goal Setting and Feedback to Increase Step Count among Workers with High Blood Pressure: Before-After Study (Preprint)

BACKGROUND

High blood pressure (BP) and physical inactivity are the major risk factors for cardiovascular diseases. Mobile health is expected to support patients' self-management for improving cardiovascular health; the development of fully automated systems is necessary to minimize the workloads of health care providers.

OBJECTIVE

The objective of our study was to evaluate the preliminary efficacy, feasibility, and perceived usefulness of an intervention using a novel smartphone-based self-management system (DialBetes Step) in increasing steps per day among workers with high BP.

METHODS

On the basis of the Social Cognitive Theory, we developed personalized goal-setting and feedback functions and information delivery functions for increasing step count. Personalized goal setting and feedback consist of 4 components to support users' self-regulation and enhance their self-efficacy: goal setting for daily steps, positive feedback, action planning, and barrier identification and problem-solving. In the goal-setting component, users set their own step goals weekly in gradual increments based on the system's suggestion. We added these fully automated functions to an extant system with the function of self-monitoring daily step count, BP, body weight, blood glucose, exercise, and diet. We conducted a single-arm before-and-after study of workers with high BP who were willing to increase their physical activity. After an educational group session, participants used only the self-monitoring function for 2 weeks (baseline) and all functions of DialBetes Step for 24 weeks. We evaluated changes in steps per day, self-reported frequencies of self-regulation and self-management behavior, self-efficacy, and biomedical characteristics (home BP, BMI, visceral fat area, and glucose and lipid parameters) around week 6 (P1) of using the new functions and at the end of the intervention (P2). Participants rated the usefulness of the system using a paper-based questionnaire.

RESULTS

We analyzed 30 participants (n=19, 63% male; mean age 52.9, SD 5.3 years); 1 (3%) participant dropped out of the intervention. The median percentage of step measurement was 97%. Compared with baseline (median 10,084 steps per day), steps per day significantly increased at P1 (median +1493 steps per day; P<.001), but the increase attenuated at P2 (median +1056 steps per day; P=.04). Frequencies of self-regulation and self-management behavior increased at P1 and P2. Goal-related self-efficacy tended to increase at P2 (median +5%; P=.05). Home BP substantially decreased only at P2. Of the other biomedical characteristics, BMI decreased significantly at P1 (P<.001) and P2 (P=.001), and high-density lipoprotein cholesterol increased significantly only at P1 (P<.001). DialBetes Step was rated as useful or moderately useful by 97% (28/29) of the participants.

CONCLUSIONS

DialBetes Step intervention might be a feasible and useful way of increasing workers' step count for a short period and, consequently, improving their BP and BMI; self-efficacy-enhancing techniques of the system should be improved.

Mobile health platform based on user-centered design to promote exercise for patients with peripheral artery disease

Background

Peripheral artery disease (PAD) is a cardiovascular disease that can be improved by risk factor modification. Mobile health (mHealth) intervention is an effective method of healthcare delivery to promote behavior changes. An mHealth platform can encourage consistent involvement of participants and healthcare providers for health promotion. This study aimed to develop an mHealth platform consisting of a smartphone application (app) synchronized with a wearable activity tracker and a web-based portal to support exercise intervention in patients with PAD.

Methods

This study was conducted based on an iterative development process, including analysis, design, and implementation. In the analysis phase, a literature review and needs assessment through semi-structured interviews (n = 15) and a questionnaire-based survey (n = 138) were performed. The initial prototype design and contents were developed based on the users’ requirements. In the implementation phase, multidisciplinary experts (n = 4) evaluated the heuristics, following which the mHealth platform was revised. User evaluation of the usability was performed by nurses (n = 4) and patients with PAD (n = 3).

Results

Through the development process, the functional requirements of the platform were represented through visual display, reminder, education, self-monitoring, goal setting, goal attainment, feedback, and recording. In-app videos of exercise and PAD management were produced to provide information and in-app automatic text messages were developed for user motivation. The final version of the platform was rated 67.86 out of 100, which indicated “good” usability.

Conclusions

The mHealth platform was designed and developed for patients with PAD and their healthcare providers. This platform can be used to educate and promote individualized exercise among patients with PAD.

Just-in-Time Prompts for Running, Walking, and Performing Strength Exercises in the Built Environment: 4-Week Randomized Feasibility Study

Background

App-based mobile health exercise interventions can motivate individuals to engage in more physical activity (PA). According to the Fogg Behavior Model, it is important that the individual receive prompts at the right time to be successfully persuaded into PA. These are referred to as just-in-time (JIT) interventions. The Playful Active Urban Living (PAUL) app is among the first to include 2 types of JIT prompts: JIT adaptive reminder messages to initiate a run or walk and JIT strength exercise prompts during a walk or run (containing location-based instruction videos). This paper reports on the feasibility of the PAUL app and its JIT prompts.

Objective

The main objective of this study was to examine user experience, app engagement, and users’ perceptions and opinions regarding the PAUL app and its JIT prompts and to explore changes in the PA behavior, intrinsic motivation, and the perceived capability of the PA behavior of the participants.

Methods

In total, 2 versions of the closed-beta version of the PAUL app were evaluated: a basic version (Basic PAUL) and a JIT adaptive version (Smart PAUL). Both apps send JIT exercise prompts, but the versions differ in that the Smart PAUL app sends JIT adaptive reminder messages to initiate running or walking behavior, whereas the Basic PAUL app sends reminder messages at randomized times. A total of 23 participants were randomized into 1 of the 2 intervention arms. PA behavior (accelerometer-measured), intrinsic motivation, and the perceived capability of PA behavior were measured before and after the intervention. After the intervention, participants were also asked to complete a questionnaire on user experience, and they were invited for an exit interview to assess user perceptions and opinions of the app in depth.

Results

No differences in PA behavior were observed (Z=−1.433; P=.08), but intrinsic motivation for running and walking and for performing strength exercises significantly increased (Z=−3.342; P<.001 and Z=−1.821; P=.04, respectively). Furthermore, participants increased their perceived capability to perform strength exercises (Z=2.231; P=.01) but not to walk or run (Z=−1.221; P=.12). The interviews indicated that the participants were enthusiastic about the strength exercise prompts. These were perceived as personal, fun, and relevant to their health. The reminders were perceived as important initiators for PA, but participants from both app groups explained that the reminder messages were often not sent at times they could exercise. Although the participants were enthusiastic about the functionalities of the app, technical issues resulted in a low user experience.

Conclusions

The preliminary findings suggest that the PAUL apps are promising and innovative interventions for promoting PA. Users perceived the strength exercise prompts as a valuable addition to exercise apps. However, to be a feasible intervention, the app must be more stable.

Evaluation of Digital Interventions for Physical Activity Promotion: Scoping Review

Background

Digital interventions are interventions supported by digital tools or technologies, such as mobile apps, wearables, or web-based software. Digital interventions in the context of public health are specifically designed to promote and improve health. Recent reviews have shown that many digital interventions target physical activity promotion; however, it is unclear how such digital interventions are evaluated.

Objective

We aimed to investigate evaluation strategies in the context of digital interventions for physical activity promotion using a scoping review of published reviews. We focused on the target (ie, user outcomes or tool performance), methods (ie, tool data or self-reported data), and theoretical frameworks of the evaluation strategies.

Methods

A protocol for this study was preregistered and published. From among 300 reviews published up to March 19, 2021 in Medline, PsycINFO, and CINAHL databases, 40 reviews (1 rapid, 9 scoping, and 30 systematic) were included in this scoping review. Two authors independently performed study selection and data coding. Consensus was reached by discussion. If applicable, data were coded quantitatively into predefined categories or qualitatively using definitions or author statements from the included reviews. Data were analyzed using either descriptive statistics, for quantitative data (relative frequencies out of all studies), or narrative synthesis focusing on common themes, for qualitative data.

Results

Most reviews that were included in our scoping review were published in the period from 2019 to 2021 and originated from Europe or Australia. Most primary studies cited in the reviews included adult populations in clinical or nonclinical settings, and focused on mobile apps or wearables for physical activity promotion. The evaluation target was a user outcome (efficacy, acceptability, usability, feasibility, or engagement) in 38 of the 40 reviews or tool performance in 24 of the 40 reviews. Evaluation methods relied upon objective tool data (in 35/40 reviews) or other data from self-reports or assessments (in 28/40 reviews). Evaluation frameworks based on behavior change theory, including goal setting, self-monitoring, feedback on behavior, and educational or motivational content, were mentioned in 22 out of 40 reviews. Behavior change theory was included in the development phases of digital interventions according to the findings of 20 out of 22 reviews.

Conclusions

The evaluation of digital interventions is a high priority according to the reviews included in this scoping review. Evaluations of digital interventions, including mobile apps or wearables for physical activity promotion, typically target user outcomes and rely upon objective tool data. Behavior change theory may provide useful guidance not only for development of digital interventions but also for the evaluation of user outcomes in the context of physical activity promotion. Future research should investigate factors that could improve the efficacy of digital interventions and the standardization of terminology and reporting in this field.

International Registered Report Identifier (IRRID)

RR2-10.2196/35332

Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Results From a 2-Month Randomized Controlled Trial

Background

Although the health benefits of physical activity are well established, it remains challenging for people to adopt a more active lifestyle. Mobile health (mHealth) interventions can be effective tools to promote physical activity and reduce sedentary behavior. Promising results have been obtained by using gamification techniques as behavior change strategies, especially when they were tailored toward an individual’s preferences and goals; yet, it remains unclear how goals could be personalized to effectively promote health behaviors.

Objective

In this study, we aim to evaluate the impact of personalized goal setting in the context of gamified mHealth interventions. We hypothesize that interventions suggesting health goals that are tailored based on end users’ (self-reported) current and desired capabilities will be more engaging than interventions with generic goals.

Methods

The study was designed as a 2-arm randomized intervention trial. Participants were recruited among staff members of 7 governmental organizations. They participated in an 8-week digital health promotion campaign that was especially designed to promote walks, bike rides, and sports sessions. Using an mHealth app, participants could track their performance on two social leaderboards: a leaderboard displaying the individual scores of participants and a leaderboard displaying the average scores per organizational department. The mHealth app also provided a news feed that showed when other participants had scored points. Points could be collected by performing any of the 6 assigned tasks (eg, walk for at least 2000 m). The level of complexity of 3 of these 6 tasks was updated every 2 weeks by changing either the suggested task intensity or the suggested frequency of the task. The 2 intervention arms—with participants randomly assigned—consisted of a personalized treatment that tailored the complexity parameters based on participants’ self-reported capabilities and goals and a control treatment where the complexity parameters were set generically based on national guidelines. Measures were collected from the mHealth app as well as from intake and posttest surveys and analyzed using hierarchical linear models.

Results

The results indicated that engagement with the program inevitably dropped over time. However, engagement was higher for participants who had set themselves a goal in the intake survey. The impact of personalization was especially observed for frequency parameters because the personalization of sports session frequency did foster higher engagement levels, especially when participants set a goal to improve their capabilities. In addition, the personalization of suggested ride duration had a positive effect on self-perceived biking performance.

Conclusions

Personalization seems particularly promising for promoting the frequency of physical activity (eg, promoting the number of suggested sports sessions per week), as opposed to the intensity of the physical activity (eg, distance or duration). Replications and variations of our study setup are critical for consolidating and explaining (or refuting) these effects.

Trial Registration

ClinicalTrials.gov NCT05264155; https://clinicaltrials.gov/ct2/show/NCT05264155

Evaluation of Digital Interventions for Physical Activity Promotion: Protocol for a Scoping Review

Background

Digital interventions (DIs) could support physical activity (PA) promotion, according to recent reviews. However, it remains unclear if and how DIs for PA promotion are evaluated; thus, it is unclear if they support behavior change in real-world settings. A mapping of evidence from published reviews is required to focus on the evaluation of DIs for PA promotion.

Objective

The aim of our study is to investigate evaluation strategies for any outcome in the context of DIs for PA promotion by conducting a scoping review of published reviews.

Methods

Our scoping review adheres to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The information sources include bibliographic databases (MEDLINE, PsycINFO, and CINAHL) and the bibliographies of the selected studies. The electronic search strategy was developed and conducted in collaboration with an experienced database specialist. The electronic search was conducted in English with no limits up to March 19, 2021, for sources with the terms digital intervention AND evaluation AND physical activity in titles or abstracts. After deduplication, 300 reviews selected from 4912 search results were assessed for eligibility by 2 authors working independently. The inclusion criteria were (1) healthy or clinical samples (population), (2) DIs for PA promotion (intervention), (3) comparisons to any other intervention or no intervention (comparison), (4) evaluation strategies (methods, results, or frameworks) for any outcome in the context of DIs for PA promotion (outcome), and (5) any published review (study type). According to the consensus reached during a discussion, 40 reviews met the inclusion criteria—36 from the electronic search and 4 from the manual search of the bibliographies of the 36 reviews. All reviews reported the evaluation strategies for any outcomes in the context of DIs for PA promotion in healthy or clinical samples. Data coding and the quality appraisal of systematic reviews are currently being performed independently by 2 authors.

Results

Our scoping review includes data from 40 published reviews (1 rapid review, 9 scoping reviews, and 30 systematic reviews). The focus of data coding is on evaluation strategies in the context of DIs for PA promotion and on the critical appraisal of the included systematic reviews. The final consensus regarding all data is expected in early 2022.

Conclusions

Interventions for PA promotion that are supported by digital technologies require evaluation to ensure their efficacy in real-world settings. Our scoping review is needed because it addresses novel objectives that focus on such evaluations and are not answered in the published reviews identified in our search. The evaluation strategies addressing DIs for PA promotion will be mapped to synthesize the results that have been reported in published reviews so far.

International Registered Report Identifier (IRRID)

DERR1-10.2196/35332

Combining Persuasive System Design Principles and Behavior Change Techniques in Digital Interventions Supporting Long-term Weight Loss Maintenance: Design and Development of eCHANGE (Preprint)

Background

Long-term weight maintenance after weight loss is challenging, and innovative solutions are required. Digital technologies can support behavior change and, therefore, have the potential to be an effective tool for weight loss maintenance. However, to create meaningful and effective digital behavior change interventions that support end user values and needs, a combination of persuasive system design (PSD) principles and behavior change techniques (BCTs) might be needed.

Objective

This study aimed to investigate how an evidence-informed digital behavior change intervention can be designed and developed by combining PSD principles and BCTs into design features to support end user values and needs for long-term weight loss maintenance.

Methods

This study presents a concept for how PSD principles and BCTs can be translated into design features by combining design thinking and Agile methods to develop and deliver an evidence-informed digital behavior change intervention aimed at supporting weight maintenance. Overall, 45 stakeholders participated in the systematic and iterative development process comprising co-design workshops, prototyping, Agile development, and usability testing. This included prospective end users (n=17, 38%; ie, people with obesity who had lost ≥8% of their weight), health care providers (n=9, 20%), healthy volunteers (n=4, 9%), a service designer (n=1, 2%), and stakeholders from the multidisciplinary research and development team (n=14, 31%; ie, software developers; digital designers; and eHealth, behavior change, and obesity experts). Stakeholder input on how to operationalize the design features and optimize the technology was examined through formative evaluation and qualitative analyses using rapid and in-depth analysis approaches.

Results

A total of 17 design features combining PSD principles and BCTs were identified as important to support end user values and needs based on stakeholder input during the design and development of eCHANGE, a digital intervention to support long-term weight loss maintenance. The design features were combined into 4 main intervention components: Week Plan, My Overview, Knowledge and Skills, and Virtual Coach and Smart Feedback System. To support a healthy lifestyle and continued behavior change to maintain weight, PSD principles such as tailoring, personalization, self-monitoring, reminders, rewards, rehearsal, praise, and suggestions were combined and implemented into the design features together with BCTs from the clusters of goals and planning, feedback and monitoring, social support, repetition and substitution, shaping knowledge, natural consequences, associations, antecedents, identity, and self-belief.

Conclusions

Combining and implementing PSD principles and BCTs in digital interventions aimed at supporting sustainable behavior change may contribute to the design of engaging and motivating interventions in line with end user values and needs. As such, the design and development of the eCHANGE intervention can provide valuable input for future design and tailoring of evidence-informed digital interventions, even beyond digital interventions in support of health behavior change and long-term weight loss maintenance.

Trial Registration

ClinicalTrials.gov NCT04537988; https://clinicaltrials.gov/ct2/show/NCT04537988

Digitization and Health in Germany: Cross-sectional Nationwide Survey

Background

Digital technologies are shaping medicine and public health.

Objective

The aim of this study was to investigate the attitudes toward and the use of digital technologies for health-related purposes using a nationwide survey.

Methods

We performed a cross-sectional study using a panel sample of internet users selected from the general population living in Germany. Responses to a survey with 28 items were collected using computer-assisted telephone interviews conducted in October 2020. The items were divided into four topics: (1) general attitudes toward digitization, (2) COVID-19 pandemic, (3) physical activity, and (4) perceived digital health (eHealth) literacy measured with the eHealth Literacy Scale (eHEALS; sum score of 8=lowest to 40=highest perceived eHealth literacy). The data were analyzed in IBM-SPSS24 using relative frequencies. Three univariate multiple regression analyses (linear or binary logistic) were performed to investigate the associations among the sociodemographic factors (age, gender, education, and household income) and digital technology use.

Results

The participants included 1014 internet users (n=528, 52.07% women) aged 14 to 93 years (mean 54, SD 17). Among all participants, 66.47% (674/1014) completed up to tertiary (primary and secondary) education and 45.07% (457/1017) reported a household income of up to 3500 Euro/month (1 Euro=US $1.18). Over half (579/1014, 57.10%) reported having used digital technologies for health-related purposes. The majority (898/1014, 88.56%) noted that digitization will be important for therapy and health care, in the future. Only 25.64% (260/1014) reported interest in smartphone apps for health promotion/prevention and 42.70% (433/1014) downloaded the COVID-19 contact-tracing app. Although 52.47% (532/1014) reported that they come across inaccurate digital information on the COVID-19 pandemic, 78.01% (791/1014) were confident in their ability to recognize such inaccurate information. Among those who use digital technologies for moderate physical activity (n=220), 187 (85.0%) found such technologies easy to use and 140 (63.6%) reported using them regularly (at least once a week). Although the perceived eHealth literacy was high (eHEALS mean score 31 points, SD 6), less than half (43.10%, 400/928) were confident in using digital information for health decisions. The use of digital technologies for health was associated with higher household income (odds ratio [OR] 1.28, 95% CI 1.11-1.47). The use of digital technologies for physical activity was associated with younger age (OR 0.95, 95% CI 0.94-0.96) and more education (OR 1.22, 95% CI 1.01-1.46). A higher perceived eHealth literacy score was associated with younger age (β=–.22, P<.001), higher household income (β=.21, P<.001), and more education (β=.14, P<.001).

Conclusions

Internet users in Germany expect that digitization will affect preventive and therapeutic health care in the future. The facilitators and barriers associated with the use of digital technologies for health warrant further research. A gap exists between high confidence in the perceived ability to evaluate digital information and low trust in internet-based information on the COVID-19 pandemic and health decisions.

Short and Long-Term Innovations on Dietary Behavior Assessment and Coaching: Present Efforts and Vision of the Pride and Prejudice Consortium

Overweight, obesity and cardiometabolic diseases are major global health concerns. Lifestyle factors, including diet, have been acknowledged to play a key role in the solution of these health risks. However, as shown by numerous studies, and in clinical practice, it is extremely challenging to quantify dietary behaviors as well as influencing them via dietary interventions. As shown by the limited success of 'one-size-fits-all' nutritional campaigns catered to an entire population or subpopulation, the need for more personalized coaching approaches is evident. New technology-based innovations provide opportunities to further improve the accuracy of dietary assessment and develop approaches to coach individuals towards healthier dietary behaviors. Pride & Prejudice (P&P) is a unique multi-disciplinary consortium consisting of researchers in life, nutrition, ICT, design, behavioral and social sciences from all four Dutch Universities of Technology. P&P focuses on the development and integration of innovative technological techniques such as artificial intelligence (AI), machine learning, conversational agents, behavior change theory and personalized coaching to improve current practices and establish lasting dietary behavior change.

Evaluation of Web-Based and In-Person Methods to Recruit Adults With Type 1 Diabetes for a Mobile Exercise Intervention: Prospective Observational Study

BACKGROUND

Our clinical trial of a mobile exercise intervention for adults 18 to 65 years old with type 1 diabetes (T1D) occurred during COVID-19 social distancing restrictions, prompting us to test web-based recruitment methods previously underexplored for this demographic.

OBJECTIVE

Our objectives for this study were to (1) evaluate the effectiveness and cost of using social media news feed advertisements, a clinic-based approach method, and web-based snowball sampling to reach inadequately active adults with T1D and (2) compare characteristics of enrollees against normative data.

METHODS

Participants were recruited between November 2019 and August 2020. In method #1, Facebook and Instagram news feed advertisements ran for five 1-to-8-day windows targeting adults (18 to 64 years old) in the greater New Haven and Hartford, Connecticut, areas with one or more diabetes-related profile interest. If interested, participants completed a webform so that the research team could contact them for eligibility screening. In method #2, patients 18 to 24 years old with T1D were approached in person at clinical visits in November and December 2019. Those who were interested immediately completed eligibility screening. Older patients could not be approached due to clinic restrictions. In method #3, snowball sampling was conducted by physically active individuals with T1D contacting their peers on Facebook and via email for 48 days, with details to contact the research staff to express interest and complete eligibility screening. Other methods referred participants to the study similarly to snowball sampling.

RESULTS

In method #1, advertisements were displayed to 11,738 unique viewers and attracted 274 clickers (2.33%); 20 participants from this group (7.3%) volunteered, of whom 8 (40%) were eligible. Costs averaged US $1.20 per click and US $95.88 per eligible volunteer. Men had lower click rates than women (1.71% vs 3.17%; P<.001), but their responsiveness and eligibility rates did not differ. In method #2, we approached 40 patients; 32 of these patients (80%) inquired about the study, of whom 20 (63%) volunteered, and 2 of these volunteers (10%) were eligible. Costs including personnel for in-person approaches averaged US $21.01 per inquirer and US $479.79 per eligible volunteer. In method #3, snowball sampling generated 13 inquirers; 12 of these inquirers (92%) volunteered, of whom 8 (67%) were eligible. Incremental costs to attract inquirers were negligible, and total costs averaged US $20.59 per eligible volunteer. Other methods yielded 7 inquirers; 5 of these inquirers (71%) volunteered, of whom 2 (40%) were eligible. Incremental costs to attract inquirers were negligible, and total costs averaged US $34.94 per eligible volunteer. Demographic overrepresentations emerged in the overall cohort (ie, optimal glycemic control, obesity, and low exercise), among those recruited by news feed advertisements (ie, obesity and older age), and among those recruited by snowball sampling (ie, optimal glycemic control and low exercise).

CONCLUSIONS

Web-based advertising and recruitment strategies are a promising means to attract adults with T1D to clinical trials and exercise interventions, with costs comparing favorably to prior trials despite targeting an uncommon condition (ie, T1D) and commitment to an intervention. These strategies should be tailored in future studies to increase access to higher-risk participants.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04204733; https://clinicaltrials.gov/ct2/show/NCT04204733.

A Focus Group Study Among Inactive Adults Regarding the Perceptions of a Theory-Based Physical Activity App

Background: Despite the increasing attention for the positive effects of physical activity (PA), nearly half of the Dutch citizens do not meet the national PA guidelines. A promising method for increasing PA are mobile exercise applications (apps), especially if they are embedded with theoretically supported persuasive strategies (e.g., goal setting and feedback) that align with the needs and wishes of the user. In addition, it is argued that the operationalization of the persuasive strategies could increase the effectiveness of the app, such as the actual content or visualization of feedback. Although much research has been done to examine the preferences for persuasive strategies, little is known about the needs, wishes, and preferences for the design and operationalization of persuasive strategies.

Objective: The purpose of this study was to get insight in the needs, wishes, and preferences regarding the practical operationalization of persuasive strategies in a mobile application aimed at promoting PA in healthy inactive adults.

Methods: Five semistructured focus groups were performed. During the focus groups, the participants were led into a discussion about the design and operationalization of six predefined theory-based persuasive strategies (e.g., self-monitoring, feedback, goal setting, reminders, rewards, and social support) directed by two moderators. The audio-recorded focus groups were transcribed verbatim and analyzed following the framework approach.

Results: Eight men and 17 women between 35 and 55 years (mean age, 49.2) participated in the study. Outcomes demonstrated diverse preferences for implementation types and design characteristics of persuasive strategies in mobile applications. Basic statistics (such as distance, time and calories), positive feedback based on easy-to-achieve goals that relate to health guidelines, and motivating reminders on a relevant moment were preferred. Participants had mixed preferences regarding rewards and a social platform to invite other users to join PA.

Conclusions: Findings indicated that in mHealth applications for healthy but inactive adults, persuasive strategies should be designed and implemented in a way that they relate to health guidelines. Moreover, there is a need for an app that can be adapted or can learn based on personal preferences as, for example, preferences with regard to timing of feedback and reminders differed between people.

The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining

Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for developing personalized apps. In this paper, we describe the design and development of the Playful data-driven Active Urban Living (PAUL): a personalized PA application.

Methods: The two-phased development process of the PAUL apps rests on principles from the behavior change model; the Integrate, Design, Assess, and Share (IDEAS) framework; and the behavioral intervention technology (BIT) model. During the first phase, we explored whether location-specific information on performing PA in the built environment is an enhancement to a PA app. During the second phase, the other modules of the app were developed. To this end, we first build the theoretical foundation for the PAUL intervention by performing a literature study. Next, a focus group study was performed to translate the theoretical foundations and the needs and wishes in a set of user requirements. Since the participants indicated the need for reminders at a for-them-relevant moment, we developed a self-learning module for the timing of the reminders. To initialize this module, a data-mining study was performed with historical running data to determine good situations for running.

Results: The results of these studies informed the design of a personalized mobile health (mHealth) application for running, walking, and performing strength exercises. The app is implemented as a set of modules based on the persuasive strategies “monitoring of behavior,” “feedback,” “goal setting,” “reminders,” “rewards,” and “providing instruction.” An architecture was set up consisting of a smartphone app for the user, a back-end server for storage and adaptivity, and a research portal to provide access to the research team.

Conclusions: The interdisciplinary research encompassing psychology, human movement sciences, computer science, and artificial intelligence has led to a theoretically and empirically driven leisure time PA application. In the current phase, the feasibility of the PAUL app is being assessed.