A Web-Based, Social Networking Physical Activity Intervention for Insufficiently Active Adults Delivered via Facebook App: Randomized Controlled Trial

The effectiveness of internet-based group behavioural interventions on lifestyle modifications: A systematic review

OBJECTIVES

To examine the effectiveness of internet-based group interventions incorporating social support elements in addressing behaviours related to smoking, nutrition, alcohol consumption, physical activity, and obesity.

METHODS

A literature search was undertaken in six databases from inception to April 2024. Articles were eligible if they reported on group-based online interventions targeting smoking, nutrition, alcohol consumption, physical activity, and obesity, and included interactive features aimed at promoting social engagement and support. Two reviewers independently screened and assessed the quality of articles using Joanna Briggs Institute Critical Appraisal tools. A narrative analysis was used to synthesize and interpret the data to understand the effects of online interventions on lifestyle modifications.

RESULTS

A total of 4063 citations underwent screening, resulting in 32 articles being deemed eligible and included in this review. Most studies examined physical activity (n = 14), followed by obesity (n = 7) and smoking (n = 6), Most studies were conducted in the USA (n = 14) and Australia (n = 11). Websites were the most utilised mode of intervention delivery (n = 11), followed by Facebook (n = 7) and mobile apps (n = 5). Group-based internet interventions were effective in improving smoking cessation, increasing physical activity and addressing obesity. However, there is insufficient data to determine their effect on promoting healthy nutrition and reducing alcohol intake.

CONCLUSION

Group-based interventions delivered on the internet are effective in changing various health behaviours. This approach can offer large scale and cost-effective means to deliver behavioural interventions. However, the long-term effects and strategies for maintaining the behaviour changes are lacking, underscoring the need for further research.

Improving physical activity among prostate cancer survivors through a peer-based digital walking program

Physical activity is important for prostate cancer survivors. Yet survivors face significant barriers to traditional structured exercise programs, limiting engagement and impact. Digital programs that incorporate fitness trackers and peer support via social media have potential to improve the reach and impact of traditional support. Using a digital walking program with prostate cancer survivors, we employed mixed methods to assess program outcomes, engagement, perceived utility, and social influence. After 6 weeks of program use, survivors and loved ones (n=18) significantly increased their average daily step count. Although engagement and perceived utility of using a fitness tracker and interacting with walking buddies was high, social media engagement and utility were limited. Group strategies associated with social influence were driven more by group attraction to the collective task of walking than by interpersonal bonds. Findings demonstrate the feasibility of a digital walking program to improve physical activity and extend the reach of traditional support.

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.

Harnessing technology and gamification to increase adult physical activity: a cluster randomized controlled trial of the Columbia Moves pilot

BACKGROUND

The use of health technologies and gamification to promote physical activity has increasingly been examined, representing an opportunistic method for harnessing social support inherent within existing social ties. However, these prior studies have yielded mixed findings and lacked long-term follow-up periods. Thus, a pilot cluster randomized controlled trial was conducted to gauge the feasibility and preliminary efficacy of a digital gamification-based physical activity promotion approach among teams of insufficiently active adults with existing social ties.

METHODS

Teams (N = 24; 116 total participants) were randomized to either a 12-week intervention (Fitbit, step goals, app, feedback; TECH) or the same program plus gamification (TECH + Gamification). Mixed effects models were used to compare group differences in treatment adherence, and changes in social support, steps, and moderate-to-vigorous physical activity at 12 weeks and 52 weeks from baseline, adjusted for sociodemographic characteristics and team size.

RESULTS

TECH had a lower mean number of days of Fitbit self-monitoring versus TECH + Gamification during the intervention (adjusted difference: -.30; 95% CI, -.54 to -.07; P = .01). Post-intervention, TECH had 47% lower odds of self-monitoring 7 days per week versus TECH + Gamification (.53; 95% CI, .31 to .89; P = .02). No differences were observed between TECH + Gamification and TECH in increases in social support (0.04; 95% CI, -.21 to .29; P = .76), ActiGraph-measured daily steps (-425; 95% CI, -1065 to 215; P = .19), or moderate-to-vigorous physical activity minutes (-3.36; 95% CI, -8.62 to 1.91; P = .21) from baseline to 12 weeks or in the regression of these improvements by 1 year (Ps > .05). Although not significant in the adjusted models (Ps > .05), clinically meaningful differences in Fitbit-measured daily steps (TECH, 7041 ± 2520; TECH + Gamification, 7988 ± 2707) and active minutes (TECH, 29.90 ± 29.76; TECH + Gamification, 36.38 ± 29.83) were found during the intervention.

CONCLUSIONS

A gamified physical activity intervention targeting teams of adults with existing social ties was feasible and facilitated favorable, clinically meaningful additive physical activity effects while in place but did not drive enhanced, long-term physical activity participation. Future investigations should explore optimal team dynamics and more direct ways of leveraging social support (training teams; gamifying social support).

TRIAL REGISTRATION

Clinicaltrials.gov ( NCT03509129 , April 26, 2018).

The Impact of Social Media Interventions on Weight Reduction and Physical Activity Improvement Among Healthy Adults: Systematic Review

BACKGROUND

A sedentary lifestyle and being overweight or obese are well-established cardiovascular risk factors and contribute substantially to the global burden of disease. Changing such behavior is complex and requires support. Social media interventions show promise in supporting health behavior change, but their impact is unclear. Moreover, previous reviews have reported contradictory evidence regarding the relationship between engagement with social media interventions and the efficacy of these interventions.

OBJECTIVE

This review aimed to critically synthesize available evidence regarding the impact of social media interventions on physical activity and weight among healthy adults. In addition, this review examined the effect of engagement with social media interventions on their efficacy.

METHODS

CINAHL and MEDLINE were searched for relevant randomized trials that were conducted to investigate the impact of social media interventions on weight and physical activity and were published between 2011 and 2021 in the English language. Studies were included if the intervention used social media tools that provided explicit interactions between the participants. Studies were excluded if the intervention was passively delivered through an app website or if the participants had a known chronic disease. Eligible studies were appraised for quality and synthesized using narrative synthesis.

RESULTS

A total of 17 papers reporting 16 studies from 4 countries, with 7372 participants, were identified. Overall, 56% (9/16) of studies explored the effect of social media interventions on physical activity; 38% (6/16) of studies investigated weight reduction; and 6% (1/16) of studies assessed the effect on both physical activity and weight reduction. Evidence of the effects of social media interventions on physical activity and weight loss was mixed across the included studies. There were no standard metrics for measuring engagement with social media, and the relationship between participant engagement with the intervention and subsequent behavior change was also mixed. Although 35% (6/16) of studies reported that engagement was not a predictor of behavior change, engagement with social media interventions was found to be related to behavior change in 29% (5/16) of studies.

CONCLUSIONS

Despite the promise of social media interventions, evidence regarding their effectiveness is mixed. Further robust studies are needed to elucidate the components of social media interventions that lead to successful behavior change. Furthermore, the effect of engagement with social media interventions on behavior change needs to be clearly understood.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022311430; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=311430.

Mobile Digital Health Intervention to Promote Nutrition and Physical Activity Behaviors Among Long-term Unemployed in Rural Areas: Protocol for a Randomized Controlled Trial

Background

Long-term unemployed have poor nutritional and physical activity statuses, and, therefore, special health promotion needs. Particularly in rural areas, however, they often do not have access to health promotion service. Thus, new promising strategies to improve the health of long-term unemployed are needed. Hence, a digital health intervention to promote nutritional and physical health behaviors was conceived, and the effectiveness of the intervention in combination with face-to-face sessions will be evaluated in a randomized controlled trial.

Objective

The aim of this study is to elucidate the effectiveness of a mobile digital health intervention to promote the nutritional and physical activity behaviors of long-term unemployed in the rural areas of Germany.

Methods

The 9-week intervention aims to promote nutritional or physical activity behavior by improving drinking habits, increasing the consumption of fruits, vegetables, and whole grains, increasing daily step count, strengthening muscles, and improving endurance. The intervention design is based on the transtheoretical model and is implemented in a mobile app using the MobileCoach open-source platform. The effectiveness of the intervention will be elucidated by a 9-week, 2-armed, parallel-designed trial. Therefore, long-term unemployed will be recruited by employees of the German social sector institutions and randomized either to receive information brochures; the digital intervention in the form of a mobile app; and 3 face-to-face sessions regarding technical support, healthy eating, and physical activity (n=100) or to receive a control treatment consisting of solely the hand over of information brochures (n=100). The effectiveness of the intervention will be assessed using questionnaires at baseline, after 9 weeks in face-to-face appointments, and after a 3-month follow-up period by postal contact. The use of the mobile app will be monitored, and qualitative interviews or focus groups with the participants will be conducted. Incentives of €50 (US $49.7) will be paid to the participants and are tied to the completion of the questionnaires and not to the use of the mobile app or progress in the intervention.

Results

The effectiveness of the intervention in promoting the nutritional and physical activity behaviors of long-term unemployed participants will be elucidated. The adherence of the participants to and the acceptance and usability of the mobile device app will be evaluated. Recruitment started in March 2022, and the final publication of the results is expected in the first half of 2023.

Conclusions

Positive health-related changes made by the intervention would display the potency of digital health interventions to promote nutritional and physical activity behaviors among long-term unemployed in the rural areas of Germany, which would also contribute to an improved health status of the German population in general.

Trial Registration

German Clinical Trials Register DRKS00024805; https://www.drks.de/DRKS00024805

International Registered Report Identifier (IRRID)

PRR1-10.2196/40321

Relationship between internet use intensity and quality of life in chronic patients during the COVID-19 pandemic: The role of physical exercise and health insurance

The internet use intensity of human has increased substantially during the COVID-19 Pandemic, and it is severely impacting the well-being of chronic patients. This study aimed to explore the underlying mechanism of the relationship between internet use intensity and quality of life in chronic patients, based on the cross-sectional data from China Family Panel Studies (CFPS) during the COVID-19 Pandemic in 2020. The results showed that the internet use intensity had significant positive association with quality of life among chronic patients, and such association has been found in both urban and rural samples. Among the relationship of internet use intensity and quality of life in chronic patients, the mediating effect of physical exercise reached 10.25%. Furthermore, health insurance positively moderated this relationship. There are new insights for policy recommendations and clinical guidance on the role of physical activity and health insurance aimed at improving chronic patients' quality of life. Meanwhile, in both rural and urban governance, public health agencies should promote the "Internet + Healthcare" program to improve health insurance and physical activity literacy, thus providing a higher level of quality of life for patients with chronic diseases during the COVID-19 Pandemic.

Exploring the effectiveness of a fitness-app prototype for home care service users in Austria and Italy

An infinite number of fitness apps are available on various app stores. However, hardly any of them are fitted to the needs and requirements of care-dependent people. This paper investigates the effectiveness of a customised fitness-app prototype for increasing physical activity in home care service users. Home care service users from Austria and Italy were randomly assigned to two groups. In total, 216 participants were involved in the field trial, 104 received a tablet with the fitness app and an activity tracker (treatment group), 112 did not (control group). Regularity of physical activity, frequency of fitness exercises and walking behaviour were self-reported by participants at baseline, after 4 months and after 8 months. In addition, the frequency of using the prototype was assessed based on the fitness app's logged usage data. We estimated multilevel mixed-effects ordered logistic models to examine the effects of the intervention. After 4 months, the intervention increased the home care users' probability of agreeing strongly with being physically active on a regular basis by 28 percentage points (p < 0.001; 95% CI: 0.20, 0.36) and their probability of reporting to exercise more than once a week by 45 percentage points (p < 0.001; 95% CI: 0.32, 0.57). Walking behaviour was not affected on group-level but improved for frequent users of the activity tracker. Frequent and regular users of the fitness app benefited most and effects persisted until the end of the 8 months controlled trial. Tailoring a fitness-app prototype to the needs of care-dependent people has the potential to support people with functional limitations to engage in a more active lifestyle. Future research is encouraged to seek further insights into how new technologies can support physical activities in people with long-term care needs.

The Role of Facebook® in Promoting a Physically Active Lifestyle: A Systematic Review and Meta-Analysis

BACKGROUND

it is well known in literature that sedentary lifestyle contributes to worsening people's health. This issue highlights the need for effective interventions to promote an active lifestyle. Research suggested multilevel intervention strategies to promote adherence to recommended physical activity levels, including the use of social networks that may simplify access to health notions. Being Facebook^® the most extensive worldwide social network, this document aimed to analyze the current body of evidence on the role of Facebook^® in the promotion of physical activity.

METHODS

eighteen manuscripts were considered eligible for this systematic review, and it was performed a meta-analysis (PRISMA guidelines) for overall physical activity parameters in eleven out of eighteen studies.

RESULTS

significant improvements were detected in the total amount of physical activity. In parallel, an increase in other parameters, such as cardiovascular, body composition, and social support, were found. The aerobic training, with supervised and tailored modalities, showed more considerable improvements.

CONCLUSIONS

this study showed that Facebook^® might be considered a feasible and accessible approach to promoting regular exercise practice and achieving health benefits indicators. Future research on the cross-link between physical activity and social network management could also focus on strength training to verify if a more structured intervention would show an effect.

Feasibility of a Social Network-Based Physical Activity Intervention Targeting Vocational School Students: A Pilot Study

Globally, four out of five adolescents do not meet the recommendations for physical activity (PA). Moving large segments of young adults from inactivity to activity is essential to reach the global target of a 15% relative reduction in inactivity by 2030 worldwide. This study aimed to examine the feasibility of a social network-based PA intervention (WALK2gether) in vocational school students. Fourteen students from one vocational school in the city of Duesseldorf were instructed to walk ten thousand steps per day over six weeks. Applied behavior change techniques were self-monitoring of steps and social comparison via a pedometer app and a Facebook group. Indicators of feasibility were documented. The intervention was minimally resource intensive, with a total of 92 h spent by the research staff. The recruitment rate was 19.2% and loss-to-follow up 28.6%. Our data revealed no significant change in the target behavior PA from baseline to follow-up. The target population did not interact in the Facebook group, while a moderate use of the pedometer app was noted. Although the results ought to be interpreted with caution due to the small sample size, the findings suggest that the WALK2gether intervention was partially feasible, but not appropriate for the target group.

The effectiveness of Facebook as a social network intervention to increase physical activity in Chinese young adults

Introduction

Facebook, one of the worlds' most popular online social networks, is easy to access and cost-effective. Its use to enhance individual's physical activity (PA) participation should be examined. This research reviews the effectiveness and successful features of Facebook for influencing PA behaviors in young adults (Study 1), and empirically examines the efficacy of the features purported in increase PA via a Facebook intervention (Study 2).

Methods

In Study 1, PubMed, Medline, SPORT Discus, ERIC, and Embase were searched for articles that identified successful features and effectiveness of Facebook PA interventions published between January 2005 and February 2022. In Study 2, a 4-week Facebook PA intervention with University students was conducted using features identified in Study 1. The PA behaviors with objective (ActiGraph) and subjective (questionnaire) measures, perceived PA level, stage of readiness, effectiveness, and efficiency of Facebook were examined.

Results

Study 1 concluded that the most effective strategies for producing significant PA changes in young adults using a PA Facebook intervention included the following: Adding behavior modification (goal setting and self-monitoring), using influence agents, recruiting members of an existing network with the snowball technique, being attentive to group size, enhancing social support with motivational quotes, interactive posts, opinion polls, increasing tailored feedback, and providing educational information. Study 2 found no significant difference in PA between the intervention and the control groups, as measured objectively, but the subjective reporting of PA behavior was higher in the intervention group. Compared to the control group, the Facebook PA intervention group reported more positive change in perceived stage of readiness in PA participation, commuting type, sport type, sport venue, sport emotion, and fast breathing or sweating. When features were ranked by the Facebook PA intervention group, motivation (supports from your friends) and tailored feedback (the responses from your friends are really personal and fits you) were the top two ranked features.

Conclusion

The use of influence agents in the Facebook PA intervention could address exercise preference and facilitate higher program engagement. Significant differences related to commuting type, sport types, sport venue barriers, and exercise intensity across groups were noteworthy and warrant additional investigation in the future.

Measurement of Adherence to mHealth Physical Activity Interventions and Exploration of the Factors That Affect the Adherence: Scoping Review and Proposed Framework

BACKGROUND

Mobile health (mHealth) is widely used as an innovative approach to delivering physical activity (PA) programs. Users' adherence to mHealth programs is important to ensure the effectiveness of mHealth-based programs.

OBJECTIVE

Our primary aim was to review the literature on the methods used to assess adherence, factors that could affect users' adherence, and the investigation of the association between adherence and health outcomes. Our secondary aim was to develop a framework to understand the role of adherence in influencing the effectiveness of mHealth PA programs.

METHODS

MEDLINE, PsycINFO, EMBASE, and CINAHL databases were searched to identify studies that evaluated the use of mHealth to promote PA in adults aged ≥18 years. We used critical interpretive synthesis methods to summarize the data collected.

RESULTS

In total, 54 papers were included in this review. We identified 31 specific adherence measurement methods, which were summarized into 8 indicators; these indicators were mapped to 4 dimensions: length, breadth, depth, and interaction. Users' characteristics (5 factors), technology-related factors (12 factors), and contextual factors (1 factor) were reported to have impacts on adherence. The included studies reveal that adherence is significantly associated with intervention outcomes, including health behaviors, psychological indicators, and clinical indicators. A framework was developed based on these review findings.

CONCLUSIONS

This study developed an adherence framework linking together the adherence predictors, comprehensive adherence assessment, and clinical effectiveness. This framework could provide evidence for measuring adherence comprehensively and guide further studies on adherence to mHealth-based PA interventions. Future research should validate the utility of this proposed framework.

Gamification in a Physical Activity App: What Gamification Features Are Being Used, by Whom, and Does It Make a Difference?

Background: Gamification is purported to enhance engagement with health behavior apps, ultimately improving their effectiveness. This study aimed to examine (1) whether the inclusion of gamification features in a physical activity smartphone app was associated with improved app usage and goal adherence, describe (2) use of the gamification features, and (3) by whom, and determine (4) whether engagement was associated with increased physical activity. Methods: Data from community-dwelling adult participants (mean age 42.1 years, standard deviation [SD 11.9], 74% female) in the gamified (n = 134) and nongamified (n = 155) conditions from a three-group randomized controlled trial were analyzed. Physical activity was assessed at baseline and 9 months using a survey and accelerometers. App usage (number of days steps were logged), goal adherence (number of days step count was ≥10,000), and behavioral engagement with gamification features were obtained from server logs. Multilevel modeling was used to examine the study aims. Results: Participants who received the gamified app showed more days of usage than those who received the nongamified app (M = 113 days [SD 88] vs. M = 81 days [SD 54], P = 0.006), whereas goal adherence did not differ between groups. The leaderboard and "status" gamification features were the most frequently used gamification features (M = 83 [SD 114] and M = 50 [SD 67] views, respectively). Older age (P = 0.008) and lower body mass index (P = 0.004) were associated with more status views. Participants who reported higher stress symptoms sent more gifts (P = 0.04). The use of gamification features was associated with increased physical activity (P = 0.04). Conclusion: The gamified app was used substantially longer than the nongamified app. Use of gamification features was positively associated with change in physical activity. Leaderboards promoting social comparison may be a promising form of gamification. Research on different forms of gamification is warranted.

Efficacy of Mobile Health Applications to Improve Physical Activity and Sedentary Behavior: A Systematic Review and Meta-Analysis for Physically Inactive Individuals

Physical inactivity and sedentary behavior (SB) have attracted growing attention globally since they relate to noninfectious chronic diseases (NCDs) and could further result in the loss of life. This systematic literature review aimed to identify existing evidence on the efficacy of mobile health (mHealth) technology in inducing physical activity and reducing sedentary behavior for physically inactive people. Studies were included if they used a smartphone app in an intervention to improve physical activity and/or sedentary behavior for physically inactive individuals. Interventions could be stand-alone interventions or multi-component interventions, including an app as one of several intervention components. A total of nine studies were included, and all were randomized controlled trials. Two studies involved interventions delivered solely via a mobile application (stand-alone intervention) and seven studies involved interventions that used apps and other intervention strategies (multi-component intervention). Methodological quality was assessed, and the overall quality of the studies was ensured. The pooled data favored intervention in improving physical activity and reducing sedentary behavior. This review provided evidence that mobile health intervention improved physical activity and reduced sedentary behavior among inactive individuals. More beneficial effects can be guaranteed when interventions include multiple components. Further studies that maintain the effectiveness of such interventions are required to maximize user engagement and intervention efficacy.

Effects of Gamified Smartphone Applications on Physical Activity: A Systematic Review and Meta-Analysis

INTRODUCTION

This systematic review and meta-analysis aims to examine the impacts of standalone gamified smartphone application-delivered interventions on physical activity.

METHODS

Web of Science, Scopus, PubMed, PsycINFO, and ACM Digital Library were searched for publications that were published between January 1, 2008 and August 31, 2021. Eligibility criteria were RCTs or single-arm pre-to-post interventions delivered by standalone gamified applications and targeting physical activity. Study-specific results were analyzed using random-effects meta-analysis, with a standardized mean difference. Meta-regressions, subgroup analyses, and sensitivity analyses were performed. PRISMA guidelines were followed, and the Grading of Recommendations Assessment, Development and Evaluation system was used to determine the strength of the evidence.

RESULTS

A total of 19 studies with 24 gamified applications were eligible, and 16 studies were included in the meta-analysis. Standalone gamified applications had a small-to-moderate effect on physical activity in both the between-group RCTs (n=12 applications, standardized mean difference=0.34, 95% CI=0.06, 0.62, I²=72%, p<0.01; Grading of Recommendations Assessment, Development and Evaluation: moderate) and the within-group pre-to-post interventions (n=18 applications, standardized mean difference=0.38, 95% CI=0.17, 0.59, I²=74%, p<0.01; Grading of Recommendations Assessment, Development and Evaluation: very low). Leave-one-out sensitivity analyses sustained the main effects with lower heterogeneity (I² of 31.0% and 47.8%, respectively).

DISCUSSION

Using gamified smartphone applications as standalone interventions may increase physical activity. Future research could investigate the impacts of gamified applications on physical activity by isolating the role of specific single or clustered groups of application features.

Evaluating the Presence of Hospitals on Social Media

Today, adults are use social media to seek health information. Evidence suggests that hospitals using Instagram reported better patient engagement and in turn increased profit and reputation. Yet, little is known about how public and private hospitals are leveraging Instagram. This study aims to analyze the presence of hospitals on Instagram using Kuwait as a case study. Hospitals were identified using the Ministry of Health’s website and Instagram. Posts collected from 7 odd months were analyzed using the Constant Comparison method. A total of 3,439 posts were distributed across six categories: Health advice & education, operations & services, current events, hospital community, seasonal occasions, and trivia. Public and private hospitals differed in their activity on Instagram in terms of health topics covered, post categories, and interactions. Hospitals should improve their presence on Instagram to promote healthy lifestyles, augment public health campaigns, and be a source of reliable and accessible health information online.

Enhancing Physical Activity and Psychological Well-Being in College Students during COVID-19 through WeActive and WeMindful Interventions

This study aimed to examine the immediate and short-term effects of aerobic and resistance training (WeActive) and mindful exercise (WeMindful) virtual interventions in improving physical activity (PA) and resilience among college students. Participants were 55 students who were randomly assigned to either the WeActive group (n = 31) or the WeMindful group (n = 24). Both groups attended two virtual 30 min aerobic and resistance training sessions (WeActive) or mindful exercise sessions (WeMindful) per week for eight weeks. All participants completed the International Physical Activity Questionnaire and the Connor–Davidson Resilience Scale (CD-RISC-10) via Qualtrics one week prior to (pre-test) and after the intervention (post-test) and 6 weeks after the intervention (follow up). There was a significant main effect of time for resilience (F = 3.4.15, p = 0.024), where both the WeActive group and the WeMindful group significantly increased the resilience scores from pre-test to follow up (t = −2.74, p = 0.02; t = −2.54, p = 0.04), respectively. For moderate physical activity (MPA), there was a significant interaction effect of time with group (F = 4.81, p = 0.01, η² = 0.038), where the WeActive group significantly increased MPA over time from pre-test to follow-up test as compared to the WeMindful group (t = −2.6, p = 0.033). Only the WeActive intervention was effective in increasing MPA. Both interventions were effective in increasing resilience from pre-test to 6 week follow up.

Running Together: How Sports Partners Keep You Running

We examined how recreational runners benefit from running with others to maintain a consistent training regimen over time. We used data from the ABS project (“Always Keep Active”). Our sample consisted of more than 800 individuals who had registered to participate in the 2019 edition of the 7K or 15K Seven Hills Run (Nijmegen, The Netherlands) for the first time. Taking advantage of this three-wave, individual-level panel data, we found that increases over time in the number of co-runners (of any ability level) are related to increases in the number of weekly running sessions. The probability of turning up at the Seven Hills Run was positively related to the number of equally or less competent co-runners, and to the number with whom respondents also discussed important matters on a frequent basis. Our recreational athletes differed in the extent to which they expressed social motivations to run. However, among these athletes, the positive impact of sports partners on sport outcomes did not depend on the importance of social motives. Our study demonstrates that social networks play an important role in maintaining a consistent training habit and in reaching set goals (i.e., participating in a race).

The Effects of mHealth-Based Gamification Interventions on Participation in Physical Activity: Systematic Review

BACKGROUND

It is well known that regular physical exercise has associated benefits; yet, participation remains suboptimal. Mobile health (mHealth) has become an indispensable medium to deliver behavior change interventions, and there is a growing interest in the gamification apps in mHealth to promote physical activity (PA) participation. Gamification could use game design elements (such as points, leaderboards, and progress bars), and it has the potential to increase motivation for PA and engagement. However, mHealth-based gamification interventions are still emerging, and little is known about the application status and efficacy of such interventions.

OBJECTIVE

This systematic review aims to investigate gamification apps in mHealth for improving PA levels and simultaneously summarize the impact of gamification interventions on PA participation.

METHODS

We searched PubMed, Scopus, Web of Science, Embase, CINAHL (EBSCO host), and IEEE Xplore from inception to December 20, 2020. Original empirical research exploring the effects of gamification interventions on PA participation was included. The papers described at least one outcome regarding exercise or PA participation, which could be subjective self-report or objective indicator measurement. Of note, we excluded studies about serious games or full-fledged games.

RESULTS

Of 2944 studies identified from the database search, 50 (1.69%) were included, and the information was synthesized. The review revealed that gamification of PA had been applied to various population groups and broadly distributed among young people but less distributed among older adults and patients with a disease. Most of the studies (30/50, 60%) combined gamification with wearable devices to improve PA behavior change, and 50% (25/50) of the studies used theories or principles for designing gamified PA interventions. The most frequently used game elements were goal-setting, followed by progress bars, rewards, points, and feedback. This review demonstrated that gamification interventions could increase PA participation; however, the results were mixed, and modest changes were attained, which could be attributed to the heterogeneity across studies.

CONCLUSIONS

Overall, this study provides an overview of the existing empirical research in PA gamification interventions and provides evidence for the efficacy of gamification in enhancing PA participation. High-quality empirical studies are needed in the future to assess the efficacy of a combination of gamification and wearable activity devices to promote PA, and further exploration is needed to investigate the optimal implementation of these features of game elements and theories to enhance PA participation.

Gamified Challenges in Online Weight-Loss Communities

Gamified challenges, one of the most popular features of online weight-loss communities, enable users to set weight-loss goals and compete with other challenge participants via leaderboards. Using the data from a leading online weight-loss community, we study the effect of gamified challenges on the weight-loss outcome. Our findings indicate that participation in gamified challenges has a positive and significant effect on weight loss. We found that, on average, the participants achieved a weight loss of 0.742 kg by participating in at least one challenge a month. We found that effective challenges do not include a numeric weight goal (e.g., lose 5 kg), focus on exercise-only behavioral goals, and have a large active group size. Further, the results show that the absence (presence) of a numeric weight goal benefits users in exercise (diet) challenges. Moreover, a small active group size can help (hurt) users in exercise (diet) challenges. Our results suggest that gamification elements that induce competition should be used with caution in goal-setting environments, especially when gamifying dietary goals. Online weight-loss communities can recommend a useful combination of numeric weight goals, behavioral goals, and an optimal number of participants in each challenge to induce an encouraging level of social comparison.

Digital Health Promotion and Prevention in Settings: Scoping Review

BACKGROUND

Digital technologies are increasingly integrating into people's daily living environments such as schools, sport clubs, and health care facilities. These settings play a crucial role for health promotion and prevention because they affect the health of their members, as the World Health Organization has declared. Implementing digital health promotion and prevention in settings offers the opportunity to reach specific target groups, lower the costs of implementation, and improve the health of the population. Currently, there is a lack of scientific evidence that reviews the research on digital health promotion and prevention in settings.

OBJECTIVE

This scoping review aims to provide an overview of research targeting digital health promotion and primary prevention in settings. It assesses the range of scientific literature regarding outcomes such as applied technology, targeted setting, and area of health promotion or prevention, as well as identifies research gaps.

METHODS

The scoping review was conducted following the Levac, Colquhoun, and O'Brien framework. We searched scientific databases and gray literature for articles on digital setting-based health promotion and prevention published from 2010 to January 2020. We included empirical and nonempirical publications in English or German and excluded secondary or tertiary prevention and health promotion at the workplace.

RESULTS

From 8888 records, the search resulted in 200 (2.25%) included publications. We identified a huge diversity of literature regarding digital setting-based health promotion and prevention. The variety of technology types extends from computer- and web-based programs to mobile devices (eg, smartphone apps) and telemonitoring devices (sensors). We found analog, digital, and blended settings in which digital health promotion and prevention takes place. The most frequent analog settings were schools (39/200, 19.5%) and neighborhoods or communities (24/200, 12%). Social media apps were also included because in some studies they were defined as a (digital) setting. They accounted for 31.5% (63/200) of the identified settings. The most commonly focused areas of health promotion and prevention were physical activity (81/200, 40.5%), nutrition (45/200, 22.5%), and sexual health (34/200, 17%). Most of the interventions combined several health promotion or prevention methods, including environmental change; providing information, social support, training, or incentives; and monitoring. Finally, we found that the articles mostly reported on behavioral rather than structural health promotion and prevention.

CONCLUSIONS

The research field of digital health promotion and prevention in settings is heterogeneous. At the same time, we identified research gaps regarding the absence of valid definitions of relevant terms (eg, digital settings) and the lack of literature on structural health promotion and prevention in settings. Therefore, it remains unclear how digital technologies can contribute to structural (or organizational) changes in settings. More research is needed to successfully implement digital technologies to achieve health promotion and prevention in settings.

Evaluating the Effectiveness of Gamification on Physical Activity: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Gamification refers to the use of game elements in nongame contexts. The use of gamification to change behaviors and promote physical activity (PA) is a promising avenue for tackling the global physical inactivity pandemic and the current prevalence of chronic diseases. However, there is no evidence of the effectiveness of gamified interventions with the existence of mixed results in the literature.

OBJECTIVE

The aim of this systematic review and meta-analysis is to evaluate the effectiveness of gamified interventions and their health care potential by testing the generalizability and sustainability of their influence on PA and sedentary behavior.

METHODS

A total of 5 electronic databases (PubMed, Embase, Scopus, Web of Science, and the Cochrane Central Register of Controlled Trials) were searched for randomized controlled trials published in English from 2010 to 2020. Eligibility criteria were based on the components of the participants, interventions, comparators, and outcomes framework. Studies were included when they used gamified interventions in daily life with an active or inactive control group and when they assessed a PA or sedentary behavior outcome. We conducted meta-analyses using a random-effects model approach. Sensitivity analyses, influence analyses, and publication bias analyses were performed to examine the robustness of our results.

RESULTS

The main meta-analysis performed on 16 studies and 2407 participants revealed a small to medium summary effect of gamified interventions on PA behavior (Hedges g=0.42, 95% CI 0.14-0.69). No statistical difference among different subgroups (adults vs adolescents and healthy participants vs adults with chronic diseases) and no interaction effects with moderators such as age, gender, or BMI were found, suggesting good generalizability of gamified interventions to different user populations. The effect was statistically significant when gamified interventions were compared with inactive control groups, such as waiting lists (Hedges g=0.58, 95% CI 0.08-1.07), and active control groups that included a nongamified PA intervention (Hedges g=0.23, 95% CI 0.05-0.41). This suggests that gamified interventions are not only efficient in changing behavior but also more effective compared with other behavioral interventions. The long-term effect (measured with follow-up averaging 14 weeks after the end of the intervention) was weaker, with a very small to small effect (Hedges g=0.15, 95% CI 0.07-0.23).

CONCLUSIONS

This meta-analysis confirms that gamified interventions are promising for promoting PA in various populations. Additional analyses revealed that this effect persists after the follow-up period, suggesting that it is not just a novelty effect caused by the playful nature of gamification, and that gamified products appear effective compared with equivalent nongamified PA interventions. Future rigorous trials are required to confirm these findings.

Effectiveness of Social Media-Based Interventions for the Promotion of Physical Activity: Scoping Review

A global target of the World Health Organization (WHO) is to reduce physical inactivity among all adults and adolescents by approximately fifteen percent by 2030. Social media could have an impact in this effort because of its enormous reach, potentially addressing underserved populations in need for physical activity (PA) interventions. This scoping review provides a broad overview of social media-based interventions and systematically maps the evidence regarding their effectiveness for PA promotion and other health outcomes. Scopus and Medline were searched using the terms “physical activity” and “social media” and the names of key social media platforms. Following the PRISMA guidelines for scoping reviews, abstracts and full texts were screened for eligibility. In total, 12,321 publications were identified and 53 met the inclusion criteria. The use of Facebook was most prevalent in PA interventions, followed by study-specific platforms. More than one third of the studies revealed positive effects regarding the promotion of PA. Additionally, social media-based interventions positively affected other physical dimensions of health (e.g., weight or blood pressure). Results pertaining to feasibility were heterogeneous. Social media seems to be a promising tool for increasing PA at the population level. Future studies should take the abundance of platforms into account and select social media platforms consciously.

A Protocol Study to Establish Psychological Outcomes From the Use of Wearables for Health and Fitness Monitoring

Background: The last few decades people have increasingly started to use technological tools for health and activity monitoring, such as tracking apps and wearables. The main assumption is that these tools are effective in reinforcing self-empowerment because they support better-informed lifestyle decision-making. However, experimental research assessing the effectiveness of the technological tools on such psychological outcomes is limited.

Methods and Design: Three studies will be conducted. First, we will perform a systematic review to examine the experimental evidence on the effects of self-tracking apps on psychological outcome measurements. Second, we will conduct a longitudinal field experiment with a between subject design. Participants (N = 150) begin a 50-day exercise program, either with or without the aid of the self-tracking app Strava. Among those who use Strava, we vary between those who use all features and those who use a limited set of features. Participants complete questionnaires at baseline, at 10, 25, and 50 days, and provide details on what information has been tracked via the platform. Third, a subset of participants is interviewed to acquire additional qualitative data. The study will provide a rich set of data, enabling triangulation, and contextualization of the findings.

Discussion: People increasingly engage in self-tracking whereby they use technological tools for health and activity monitoring, although the effects are still unknown. Considering the mixed results of the existing evidence, it is difficult to draw firm conclusions, showing more research is needed to develop a comprehensive understanding.

Trial registration: Netherlands Trial registration: NL9402, received on 20 April 2021; https://www.trialregister.nl/trial/9402.

Theory-Based Social and Non-Social Engagement Features in Smoking Cessation Mobile Apps: A Content Analysis

Despite the ubiquity of smartphone ownership and the increasing integration of social engagement features in smoking cessation apps to engage users, the social and non-social engagement features that are present in current smoking cessation apps and the effectiveness of these features in engaging users remain understudied. To fill the gap in the literature, a content analysis of free and paid smoking cessation mobile apps was conducted to examine (a) the presence of social features (i.e., social support, social announcement, and social referencing) and non-social engagement features (e.g., personal environmental changes, goal setting, progress tracking, reinforcement tracking, self-monitoring, and personalized recommendations) and (b) their relationships with user engagement scores measured by the Mobile App Rating Scale. In this study, 28.2% of the smoking cessation apps enable social announcement and 8.1% offered the social support feature. Only two apps provided a social referencing feature (1.3%). No app included reinforcement tracking, with the percentage of other non-social engagement features ranging from 9.4% to 49.0%. Social support (β = 0.30, p < 0.001), social announcement (β = 0.21, p < 0.05), and social referencing (β = 0.18, p < 0.05) were significant predictors of user engagement. Regarding the non-social engagement features, personal environment changes (β = 0.38, p < 0.001), progress tracking (β = 0.18, p < 0.05), and personalized recommendations (β = 0.37, p < 0.001) significantly predicted user engagement. The findings not only contribute to the mobile communication literature by applying and extending the theory-based mobile health apps engagement typology, but also inform the future architecture design of smoking cessation mobile apps.

The Body Confident Mums challenge: a feasibility trial and qualitative evaluation of a body acceptance program delivered to mothers using Facebook

Background

Motherhood is a time of intense physical, psychological, and identity transformation, and body dissatisfaction may emerge through the process of pregnancy, birth, and adaptation to parenting. We present a feasibility trial of the Body Confident Mums Challenge, a program developed by adapting existing, effective interventions that focus on self-compassion and appreciation of body functionality to be specific to mothers.

Methods

The program was delivered using the social learning function in a closed Facebook group. Qualitative evaluation of evidence of change was conducted by gathering individual written reflections posted during the challenge (n = 120). Feasibility and acceptability was determined using a feedback survey (n = 22).

Results

Participant’s reflective posts indicated that they were embracing self-compassion, and de-prioritising body image concerns during the challenge. Feedback indicated that the program was mostly feasible and acceptable for mothers, with recommendations from some participants relating to slowing the pace of content delivery and reducing the time commitment of the Challenge.

Conclusions

The social media environment may therefore be a useful setting in which to implement brief intervention programs to improve body image and wellbeing.

Behavioural interventions delivered through interactive social media for health behaviour change, health outcomes, and health equity in the adult population

BACKGROUND

Social networking platforms offer a wide reach for public health interventions allowing communication with broad audiences using tools that are generally free and straightforward to use and may be combined with other components, such as public health policies. We define interactive social media as activities, practices, or behaviours among communities of people who have gathered online to interactively share information, knowledge, and opinions.

OBJECTIVES

We aimed to assess the effectiveness of interactive social media interventions, in which adults are able to communicate directly with each other, on changing health behaviours, body functions, psychological health, well-being, and adverse effects. Our secondary objective was to assess the effects of these interventions on the health of populations who experience health inequity as defined by PROGRESS-Plus. We assessed whether there is evidence about PROGRESS-Plus populations being included in studies and whether results are analysed across any of these characteristics.

SEARCH METHODS

We searched CENTRAL, CINAHL, Embase, MEDLINE (including trial registries) and PsycINFO. We used Google, Web of Science, and relevant web sites to identify additional studies and searched reference lists of included studies. We searched for published and unpublished studies from 2001 until June 1, 2020. We did not limit results by language.

SELECTION CRITERIA

We included randomised controlled trials (RCTs), controlled before-and-after (CBAs) and interrupted time series studies (ITSs). We included studies in which the intervention website, app, or social media platform described a goal of changing a health behaviour, or included a behaviour change technique. The social media intervention had to be delivered to adults via a commonly-used social media platform or one that mimicked a commonly-used platform. We included studies comparing an interactive social media intervention alone or as a component of a multi-component intervention with either a non-interactive social media control or an active but less-interactive social media comparator (e.g. a moderated versus an unmoderated discussion group). Our main outcomes were health behaviours (e.g. physical activity), body function outcomes (e.g. blood glucose), psychological health outcomes (e.g. depression), well-being, and adverse events. Our secondary outcomes were process outcomes important for behaviour change and included knowledge, attitudes, intention and motivation, perceived susceptibility, self-efficacy, and social support.

DATA COLLECTION AND ANALYSIS

We used a pre-tested data extraction form and collected data independently, in duplicate. Because we aimed to assess broad outcomes, we extracted only one outcome per main and secondary outcome categories prioritised by those that were the primary outcome as reported by the study authors, used in a sample size calculation, and patient-important.

MAIN RESULTS

We included 88 studies (871,378 participants), of which 84 were RCTs, three were CBAs and one was an ITS. The majority of the studies were conducted in the USA (54%). In total, 86% were conducted in high-income countries and the remaining 14% in upper middle-income countries. The most commonly used social media platform was Facebook (39%) with few studies utilising other platforms such as WeChat, Twitter, WhatsApp, and Google Hangouts. Many studies (48%) used web-based communities or apps that mimic functions of these well-known social media platforms. We compared studies assessing interactive social media interventions with non-interactive social media interventions, which included paper-based or in-person interventions or no intervention. We only reported the RCT results in our 'Summary of findings' table. We found a range of effects on health behaviours, such as breastfeeding, condom use, diet quality, medication adherence, medical screening and testing, physical activity, tobacco use, and vaccination. For example, these interventions may increase physical activity and medical screening tests but there was little to no effect for other health behaviours, such as improved diet or reduced tobacco use (20,139 participants in 54 RCTs). For body function outcomes, interactive social media interventions may result in small but important positive effects, such as a small but important positive effect on weight loss and a small but important reduction in resting heart rate (4521 participants in 30 RCTs). Interactive social media may improve overall well-being (standardised mean difference (SMD) 0.46, 95% confidence interval (CI) 0.14 to 0.79, moderate effect, low-certainty evidence) demonstrated by an increase of 3.77 points on a general well-being scale (from 1.15 to 6.48 points higher) where scores range from 14 to 70 (3792 participants in 16 studies). We found no difference in effect on psychological outcomes (depression and distress) representing a difference of 0.1 points on a standard scale in which scores range from 0 to 63 points (SMD -0.01, 95% CI -0.14 to 0.12, low-certainty evidence, 2070 participants in 12 RCTs). We also compared studies assessing interactive social media interventions with those with an active but less interactive social media control (11 studies). Four RCTs (1523 participants) that reported on physical activity found an improvement demonstrated by an increase of 28 minutes of moderate-to-vigorous physical activity per week (from 10 to 47 minutes more, SMD 0.35, 95% CI 0.12 to 0.59, small effect, very low-certainty evidence). Two studies found little to no difference in well-being for those in the intervention and control groups (SMD 0.02, 95% CI -0.08 to 0.13, small effect, low-certainty evidence), demonstrated by a mean change of 0.4 points on a scale with a range of 0 to 100. Adverse events related to the social media component of the interventions, such as privacy issues, were not reported in any of our included studies. We were unable to conduct planned subgroup analyses related to health equity as only four studies reported relevant data.

AUTHORS' CONCLUSIONS

This review combined data for a variety of outcomes and found that social media interventions that aim to increase physical activity may be effective and social media interventions may improve well-being. While we assessed many other outcomes, there were too few studies to compare or, where there were studies, the evidence was uncertain. None of our included studies reported adverse effects related to the social media component of the intervention. Future studies should assess adverse events related to the interactive social media component and should report on population characteristics to increase our understanding of the potential effect of these interventions on reducing health inequities.

Long-term Effectiveness of mHealth Physical Activity Interventions: Systematic Review and Meta-analysis of Randomized Controlled Trials

BACKGROUND

Mobile health (mHealth) interventions can increase physical activity (PA); however, their long-term impact is not well understood.

OBJECTIVE

The primary aim of this study is to understand the immediate and long-term effects of mHealth interventions on PA. The secondary aim is to explore potential effect moderators.

METHODS

We performed this study according to the Cochrane and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed, the Cochrane Library, SCOPUS, and PsycINFO in July 2020. Eligible studies included randomized controlled trials of mHealth interventions targeting PA as a primary outcome in adults. Eligible outcome measures were walking, moderate-to-vigorous physical activity (MVPA), total physical activity (TPA), and energy expenditure. Where reported, we extracted data for 3 time points (ie, end of intervention, follow-up ≤6 months, and follow-up >6 months). To explore effect moderators, we performed subgroup analyses by population, intervention design, and control group type. Results were summarized using random effects meta-analysis. Risk of bias was assessed using the Cochrane Collaboration tool.

RESULTS

Of the 2828 identified studies, 117 were included. These studies reported on 21,118 participants with a mean age of 52.03 (SD 14.14) years, of whom 58.99% (n=12,459) were female. mHealth interventions significantly increased PA across all the 4 outcome measures at the end of intervention (walking standardized mean difference [SMD] 0.46, 95% CI 0.36-0.55; P<.001; MVPA SMD 0.28, 95% CI 0.21-0.35; P<.001; TPA SMD 0.34, 95% CI 0.20-0.47; P<.001; energy expenditure SMD 0.44, 95% CI 0.13-0.75; P=.01). Only 33 studies reported short-term follow-up measurements, and 8 studies reported long-term follow-up measurements in addition to end-of-intervention results. In the short term, effects were sustained for walking (SMD 0.26, 95% CI 0.09-0.42; P=.002), MVPA (SMD 0.20, 95% CI 0.05-0.35; P=.008), and TPA (SMD 0.53, 95% CI 0.13-0.93; P=.009). In the long term, effects were also sustained for walking (SMD 0.25, 95% CI 0.10-0.39; P=.001) and MVPA (SMD 0.19, 95% CI 0.11-0.27; P<.001). We found the study population to be an effect moderator, with higher effect scores in sick and at-risk populations. PA was increased both in scalable and nonscalable mHealth intervention designs and regardless of the control group type. The risk of bias was rated high in 80.3% (94/117) of the studies. Heterogeneity was significant, resulting in low to very low quality of evidence.

CONCLUSIONS

mHealth interventions can foster small to moderate increases in PA. The effects are maintained long term; however, the effect size decreases over time. The results encourage using mHealth interventions in at-risk and sick populations and support the use of scalable mHealth intervention designs to affordably reach large populations. However, given the low evidence quality, further methodologically rigorous studies are warranted to evaluate the long-term effects.

Designing and evaluation of E-health educational intervention on students' physical activity: an application of Pender's health promotion model

BACKGROUND

The present study was conducted to design and evaluate the software and web-based curriculum based on Pender Model in order to promote students' physical activity.

METHODS

This is a quasi-experimental study conducted on 225 eligible students who were randomly divided into two groups of web and software-based intervention and control. The sample size of the study was selected using stratified sampling method. The evaluation was done with pre-test and post-test and follow-up, which were performed immediately two and six months following the intervention. The data were analyzed employing statistical software SPSS using descriptive statistics, chi-square, one way ANOVA, and repeated measures ANOVA.

RESULTS

The obtained results revealed that the level of physical activity after the intervention in the web and software groups significantly increased compared to the control group (p < 0.001). Moreover, the mean score of Pender model constructs, immediately two and six months after the intervention, was significantly different in the web and software groups (p < 0.001).

CONCLUSION

Our results indicated that, providing tailored message based on health promotion model's constructs has a positive effect on promoting physical activity of students.

TRIAL REGISTRATION

Name: Iranian Registry of Clinical Trials. Registration number: IRCT20181009041298N1 . Registration date: 2018-12-02 [retrospectively registered].

Reliability of a smartphone application to measure physical activity

The aim of this study was to evaluate how accurate is a smartphone app to measure a physical activity parameter (steps). Physical Education undergraduate students (n = 46), both male and female, were recruited. A tally counter, a validated device (Xiaomi Mi Band 2®) and My Active Life app were used to perform the steps count. Each participant took three low-intensity treadmill walks (5 km h^-1), with a number of target steps (500-, 1000- and 1500-steps walk). Visual agreement analyses was performed through Bland-Altman plots. There was no significant interaction between steps walks and device during treadmill walking test (F_(2,84) = 3.854; p = 0.07). Differences in steps measured by Mi Band were not different from 0 in 500-steps walk (p = 0.243) and 1000-steps walk (p = 0.350), and in My Active Life in 500-steps walk (p = 0.177) and 1500-steps walk (p = 0.221). Bland-Altman analyses indicated an acceptable agreement between My active Life app and Mi Band devices for 1000-steps walk (-359.01; 310.43) and 1500-steps walk (-572.97; 377.11). In conclusion, My Active Life app showed accuracy in measuring total steps, in longer walking activities (e.g. higher than 1000 steps), and can be used on a daily basis and in research setting.

Associations Between Digital Health Intervention Engagement, Physical Activity, and Sedentary Behavior: Systematic Review and Meta-analysis

BACKGROUND

The effectiveness of digital health interventions is commonly assumed to be related to the level of user engagement with the digital health intervention, including measures of both digital health intervention use and users' subjective experience. However, little is known about the relationships between the measures of digital health intervention engagement and physical activity or sedentary behavior.

OBJECTIVE

This study aims to describe the direction and strength of the association between engagement with digital health interventions and physical activity or sedentary behavior in adults and explore whether the direction of association of digital health intervention engagement with physical activity or sedentary behavior varies with the type of engagement with the digital health intervention (ie, subjective experience, activities completed, time, and logins).

METHODS

Four databases were searched from inception to December 2019. Grey literature and reference lists of key systematic reviews and journals were also searched. Studies were eligible for inclusion if they examined a quantitative association between a measure of engagement with a digital health intervention targeting physical activity and a measure of physical activity or sedentary behavior in adults (aged ≥18 years). Studies that purposely sampled or recruited individuals on the basis of pre-existing health-related conditions were excluded. In addition, studies were excluded if the individual engaging with the digital health intervention was not the target of the physical activity intervention, the study had a non-digital health intervention component, or the digital health interventions targeted multiple health behaviors. A random effects meta-analysis and direction of association vote counting (for studies not included in meta-analysis) were used to address objective 1. Objective 2 used vote counting on the direction of the association.

RESULTS

Overall, 10,653 unique citations were identified and 375 full texts were reviewed. Of these, 19 studies (26 associations) were included in the review, with no studies reporting a measure of sedentary behavior. A meta-analysis of 11 studies indicated a small statistically significant positive association between digital health engagement (based on all usage measures) and physical activity (0.08, 95% CI 0.01-0.14, SD 0.11). Heterogeneity was high, with 77% of the variation in the point estimates explained by the between-study heterogeneity. Vote counting indicated that the relationship between physical activity and digital health intervention engagement was consistently positive for three measures: subjective experience measures (2 of 3 associations), activities completed (5 of 8 associations), and logins (6 of 10 associations). However, the direction of associations between physical activity and time-based measures of usage (time spent using the intervention) were mixed (2 of 5 associations supported the hypothesis, 2 were inconclusive, and 1 rejected the hypothesis).

CONCLUSIONS

The findings indicate a weak but consistent positive association between engagement with a physical activity digital health intervention and physical activity outcomes. No studies have targeted sedentary behavior outcomes. The findings were consistent across most constructs of engagement; however, the associations were weak.

Untapping the Health Enhancing Potential of Vigorous Intermittent Lifestyle Physical Activity (VILPA): Rationale, Scoping Review, and a 4-Pillar Research Framework

Recently revised public health guidelines acknowledge the health benefits of regular intermittent bouts of vigorous intensity incidental physical activity done as part of daily living, such as carrying shopping bags, walking uphill, and stair climbing. Despite this recognition and the advantages such lifestyle physical activity has over continuous vigorous intensity structured exercise, a scoping review we conducted revealed that current research in this area is, at best, rudimentary. Key gaps include the absence of an empirically-derived dose specification (e.g., minimum duration of lifestyle physical activity required to achieve absolute or relative vigorous intensity), lack of acceptable measurement standards, limited understanding of acute and chronic (adaptive) effects of intermittent vigorous bouts on health, and paucity of essential information necessary to develop feasible and scalable interventions (e.g., acceptability of this kind of physical activity by the public). To encourage collaboration and research agenda alignment among groups interested in this field, we propose a research framework to further understanding of vigorous intermittent lifestyle physical activity (VILPA). This framework comprises four pillars aimed at the development of: (a) an empirical definition of VILPA, (b) methods to reliably and accurately measure VILPA, (c) approaches to examine the short and long-term dose-response effects of VILPA, and (d) scalable and acceptable behavioural VILPA-promoting interventions.

A smartphone app for sedentary behaviour change in cardiac rehabilitation and the effect on hospital admissions: the ToDo-CR randomised controlled trial study protocol

INTRODUCTION

Cardiac rehabilitation (CR) is recommended for secondary prevention of cardiovascular disease and reducing the risk of repeat cardiac events. Physical activity is a core component of CR; however, studies show that participants remain largely sedentary. Sedentary behaviour is an independent risk factor for all-cause mortality. Strategies to encourage sedentary behaviour change are needed. This study will explore the effectiveness and costs of a smartphone application (Vire) and an individualised online behaviour change program (ToDo-CR) in reducing sedentary behaviour, all-cause hospital admissions and emergency department visits over 12 months after commencing CR.

METHODS AND ANALYSIS

A multicentre, assessor-blind parallel randomised controlled trial will be conducted with 144 participants (18+ years). Participants will be recruited from three phase-II CR centres. They will be assessed on admission to CR and randomly assigned (1:1) to one of two groups: CR plus the ToDo-CR 6-month programme or usual care CR. Both groups will be re-assessed at 6 months and 12 months for the primary outcome of all-cause hospital admissions and presentations to the emergency department. Accelerometer-measured changes in sedentary behaviour and physical activity will also be assessed. Logistic regression models will be used for the primary outcome of hospital admissions and emergency department visits. Methods for repeated measures analysis will be used for all other outcomes. A cost-effectiveness analysis will be conducted to evaluate the effects of the intervention on the rates of hospital admissions and emergency department visits within the 12 months post commencing CR.

ETHICS AND DISSEMINATION

This study received ethical approval from the Australian Capital Territory Health (2019.ETH.00162), Calvary Public Hospital Bruce (20-2019) and the University of Canberra (HREC-2325) Human Research Ethics Committees (HREC). Results will be disseminated through peer-reviewed academic journals. Results will be made available to participants on request.

TRIAL REGISTRATION NUMBER

ACTRN12619001223123.

Examining the Relationship between Cellphone Use Behavior, Perceived Exercise Benefit and Physical Exercise Level Among University Students in Taiwan

This study investigated how perceived exercise benefit affects the relationship between cellphone usage and physical activity level. This cross-sectional study performed a survey of Taiwanese university students selected using cluster sampling. A total of 975 students were recruited (male = 367, female = 608, average age = 20.10 ± 1.42). Data were analyzed using descriptive statistics, correlation analysis, and hierarchical regression. The results show that cellphone usage was negatively correlated with physical activity level, whereas perceived exercise benefit was negatively correlated with cellphone usage and positively correlated with physical activity level. In hierarchical regression, the main effects of cellphone usage and perceived exercise benefit explained 22% of the variance in physical activity level. After controlling for the main effect, the interaction term accounted for an additional 1% of the variance. Cellphone usage and perceived exercise benefit thus had significant power to explain physical activity level. The results of this study reveal a novel phenomenon—that students who perceived the benefits of exercise to be greater are more physically active.

A systematic review of the dose-response relationship between usage and outcomes of online physical activity weight-loss interventions

BACKGROUND

Online physical activity interventions can be an effective strategy for weight loss. However, there is a lack of systematic reviews examining the relationship between intervention usage (dose) and participants' response to online physical activity interventions for weight loss. It remains unclear whether certain usage metrics (e.g. login frequency, percent of content accessed) would be associated with improvements in behavioral outcomes. Understanding the dose-response relationship for online physical activity interventions for weight loss would be important for designing and evaluating future interventions.

OBJECTIVE

1) Review the methods used to assess intervention usage and 2) to explore the association between intervention usage metrics and outcomes for online physical activity interventions for weight-loss.

METHODS

We conducted a systematic review following the PRISMA guidelines to examine the dose-response relationship of online-based interventions targeting physical activity. We used the following keywords: web OR internet OR online OR eHealth AND physical activity OR exercise, AND engagement OR dose OR dose-response OR usage AND obesity OR weight*. Peer-reviewed articles published between 2006 and 2019 were included.

RESULTS

A total of five articles met the inclusion criteria. The mean intervention length was 10 ± 6 months (range 2-30 months). The usage metrics were total number of logins, login frequency, and usage of online tools. All usage metrics reported were found to be related to outcomes in physical activity interventions for weight-loss.

CONCLUSION

Our findings suggest that usage metrics for online physical activity interventions for weight-loss included login frequency, login duration, and use of online tools. Increased intervention usage appeared to be associated with an improvement in participant's weight, physical activity behaviors, and intervention retention. Future research should examine innovative ways to maintain intervention usage throughout the intervention.

Adding team-based financial incentives to the Carrot Rewards physical activity app increases daily step count on a population scale: a 24-week matched case control study

Background

Mobile health applications (mHealth apps) targeting physical inactivity have increased in popularity yet are usually limited by low engagement. This study examined the impact of adding team-based incentives (Step Together Challenges, STCs) to an existing mHealth app (Carrot Rewards) that rewarded individual physical activity achievements.

Methods

A 24-week quasi-experimental study (retrospective matched pairs design) was conducted in three Canadian provinces (pre-intervention: weeks 1–12; intervention: weeks 13–24). Participants who used Carrot Rewards and STCs (experimental group) were matched with those who used Carrot Rewards only (controls) on age, gender, province and baseline mean daily step count (±500 steps/d). Carrot Rewards users earned individual-level incentives (worth $0.04 CAD) each day they reached a personalized daily step goal. With a single partner, STC users could earn team incentives ($0.40 CAD) for collaboratively reaching individual daily step goals 10 times in seven days (e.g., Partner A completes four goals and Partner B completes six goals in a week).

Results

The main analysis included 61,170 users (mean age = 32 yrs.; % female = 64). Controlling for pre-intervention mean daily step count, a significant difference in intervention mean daily step count favoured the experimental group (p < 0.0001; η_p² = 0.024). The estimated marginal mean group difference was 537 steps per day, or 3759 steps per week (about 40 walking min/wk). Linear regression suggested a dose-response relationship between the number of STCs completed (app engagement) and intervention mean daily step count (adjusted R² = 0.699) with each new STC corresponding to approximately 200 more steps per day.

Conclusion

Despite an explosion of physical activity app interest, low engagement leading to small or no effects remains an industry hallmark. In this paper, we found that adding modest team-based incentives to the Carrot Rewards app increased mean daily step count, and importantly, app engagement moderated this effect. Others should consider novel small-teams based approaches to boost engagement and effects.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-020-01043-1.

Development and pilot evaluation of a mobile app on parent-child exercises to improve physical activity and psychosocial outcomes of Hong Kong Chinese children

BACKGROUND

Parent-child exercises involve children and parents to do workout together and have positive effects on physical and mental health. We developed a mobile app on parent-child exercises called Family Move, which combines coaching videos with game features such as points and level system to enhance the health and wellbeing of both children and parents through parent-child exercises. This pilot pre-post study investigated whether the Family Move app-based intervention had a positive effect on children's health-related quality of life (HRQOL), psychosocial wellbeing, and physical activity (PA) level.

METHODS

We recruited 67 parent-child pairs. During the 8-week intervention, these pairs were invited to perform parent-child exercises using the Family Move app. Points were automatically added to the user account after viewing a coaching video. In-game ranking was available to enhance user engagement. Parent proxy-report questionnaires on children's HRQOL, psychosocial wellbeing, and PA were administered at baseline and 1- and 6-month follow-up. Paired samples t-tests were conducted to evaluate post-intervention changes in child outcomes (HRQOL, psychosocial wellbeing, and PA). Multiple linear regressions were used to examine these changes as a function of in-game ranking.

RESULTS

52 (78%) viewed at least one coaching video in the Family Move app. Children's PA level significantly increased at 1-month (d = 0.32, p = 0.030) and 6-month (d = 0.30, p = 0.042) follow-up, whereas their psychosocial problems declined at 6-month follow-up (d = 0.35, p = 0.005). Higher in-game ranking was significantly associated with fewer psychosocial problems at 1-month follow-up (β = - 0.15, p = 0.030).

CONCLUSIONS

Our findings suggest that the Family Move app could be a possible intervention to increase children's PA level and psychosocial wellbeing through parent-child exercise.

TRIAL REGISTRATION

ClinicalTrials.gov number, NCT03279354 , registered September 11, 2017 (Prospectively registered).

Successful promotion of physical activity among students of medicine through motivational interview and Web-based intervention

Background

Regular physical activity supports healthy behavior and contributes to the reduction of preventable diseases. Students in their social transition period are the ideal groups for interventions. The higher education period, associated with demanding changes and poor time management, results in a low level of physical activity. In this age, social media usually are a suitable channel of communication and multicomponent interventions are the most desirable. It has not been sufficiently investigated how effective a Web-based approach is among university students when it comes to physical activity in the long-term period. We combined a Web-based approach with motivational interviews and tested these two interventions together and separate to assess their impact on improving the physical activity of medical students 1 year after the intervention.

Methods

All 514 first-year students at the Faculty of Medicine in Belgrade were invited to fill in a baseline questionnaire. Also, they underwent measurement of weight, height and waist circumference. After that, students selected a 6 months intervention according to their preference: Intervention through social media (Facebook) (Group 1) or combined with a motivational interview (Group 2). Group 3 consisted of students without any intervention. One year after completion of the 6 months intervention period, all students were invited to a second comprehensive assessment. Analyses were performed employing a wide range of statistical testing, including direct logistic regression, to identify determinants of increased physical activity measured by an average change of Metabolic Equivalent of Task (MET). This outcome measure was defined as the difference between the values at baseline and one year after completion of the 6 months intervention period.

Results

Due to a large number of potential determinants of the change of MET, three logistic regression models considered three groups of independent variables: basic socio-demographic and anthropometric data, intervention and willingness for change, and health status with life choices. The only significant model comprised parameters related to the interventions (p < 0.001). It accurately classified 73.5% of cases. There is a highly significant overall effect for type of intervention (Wald = 19.5, df = 2, p < 0.001) with high odds for the increase of physical activity. Significant relationship between time and type of intervention also existed (F = 7.33, p < 0.001, partial η² = 0.091). The influence of both factors (time and interventions) led to a change (increase) in the dependent variable MET.

Conclusion

Our study confirmed the presence of low-level physical activity among students of medicine and showed that multicomponent interventions have significant potential for positive change. The desirable effects of the Web-based intervention are higher if an additional booster is involved, such as a motivational interview.

Behavior Change Techniques Included in Reports of Social Media Interventions for Promoting Health Behaviors in Adults: Content Analysis Within a Systematic Review

BACKGROUND

Social media are an increasingly commonly used platform for delivering health promotion interventions. Although recent research has focused on the effectiveness of social media interventions for health promotion, very little is known about the optimal content within such interventions, and the active ingredients to promote health behavior change using social media are not clear. Identifying which behavior change techniques (BCTs) are reported may help to clarify the content of interventions using a generalizable terminology that may facilitate future intervention development.

OBJECTIVE

This study aimed to identify which BCTs are reported in social media interventions for promoting health behavior change in adults.

METHODS

We included 71 studies conducted with adult participants (aged ≥18 years) and for which social media intervention was considered interactive in a Cochrane review of the effectiveness of such interventions. We developed a coding manual informed by the Behavior Change Technique Taxonomy version 1 (BCTTv1) to identify BCTs in the included studies. We identified BCTs in all study arms (including control) and described BCTs in the group and self-directed components of studies. We characterized the dose of delivery for each BCT by low and high intensity. We used descriptive analyses to characterize the reported BCTs.

RESULTS

Our data consisted of 71 studies published from 2001 to 2017, mainly conducted in high-income countries (n=65). Most studies (n=31) used tailored, interactive websites to deliver the intervention; Facebook was the most used mainstream platform. In developing our coding manual, we adapted some BCTTv1 instructions to better capture unique nuances of how BCTs were operationalized in social media with respect to likes, retweets, smiles, congratulations, and badges. Social support (unspecified), instruction on how to perform the behavior, and credible source were most frequently identified BCTs in intervention arms of studies and group-delivery settings, whereas instruction on how to perform the behavior was most commonly applied in self-directed components of studies, control arms, and individual participant settings. Instruction on how to perform the behavior was also the most frequently reported BCT in both intervention and control arms simultaneously. Instruction on how to perform the behavior, social support (unspecified), self-monitoring of behavior, information about health consequences, and credible source were identified in the top 5 BCTs delivered with the highest intensity.

CONCLUSIONS

This study within a review provides a detailed description of the BCTs and their dose to promote behavior change in web-based, interactive social media interventions. Clarifying active ingredients in social media interventions and the intensity of their delivery may help to develop future interventions that can more clearly build upon the existing evidence.

Facebook as a Novel Tool for Continuous Professional Education on Dementia: Pilot Randomized Controlled Trial

BACKGROUND

Social network sites (SNSs) are widely exploited in health education and communication by the general public, including patients with various conditions. Nevertheless, there is an absence of evidence evaluating SNSs in connecting health professionals for professional purposes.

OBJECTIVE

This pilot randomized controlled trial was designed to evaluate the feasibility of an intervention aiming to investigate the effects of a continuous professional education program utilizing Facebook to obtain knowledge on dementia and care for patients with dementia.

METHODS

Eighty health professionals from Hong Kong were recruited for participation in the study and randomized at a 1:1 ratio by a block randomization method to the intervention group (n=40) and control group (n=40). The intervention was an 8-week educational program developed to deliver updated knowledge on dementia care from a multidisciplinary perspective, either by Facebook (intervention group) or by email (control group) from October 2018 to January 2019. The primary outcomes were the effects of the intervention, measured by differences in the means of changes in pre- and postintervention scores of knowledge assessments from the 25-item Dementia Knowledge Assessment Scale (DKAS) and formative evaluation of 20 multiple choice questions. Other outcome measurements included participant compliance, participant engagement in Facebook, satisfaction, and self-perceived uses of Facebook for continuing professional education programs.

RESULTS

Significantly more intervention group participants (n=35) completed the study than the control group (n=25) (P<.001). The overall retention rate was 75% (60/80). The mean of changes in scores in the intervention group were significant in all assessments (P<.001). A significant difference in the mean of changes in scores between the two groups was identified in the DKAS subscale Communication and Behavior (95% CI 0.4-3.3, P=.02). There was no significant difference in the total DKAS scores, scores of other DKAS subscales, and multiple choice questions. Participant compliance was significantly higher in the intervention group than in the control group (P<.001). The mean numbers of participants accessing the learning materials were 31.5 (SD 3.9) and 17.6 (SD 5.2) in the intervention and control group, respectively. Polls attracted the highest level of participant engagement, followed by videos. Intervention group participants scored significantly higher in favoring the use of Facebook for the continuing education program (P=.03). Overall, participants were satisfied with the interventions (mean score 4 of a total of 5, SD 0.6).

CONCLUSIONS

The significantly higher retention rate, together with the high levels of participant compliance and engagement, demonstrate that Facebook is a promising tool for professional education. Education delivered through Facebook was significantly more effective at improving participants' knowledge of how people with dementia communicate and behave. Participants demonstrated positive attitudes toward utilizing Facebook for professional learning. These findings provide evidence for the feasibility of using Facebook as an intervention delivery tool in a manner that can be rolled out into practical settings.

The Influence of Fitness-App Usage on Psychological Well-Being and Body Awareness-A Daily Diary Randomized Trial

Self-tracking via fitness apps is popular and has been described as a means to enhance body awareness and well-being. However, the effects of fitness-app use and specific app functions on well-being and body awareness have yet to be targeted in controlled experimental studies. In two randomized groups, a fitness tracker was used for 6 weeks, and in one group a daily step target was implemented. In a third control group, participants documented their physical activity. A daily diary method was used to measure well-being and body trusting. In Bayesian multilevel analyses, no time, group, or interaction effects were found. These results were robust when controlling for diverse variables. It can be concluded that exercise-related self-tracking and specific step goals do not substantially influence psychological well-being and body trusting. Considering the large variability in effects, potential effects can be assumed under conditions that are to be identified in further studies.

Effect of web-based and software-based educational intervention on stages of behavior change of students' physical activity

INTRODUCTION

The present study aims at designing and evaluating the effect of new educational media-based educational intervention on students' stages of behavior change of physical activity.

SUBJECTS AND METHODS

In the present interventional study, 225 students of medical sciences university were assigned into two experimental and one control groups using proportional stratified random sampling, where web-based and software-based educational interventions were used. Data were collected using International Physical Activity Questionnaire, Marcus's stages of change scales, and a self-made questionnaire including constructs of barriers, benefits, and self-efficacy. Evaluation was conducted through pretest and posttest and immediate and 2 and 6 months of follow-ups after the intervention. Data were analyzed by SPSS software using descriptive statistics and Chi-square, Friedman, one-way ANOVA, and ANOVA with repeated measure.

RESULTS

Based on the results, there was no significant difference between the experimental and control groups before the intervention (P = 0.37); however, immediately and 2 and 6 months after the intervention, there was a significant difference between the experimental and control groups in terms of stages of change (P < 0.001). Furthermore, in the experimental group, the educational intervention led to improvement of individuals in the stages of change of physical activity. At 6-month follow-up, 75.4% of the software group and 60.6% of the web group achieved the maintenance stage.

CONCLUSION

The results suggest that designing intervention based on people's level of preparation for changing behavior and using new educational methods such as web and software were effective on individuals' progress in different stages of change of physical activity behavior and physical activity rate.

A Persuasive mHealth Behavioral Change Intervention for Promoting Physical Activity in the Workplace: Feasibility Randomized Controlled Trial

Background

Employees in an office setting are more likely to remain physically inactive. Physical inactivity has become one of the major barriers to overcoming the risk factors for anxiety, depression, coronary heart disease, certain cancers, and type 2 diabetes. Currently, there is a gap in mobile health (mHealth) apps to promote physical activity (PA) for workers in the workplace. Studies on behavior change theories have concluded that health apps generally lack the use of theoretical constructs.

Objective

The objective of this study was to study the feasibility of a persuasive app aimed at encouraging PA among employees and to understand the motivational aspects behind the implementation of mHealth apps among office workers.

Methods

A 4-week study using a mixed methods (quantitative and qualitative) design was conducted with office-based employees in cities in 4 countries: Oulu, Finland; Carlow, Ireland; London, United Kingdom; and Dhaka, Bangladesh. Of the 220 invited participants (experimental group, n=115; control group, n=105), 84 participated (experimental group, n=56; control group, n=28), consisting of working-age volunteers working in an office setting. Participants used 2 different interventions: The experimental group used an mHealth app for PA motivation, and the control group used a paper diary. The purpose was to motivate employees to engage in healthier behavior regarding the promotion of PA in the workplace. A user-centered design process was followed to design, develop, and evaluate the mHealth app, incorporating self-determination theory (SDT) and using game elements. The paper diary had no specific theory-driven approach, design technique, nor game elements.

Results

Compliance with app usage remained relatively low, with 27 participants (experimental group, n=20; control group, n=7) completing the study. The results support the original hypothesis that the mHealth app would help increase PA (ie, promoting daily walking in the workplace) in comparison to a paper diary (P=.033). The mHealth app supported 2 of the basic SDT psychological needs, namely autonomy (P=.004) and competence (P=.014), but not the needs of relatedness (P=.535).

Conclusions

The SDT-based mHealth application motivated employees to increase their PA in the workplace. However, compliance with app usage remained low. Future research should further develop the app based on user feedback and test it in a larger sample.

A Social Networking and Gamified App to Increase Physical Activity: Cluster RCT

INTRODUCTION

Appealing approaches to increasing physical activity levels are needed. This study evaluated whether a social and gamified smartphone app (Active Team) could be one such approach.

STUDY DESIGN

A 3-group cluster RCT compared the efficacy of Active Team with a basic self-monitoring app and waitlist control group.

SETTING/PARTICIPANTS

Australian adults (N=444, mean age of 41 years, 74% female) were recruited in teams (n=121) and randomly assigned (1:1:1) to the Active Team (n=141, 39 teams), self-monitoring app (n=160, 42 teams), or waitlist group (n=143, 40 teams). Data were collected in 2016-2017, and analysis was conducted in 2018-2019.

INTERVENTION

Active Team is a 100-day app-based, gamified, online social networking physical activity intervention.

MAIN OUTCOME MEASURES

The primary outcome was change in objective physical activity from baseline to 3-month follow-up. Secondary outcomes included objective physical activity at 9 months and self-reported physical activity, quality of life, depression, anxiety and stress, well-being, and engagement.

RESULTS

Mixed models indicated no significant differences in objective physical activity between groups at 3 (F=0.17, p=0.84; Cohen's d=0.03, 95% CI= -0.21, 0.26) or 9 months (F=0.23, p=0.92; d=0.06, 95% CI= -0.17, 0.29) and no significant differences for secondary outcomes of quality of life, depression, anxiety and stress, or well-being. Self-reported moderate-to-vigorous physical activity was significantly higher in the Active Team group at the 9-month follow-up (F=3.05, p=0.02; d=0.50, 95% CI=0.26, 0.73). Engagement was high; the Active Team group logged steps on an average of 72 (SD=35) days and used the social and gamified features an average of 89 (SD=118) times.

CONCLUSIONS

A gamified, online social networking physical activity intervention did not change objective moderate-to-vigorous physical activity, though it did increase self-reported moderate-to-vigorous physical activity and achieve high levels of engagement. Future work is needed to understand if gamification, online social networks, and app-based approaches can be leveraged to achieve positive behavior change.

TRIAL REGISTRATION

This study is registered at Australian and New Zealand Clinical Trial Registry (protocol: ANZCTR12617000113358).

The Use and Effects of an App-Based Physical Activity Intervention "Active2Gether" in Young Adults: Quasi-Experimental Trial

BACKGROUND

Insufficient physical activity (PA) is highly prevalent and associated with adverse health conditions and the risk of noncommunicable diseases. To increase levels of PA, effective interventions to promote PA are needed. Present-day technologies such as smartphones, smartphone apps, and activity trackers offer several possibilities in health promotion.

OBJECTIVE

This study aimed to explore the use and short-term effects of an app-based intervention (Active2Gether) to increase the levels of PA in young adults.

METHODS

Young adults aged 18-30 years were recruited (N=104) using diverse recruitment strategies. The participants were allocated to the Active2Gether-Full condition (tailored coaching messages, self-monitoring, and social comparison), Active2Gether-Light condition (self-monitoring and social comparison), and the Fitbit-only control condition (self-monitoring). All participants received a Fitbit One activity tracker, which could be synchronized with the intervention apps, to monitor PA behavior. A 12-week quasi-experimental trial was conducted to explore the intervention effects on weekly moderate-to-vigorous PA (MVPA) and relevant behavioral determinants (ie, self-efficacy, outcome expectations, social norm, intentions, satisfaction, perceived barriers, and long-term goals). The ActiGraph wGT3XBT and GT3X+ were used to assess baseline and postintervention follow-up PA.

RESULTS

Compared with the Fitbit condition, the Active2Gether-Light condition showed larger effect sizes for minutes of MVPA per day (regression coefficient B=3.1; 95% CI -6.7 to 12.9), and comparatively smaller effect sizes were seen for the Active2Gether-Full condition (B=1.2; 95% CI -8.7 to 11.1). Linear and logistic regression analyses for the intervention effects on the behavioral determinants at postintervention follow-up showed no significant intervention effects of the Active2Gether-Full and Active2Gether-Light conditions. The overall engagement with the Fitbit activity tracker was high (median 88% (74/84) of the days), but lower in the Fitbit condition. Participants in the Active2Gether conditions reported more technical problems than those in the Fitbit condition.

CONCLUSIONS

This study showed no statistically significant differences in MVPA or determinants of MVPA after exposure to the Active2Gether-Full condition compared with the Active2Gether-Light or Fitbit condition. This might partly be explained by the small sample size and the low rates of satisfaction in the participants in the two Active2Gether conditions that might be because of the high rates of technical problems.

User Engagement and Attrition in an App-Based Physical Activity Intervention: Secondary Analysis of a Randomized Controlled Trial

Background

The success of a mobile phone app in changing health behavior is thought to be contingent on engagement, commonly operationalized as frequency of use.

Objective

This subgroup analysis of the 2 intervention arms from a 3-group randomized controlled trial aimed to examine user engagement with a 100-day physical activity intervention delivered via an app. Rates of engagement, associations between user characteristics and engagement, and whether engagement was related to intervention efficacy were examined.

Methods

Engagement was captured in a real-time log of interactions by users randomized to either a gamified (n=141) or nongamified version of the same app (n=160). Physical activity was assessed via accelerometry and self-report at baseline and 3-month follow-up. Survival analysis was used to assess time to nonuse attrition. Mixed models examined associations between user characteristics and engagement (total app use). Characteristics of super users (top quartile of users) and regular users (lowest 3 quartiles) were compared using t tests and a chi-square analysis. Linear mixed models were used to assess whether being a super user was related to change in physical activity over time.

Results

Engagement was high. Attrition (30 days of nonuse) occurred in 32% and 39% of the gamified and basic groups, respectively, with no significant between-group differences in time to attrition (P=.17). Users with a body mass index (BMI) in the healthy range had higher total app use (mean 230.5, 95% CI 190.6-270.5; F₂=8.67; P<.001), compared with users whose BMI was overweight or obese (mean 170.6, 95% CI 139.5-201.6; mean 132.9, 95% CI 104.8-161.0). Older users had higher total app use (mean 200.4, 95% CI 171.9-228.9; F₁=6.385; P=.01) than younger users (mean 155.6, 95% CI 128.5-182.6). Super users were 4.6 years older (t₂₉₇=3.6; P<.001) and less likely to have a BMI in the obese range (χ²₂=15.1; P<.001). At the 3-month follow-up, super users were completing 28.2 (95% CI 9.4-46.9) more minutes of objectively measured physical activity than regular users (F_1,272=4.76; P=.03).

Conclusions

Total app use was high across the 100-day intervention period, and the inclusion of gamified features enhanced engagement. Participants who engaged the most saw significantly greater increases to their objectively measured physical activity over time, supporting the theory that intervention exposure is linked to efficacy. Further research is needed to determine whether these findings are replicated in other app-based interventions, including those experimentally evaluating engagement and those conducted in real-world settings.

Trial Registration

Australian New Zealand Clinical Trials Registry ACTRN12617000113358; https://www.anzctr.org.au/ACTRN12617000113358.aspx