Worldwide physical activity levels of adults are declining, which is associated with increased chronic disease risk. Wearables and smartphone applications offer new opportunities to change physical activity behaviour. This systematic review summarizes the evidence regarding the effect of wearables and smartphone applications on promoting physical activity. PubMed, EMBASE and Cochrane databases were searched for RCTs, published since January 2008, on wearables and smartphone applications to promote physical activity. Studies were excluded when the study population consisted of children or adolescents, the intervention did not promote physical activity or comprised a minor part of the intervention, or the intervention was Internet-based and not accessible by smartphone. Risk of bias was assessed by the Cochrane collaboration tool. The primary outcome was changed in physical activity level. Meta-analyses were performed to assess the pooled effect on (moderate-to-vigorous) physical activity in minutes per day and daily step count. Eighteen RCTs were included. Use of wearables and smartphone applications led to a small to moderate increase in physical activity in minutes per day (SMD = 0.43, 95% CI = 0.03 to 0.82; I2 = 85%) and a moderate increase in daily step count (SMD = 0.51, 95% CI = 0.12 to 0.91; I2 = 90%). When removing studies with an unclear or high risk of bias, intervention effects improved and statistical heterogeneity was removed. This meta-analysis showed a small to moderate effect of physical activity interventions comprising wearables and smartphone applications on physical activity. Hence, wearables and smartphone applications are likely to bring new opportunities in delivering tailored interventions to increase levels of physical activity.

Videogames for health (G4H) offer exciting, innovative, potentially highly effective methods for increasing knowledge, delivering persuasive messages, changing behaviors, and influencing health outcomes. Although early outcome results are promising, additional research is needed to determine the game design and behavior change procedures that best promote G4H effectiveness and to identify and minimize possible adverse effects. Guidelines for ideal use of different types of G4H by children and adolescents should be elucidated to enhance effectiveness and minimize adverse effects. G4H stakeholders include organizational implementers, policy makers, players and their families, researchers, designers, retailers, and publishers. All stakeholders should be involved in G4H development and have a voice in setting goals to capitalize on their insights to enhance effectiveness and use of the game. In the future, multiple targeted G4H should be available to meet a population's diverse health needs in developmentally appropriate ways. Substantial, consistent, and sophisticated research with appropriate levels of funding is needed to realize the benefits of G4H.

The main purpose of this paper is to review the benefits and factors to be taken into consideration for the design of intergenerational digital games. We conducted a systematic in Scopus, Web of Science, PsicInfo, Pubmed and Science Direct, finally including 16 empirical studies written in English. The identified benefits were found to fall into four main categories, i.e., (1) reinforcing family bond, (2) enhancing reciprocal learning (3) increasing understanding of the other generation and (4) reducing social anxiety. According to the literature, two types of factors are important to take into consideration: player-centric and game-centric factors. We identified the nature of the interactions between older (55–81 year-olds) and younger players (4–22 year-olds), their motivations to play digital games and the difference in abilities as the main player-centric factors to take into account when designing intergenerational games. The most relevant game-centric factors were found to be goal-related and space-related forms of interaction. To gain more insight into how specific benefits of playing digital games are related to a type of game, gender or age of the participant, additional empirical studies (comparative analyses), that take these factors into account are needed.

The purpose of this study was to assess the potential of the electrically assisted bicycle (EAB) as a novel tool for meeting the physical activity guidelines in terms of intensity. Twelve habitually active adult subjects were requested to cycle a track of 4.3 km at an intensity they would normally choose for commuter cycling, using three different support settings: no support (NO), eco support (ECO), and power support (POW). For estimating the intensity, the oxygen consumption was measured by using a portable gas-analyzing system, and HR was simultaneously measured. The bicycle was equipped with the SRM Training System to measure subjects' power output, pedaling rate, and the cycle velocity. Mean intensity was 6.1 MET for NO, 5.7 MET for ECO, and 5.2 MET for POW. Intensity was significantly lower in POW compared with that in NO. No differences were found between NO and ECO and between ECO and POW. Mean HR was significantly higher in NO compared with that in ECO and POW. The cycling speed with electrical support settings was significantly higher than cycling in the NO condition. Mean power output during cycling was significantly different among all three conditions. Most power outputs were supplied in the NO condition, and the lowest power output was supplied in the POW condition. Intensity during cycling on an EAB, in all three measured conditions, is sufficiently high to contribute to the physical activity guidelines for moderate-intensity health-enhancing physical activity for adults (cutoff, 3 MET). Further study is needed to conclude whether these results still hold when using the EAB in regular daily life and in subjects with other fitness level.

Background: It is unclear why some physical activity (PA) mobile health (mHealth) interventions successfully promote PA whereas others do not. One possible explanation is the variety in PA mHealth interventions—not only do interventions differ in the selection of persuasive strategies but also the design and implementation of persuasive strategies can vary. However, limited studies have examined the different designs and technical implementations of strategies or explored if they indeed influenced the effectiveness of the intervention. Objective: This scoping review sets out to explore the different technical implementations and design characteristics of common and likely most effective persuasive strategies, namely, goal setting, monitoring, reminders, rewards, sharing, and social comparison. Furthermore, this review aims to explore whether previous mHealth studies examined the influence of the different design characteristics and technical operationalizations of common persuasive strategies on the effectiveness of the intervention to persuade the user to engage in PA. Methods: An unsystematic snowball and gray literature search was performed to identify the literature that evaluated the persuasive strategies in experimental trials (eg, randomized controlled trial, pre-post test). Studies were included if they targeted adults, if they were (partly) delivered by a mobile system, if they reported PA outcomes, if they used an experimental trial, and when they specifically compared the effect of different designs or implementations of persuasive strategies. The study methods, implementations, and designs of persuasive strategies, and the study results were systematically extracted from the literature by the reviewers. Results: A total of 29 experimental trials were identified. We found a heterogeneity in how the strategies are being implemented and designed. Moreover, the findings indicated that the implementation and design of the strategy has an influence on the effectiveness of the PA intervention. For instance, the effectiveness of rewarding was shown to vary between types of rewards; rewarding goal achievement seems to be more effective than rewarding each step taken. Furthermore, studies comparing different ways of goal setting suggested that assigning a goal to users might appear to be more effective than letting the user set their own goal, similar to using adaptively tailored goals as opposed to static generic goals. This study further demonstrates that only a few studies have examined the influence of different technical implementations on PA behavior. Conclusions: The different implementations and designs of persuasive strategies in mHealth interventions should be critically considered when developing such interventions and before drawing conclusions on the effectiveness of the strategy as a whole. Future efforts are needed to examine which implementations and designs are most effective to improve the translation of theory-based persuasive strategies into practical delivery forms.