Background: Social network technologies have become part of health education and wider health promotion—either by design or happenstance. Social support, peer pressure, and information sharing in online communities may affect health behaviors. If there are positive and sustained effects, then social network technologies could increase the effectiveness and efficiency of many public health campaigns. Social media alone, however, may be insufficient to promote health. Furthermore, there may be unintended and potentially harmful consequences of inaccurate or misleading health information. Given these uncertainties, there is a need to understand and synthesize the evidence base for the use of online social networking as part of health promoting interventions to inform future research and practice. Objective: Our aim was to review the research on the integration of expert-led health promotion interventions with online social networking in order to determine the extent to which the complementary benefits of each are understood and used. We asked, in particular, (1) How is effectiveness being measured and what are the specific problems in effecting health behavior change?, and (2) To what extent is the designated role of social networking grounded in theory? Methods: The narrative synthesis approach to literature review was used to analyze the existing evidence. We searched the indexed scientific literature using keywords associated with health promotion and social networking. The papers included were only those making substantial study of both social networking and health promotion—either reporting the results of the intervention or detailing evidence-based plans. General papers about social networking and health were not included. Results: The search identified 162 potentially relevant documents after review of titles and abstracts. Of these, 42 satisfied the inclusion criteria after full-text review. Six studies described randomized controlled trials (RCTs) evaluating the effectiveness of online social networking within health promotion interventions. Most of the trials investigated the value of a “social networking condition” in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. Conclusions: More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks. [J Med Internet Res 2015;17(6):e141]

The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness

Background: Serious educational games have shown effectiveness in improving various health outcomes. Previous reviews of health education games have focused on specific diseases, certain medical subjects, fixed target groups, or limited outcomes of interest. Given the recent surge in health game studies, a scoping review of health education games is needed to provide an updated overview of various aspects of such serious games.
Objective: This study aimed to conduct a scoping review of the design and evaluation of serious educational games for health targeting health care providers, patients, and public (health) users.
Methods: We identified 2313 studies using a unique combination of keywords in the PubMed and ScienceDirect databases. A total of 161 studies were included in this review after removing duplicates (n=55) and excluding studies not meeting our inclusion criteria (1917 based on title and abstract and 180 after reviewing the full text). The results were stratified based on games targeting health care providers, patients, and public users.
Results: Most health education games were developed and evaluated in America (82/161, 50.9%) and Europe (64/161, 39.8%), with a considerable number of studies published after 2012. We discovered 58.4% (94/161) of studies aiming to improve knowledge learning and 41.6% (67/161) to enhance skill development. The studies targeted various categories of end users: health care providers (42/161, 26.1%), patients (38/161, 23.6%), public users (75/161, 46.6%), and a mix of users (6/161, 3.7%). Among games targeting patients, only 13% (6/44) targeted a specific disease, whereas a growing majority targeted lifestyle behaviors, social interactions, cognition, and generic health issues (eg, safety and nutrition). Among 101 studies reporting gameplay specifications, the most common gameplay duration was 30 to 45 min. Of the 61 studies reporting game repetition, only 14% (9/61) of the games allowed the users to play the game with unlimited repetitions. From 32 studies that measured follow-up duration after the game intervention, only 1 study reported a 2-year postintervention follow-up. More than 57.7% (93/161) of the games did not have a multidisciplinary team to design, develop, or assess the game.
Conclusions: Serious games are increasingly used for health education targeting a variety of end users. This study offers an updated scoping review of the studies assessing the value of serious games in improving health education. The results showed a promising trend in diversifying the application of health education games that go beyond a specific medical condition. However, our findings indicate the need for health education game development and adoption in developing countries and the need to focus on multidisciplinary teamwork in designing effective health education games. Furthermore, future health games should expand the duration and repetition of games and increase the length of the follow-up assessments to provide evidence on long-term effectiveness.

Health Education Serious Games Targeting Health Care Providers, Patients, and Public Health Users: Scoping Review

Background: Although many smartphone apps and wearables have been designed to improve physical activity, their rapidly evolving nature and complexity present challenges for evaluating their impact. Traditional methodologies, such as randomized controlled trials (RCTs), can be slow. To keep pace with rapid technological development, evaluations of mobile health technologies must be efficient. Rapid alternative research designs have been proposed, and efficient in-app data collection methods, including in-device sensors and device-generated logs, are available. Along with effectiveness, it is important to measure engagement (ie, users’ interaction and usage behavior) and acceptability (ie, users’ subjective perceptions and experiences) to help explain how and why apps and wearables work.

Objectives: This study aimed to (1) explore the extent to which evaluations of physical activity apps and wearables: employ rapid research designs; assess engagement, acceptability, as well as effectiveness; use efficient data collection methods; and (2) describe which dimensions of engagement and acceptability are assessed.

Method: An interdisciplinary scoping review using 8 databases from health and computing sciences. Included studies measured physical activity, and evaluated physical activity apps or wearables that provided sensor-based feedback. Results were analyzed using descriptive numerical summaries, chi-square testing, and qualitative thematic analysis.

Results: A total of 1829 abstracts were screened, and 858 articles read in full. Of 111 included studies, 61 (55.0%) were published between 2015 and 2017. Most (55.0%, 61/111) were RCTs, and only 2 studies (1.8%) used rapid research designs: 1 single-case design and 1 multiphase optimization strategy. Other research designs included 23 (22.5%) repeated measures designs, 11 (9.9%) nonrandomized group designs, 10 (9.0%) case studies, and 4 (3.6%) observational studies. Less than one-third of the studies (32.0%, 35/111) investigated effectiveness, engagement, and acceptability together. To measure physical activity, most studies (90.1%, 101/111) employed sensors (either in-device [67.6%, 75/111] or external [23.4%, 26/111]). RCTs were more likely to employ external sensors (accelerometers: P=.005). Studies that assessed engagement (52.3%, 58/111) mostly used device-generated logs (91%, 53/58) to measure the frequency, depth, and length of engagement. Studies that assessed acceptability (57.7%, 64/111) most often used questionnaires (64%, 42/64) and/or qualitative methods (53%, 34/64) to explore appreciation, perceived effectiveness and usefulness, satisfaction, intention to continue use, and social acceptability. Some studies (14.4%, 16/111) assessed dimensions more closely related to usability (ie, burden of sensor wear and use, interface complexity, and perceived technical performance).

Conclusions: The rapid increase of research into the impact of physical activity apps and wearables means that evaluation guidelines are urgently needed to promote efficiency through the use of rapid research designs, in-device sensors and user-logs to assess effectiveness, engagement, and acceptability. Screening articles was time-consuming because reporting across health and computing sciences lacked standardization. Reporting guidelines are therefore needed to facilitate the synthesis of evidence across disciplines.

/pdf/evaluating-the-impact-of-physical-activity-apps-and-mizr4qkwow.pdf

Evaluating the Impact of Physical Activity Apps and Wearables: Interdisciplinary Review

Background: Widespread diffusion of mobile phone and Web 2.0 technologies make them potentially useful tools for promoting health and tackling public health issues, such as the increasing prevalence of overweight and obesity. Research in this domain is growing rapidly but, to date, no review has comprehensively and systematically documented how mobile and Web 2.0 technologies are being deployed and evaluated in relation to weight management. Objective: To provide an up-to-date, comprehensive map of the literature discussing the use of mobile phone and Web 2.0 apps for influencing behaviors related to weight management (ie, diet, physical activity [PA], weight control, etc). Methods: A systematic scoping review of the literature was conducted based on a published protocol (registered at PROSPERO: CRD42014010323). Using a comprehensive search strategy, we searched 16 multidisciplinary electronic databases for original research documents published in English between 2004 and 2014. We used duplicate study selection and data extraction. Using an inductively developed charting tool, selected articles were thematically categorized. Results: We identified 457 articles, mostly published between 2013 and 2014 in 157 different journals and 89 conference proceedings. Articles were categorized around two overarching themes, which described the use of technologies for either (1) promoting behavior change (309/457, 67.6%) or (2) measuring behavior (103/457, 22.5%). The remaining articles were overviews of apps and social media content (33/457, 7.2%) or covered a combination of these three themes (12/457, 2.6%). Within the two main overarching themes, we categorized articles as representing three phases of research development: (1) design and development, (2) feasibility studies, and (3) evaluations. Overall, articles mostly reported on evaluations of technologies for behavior change (211/457, 46.2%). Conclusions: There is an extensive body of research on mobile phone and Web 2.0 technologies for weight management. Research has reported on (1) the development, feasibility, and efficacy of persuasive mobile technologies used in interventions for behavior change (PA and diet) and (2) the design, feasibility, and accuracy of mobile phone apps for behavioral assessment. Further research has focused exclusively on analyses of the content and quality of available apps. Limited evidence exists on the use of social media for behavior change, but a segment of studies deal with content analyses of social media. Future research should analyze mobile phone and Web 2.0 technologies together by combining the evaluation of content and design aspects with usability, feasibility, and efficacy/effectiveness for behavior change, or accuracy/validity for behavior assessment, in order to understand which technological components and features are likely to result in effective interventions. [J Med Internet Res 2015;17(11):e259]

/pdf/mobile-phone-and-web-2-0-technologies-for-weight-management-4g69st51k2.pdf

Mobile Phone and Web 2.0 Technologies for Weight Management: A Systematic Scoping Review.

Many smartphone apps and wearables have been developed to promote physical activity, however there are challenges in assessing their impact. Apps and wearables are rapidly evolving technologies and thousands of physical activity apps that are publicly available on app stores remain unevaluated. There are concerns that traditional “gold standard” evaluation approaches, such as randomised control trials (RCTs), may be too slow to keep up with these, and produce effectiveness results that do not reflect real world settings. Rapid research designs (such as single case designs; SCDs) and innovative data collection methods (in-device sensors, device-generated user logs) have been proposed to improve research efficiency, yet preliminary evidence suggests they are not widely used in mHealth.

This thesis reports three studies undertaken to investigate the use of rapid research designs and efficient methods for evaluating physical activity apps and wearables. First, a scoping review of the extent to which these approaches are employed by health and HCI researchers. Second, semi-structured interviews with researchers, data scientists and industry professionals to provide a deeper understanding of current evaluation practices. Third, the development and refinement of a methodological framework to support researchers in using SCDs in automated app store evaluations of physical activity apps.

The findings suggest rapid research designs are not often employed in evaluations of physical activity and other health behaviour change apps. Researchers feel they face opportunity barriers (e.g. risking not being funded or published) and do not have the necessary skills (e.g. in using device generated user logs). Industry professionals appear to lack the motivation and time to evaluate effectiveness. Trade-offs were perceived between the measurement accuracy of in-device sensors and other factors such as user burden.

Automated trials may speed up evaluations of physical activity apps and wearables, and the suggested data collection framework aims to support researchers in conducting rigorous effectiveness evaluations using app store- based SCDs. However, further work is needed to enable industry professionals to use the framework to evaluate their publicly-available apps.

Evaluating the impact of physical activity apps and wearables: an interdisciplinary investigation of research designs and methods

The obesity epidemic is a major health concern. More than two thirds of Americans and more than one third of children and adolescents are overweight or obese. Physical inactivity and sedentary lifestyle are contributing factors of overweight and obesity. Increasing physical activity in overweight and obese individuals can potentially improve health status and lower the risk of major health problems. Based on the theoretical frameworks of behavioral change models, health information technologies, and pervasive interactive technologies, a conceptual model has been developed. The proposed model is an intervention method combining a behavior change model and a personalized Health IT system using an interactive accelerometer-based pervasive technology component, to increase physical activity potentially in an overweight and obese population. The accelerometer automatically synchronizes with the personal health record database over wireless networks; the decision engine utilizes the theory of planned behavior model to form a feedback; and; proper interactive feedback is provided directly to the users in the personal health record interface. A prototype was developed based on the conceptual model. The prototype measures and stores the number of steps, type of steps and caloric consumption on a daily basis with an interval of 20 minutes by an advanced accelerometer that can simply be attached to any footwear. The accelerometer synchronizes automatically the stored data with a central database as soon as the participant enters a designated wireless area. Virtual characters that are embedded inside a personal health record system convey the feedback to the users. The feedback is generated based on the theory of planned behavior decision model utilizing the stored daily physical activity data. The interface prompts knowledge-based information, presents self-monitoring trend lines, and shows virtual character changes over time such as becoming obese, to reflect the tailored feedback message. In addition, the interface is integrated in a popular social-networking website where users can review other virtual characters and generate peer pressure. The purpose of this study is to explore the feasibility of implementing a behavioral change intervention using pervasive health information technology among overweight and obese population. This research explains the development of the conceptual model, integration of wireless physical activity self-monitoring devices into personal health records, and the application of rich interactive media to convey messages to the users. The final prototype will be presented and preliminary findings will be discussed.

/pdf/increasing-physical-activity-by-implementing-a-behavioral-1bhh90rckj.pdf

Increasing physical activity by implementing a behavioral change intervention using pervasive personal health record system: an exploratory study

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Increasing physical activity by implementing a behavioral change intervention using pervasive personal health record system: an exploratory study