Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Gamification has been a predominant focus of the health app industry in recent years. However, to our knowledge, there has yet to be a review of gamification elements in relation to health behavior constructs, or insight into the true proliferation of gamification in health apps. The objective of this study was to identify the extent to which gamification is used in health apps, and analyze gamification of health and fitness apps as a potential component of influence on a consumer's health behavior. An analysis of health and fitness apps related to physical activity and diet was conducted among apps in the Apple App Store in the winter of 2014. This analysis reviewed a sample of 132 apps for the 10 effective game elements, the 6 core components of health gamification, and 13 core health behavior constructs. A regression analysis was conducted in order to measure the correlation between health behavior constructs, gamification components, and effective game elements. This review of the most popular apps showed widespread use of gamification principles, but low adherence to any professional guidelines or industry standard. Regression analysis showed that game elements were associated with gamification (P<.001). Behavioral theory was associated with gamification (P<.05), but not game elements, and upon further analysis gamification was only associated with composite motivational behavior scores (P<.001), and not capacity or opportunity/trigger. This research, to our knowledge, represents the first comprehensive review of gamification use in health and fitness apps, and the potential to impact health behavior. The results show that use of gamification in health and fitness apps has become immensely popular, as evidenced by the number of apps found in the Apple App Store containing at least some components of gamification. This shows a lack of integrating important elements of behavioral theory from the app industry, which can potentially impact the efficacy of gamification apps to change behavior. Apps represent a very promising, burgeoning market and landscape in which to disseminate health behavior change interventions. Initial results show an abundant use of gamification in health and fitness apps, which necessitates the in-depth study and evaluation of the potential of gamification to change health behaviors.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet

Background: One of the leading causes of death in the United States (US) is suicide and new methods of assessment are needed to track its risk in real time. Objective: Our objective is to validate the use of machine learning algorithms for Twitter data against empirically validated measures of suicidality in the US population. Methods: Using a machine learning algorithm, the Twitter feeds of 135 Mechanical Turk (MTurk) participants were compared with validated, self-report measures of suicide risk. Results: Our findings show that people who are at high suicidal risk can be easily differentiated from those who are not by machine learning algorithms, which accurately identify the clinically significant suicidal rate in 92% of cases (sensitivity: 53%, specificity: 97%, positive predictive value: 75%, negative predictive value: 93%). Conclusions: Machine learning algorithms are efficient in differentiating people who are at a suicidal risk from those who are not. Evidence for suicidality can be measured in nonclinical populations using social media data.

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

Despite decades of research surrounding determinants of alcohol and tobacco (A&T) use among adolescents, built environment influences have only recently been explored. This study used ordinal regression on 205 Latino adolescents to explore the influence of the built environment (proximity to A&T retailers) on A&T use, while controlling for recognized social predictors. The sample was 45% foreign-born. A&T use was associated with distance from respondents’ home to the nearest A&T retailer (−), acculturation (+), parents’ consistent use of contingency management (−), peer use of A&T (+), skipping school (+), attending school in immediate proximity to the US/Mexico border (+), and the interaction between the distance to the nearest retailer and parents’ consistent use of contingency management (+). The association between decreasing distance to the nearest A&T retailer and increased A&T use in Latino adolescents reveals an additional risk behavior determinant in the US–Mexico border region.