The smartphone plays a major role in providing and integrating more features into a single device for the purpose of communication, entertainment, information seeking, e-services, healthcare, and agriculture. As such, it is important to study the influence of smartphones on various contexts. Hence this research looked at the influence of attitude on usage types among smartphone users in Chennai city, Tamil Nadu during October 2017. The study adopted the survey method to get responses from smartphone users. The result of the study indicates that the respondents of the study have a more positive attitude towards smartphones. The smartphone is mostly accessed for social use among the participants. With respect to age group, anxiety and compulsive use are significant and other variables are found to be non-significant. Males have a significant role in a negative attitude towards compulsive and social usage, and females have an important role in a positive attitude towards process and social usage and anxiety towards process usage.

Background The prevalence of obesity in India is increasing at an alarming rate. Obesity-related mHealth apps have proffered an exciting opportunity to remotely deliver obesity-related information. This opportunity raises the question of whether such apps are truly effective. Objective The aim of this study was to identify existing obesity-related mHealth apps in India and evaluate the potential of the apps’ contents to promote health behavior change. This study also aimed to discover the general quality of obesity-related mHealth apps. Methods A systematic search for obesity-related mHealth apps was conducted in both the Google Play Store and the Apple App Store. The features and quality of the sample apps were assessed using the Mobile Application Rating Scale (MARS) and the potential of the sample apps’ contents to promote health behavior change was assessed using the PRECEDE-PROCEED Model (PPM). Results A total of 13 apps (11 from the Google Play Store and 2 from the Apple App Store) were considered eligible for the study. The general quality of the 13 apps assessed using MARS resulted in mean scores ranging from 1.8 to 3.7. The bivariate Pearson correlation between the MARS rating and app user rating failed to establish statistically significant results. The multivariate regression analysis result indicated that the PPM factors are significant determinants of health behavior change (F3,9=63.186; P<.001) and 95.5% of the variance (R2=0.955; P<.001) in the dependent variable (health behavior change) can be explained by the independent variables (PPM factors). Conclusions In general, mHealth apps are found to be more effective when they are based on theory. The presence of PPM factors in an mHealth app can greatly influence the likelihood of health behavior change among users. So, we suggest mHealth app developers consider this to develop efficient apps. Also, mHealth app developers should consider providing health information from credible sources and indicating the sources of the information, which will increase the perceived credibility of the apps among the users. We strongly recommend health professionals and health organizations be involved in the development of mHealth apps. Future research should include mHealth app users to understand better the apps’ effectiveness in bringing about health behavior change.

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