Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: As mobile technology continues expanding, researchers have been using mobile phones to conduct health interventions (mHealth interventions). The multiple features of mobile devices offer great opportunities to disseminate large-scale, cost-efficient, and tailored messages to participants. However, the interventions to date have shown mixed results, with a large variance of effect sizes (Cohen’s d = -.62 to 1.65). Objective: To generate cumulative knowledge that informs mHealth intervention research, the aims of the current study are twofold: (a) to calculate an overall effect magnitude for mHealth interventions compared to alternative interventions/conditions and (b) to analyze potential moderators of mHealth interventions’ comparative efficacy. Methods: Comprehensive searches of the Communication & Mass Media Complete, PsycINFO, Web of Knowledge, Academic Search Premier, PubMed and Medline databases were conducted to identify potentially eligible studies in peer-reviewed journals and conference proceedings as well as dissertations and theses. Search queries were formulated using a combination of search terms: “intervention” (Title/Abstract) AND “health” (Title/Abstract) AND “*phone*” OR “black-berr*” (OR mHealth OR “application*” OR app* OR mobile OR cellular OR “short messag*” OR palm* OR iPhone* OR MP3* OR MP4* OR iPod*) (Title/Abstract). Results: The search resulted in 3,424 potential studies, the abstracts (and full text, as necessary) of which were reviewed for relevance. Studies were screened in multiple stages using explicit inclusion and exclusion criteria, and citations were evaluated for inclusion of qualified studies. A total of 61 studies were included in the current meta-analysis. Results showed that mHealth interventions are relatively more effective than comparison interventions/conditions, with a small but significant overall weighted effect size (d = 0.31). Additionally, the effects of interventions are moderated by theoretical paradigm, three engagement types (i.e., changing personal environment, reinforcement tracking, social presentation), mobile use type, intervention channel, and length of follow-up. Conclusions: To the best of our knowledge, this is the most comprehensive meta-analysis to date that examined the overall effectiveness of mHealth interventions across health topics and is the first study that statistically tested moderators. Our findings not only shed light on intervention design using mobile devices, but also provide new directions for research in health communication and promotion using new media. Future scholarship is needed to examine the effectiveness of mHealth interventions across various health issues, especially those that have not yet been investigated (e.g., substance use, sexual health), engaging participants using social features on mobile devices, and designing tailored mHealth interventions for diverse subpopulations to maximize effects.

The increasing popularity of social networking sites (SNSs) has drawn scholarly attention in recent years, and a large amount of efforts have been made in applying SNSs to health behavior change interventions. However, these interventions showed mixed results, with a large variance of effect sizes in Cohen’s d ranging from −1.17 to 1.28. To provide a better understanding of SNS-based interventions’ effectiveness, a meta-analysis of 21 studies examining the effects of health interventions using SNS was conducted. Results indicated that health behavior change interventions using SNS are effective in general, but the effects were moderated by health topic, methodological features, and participant features. Theoretical and practical implications of findings are discussed.

Recognizing the purchasing power of Chinese shoppers in the global luxury market, this study explores the luxury-brand preferences of a unique transnational consumer community of young, cosmopolitan Chinese consumers. Specifically, the effects of Chinese consumers’ American and Chinese cultural identifications on their snob and bandwagon luxury-brand preferences are examined. The mediating effects of bridging and bonding social capital, consumer susceptibility to normative influence, and consumer need for uniqueness are also considered. Study findings advance existing theoretical understanding of luxury consumption and provide managerial implications for international luxury branding.

Haze has become one of the most life-threatening problems in China and affects over one billion Chinese people’s health. Chinese people have become more dependent on receiving health information from social media, especially Weibo and WeChat, which shapes their health perceptions and behaviors. To investigate how Chinese people’s exposure to health information on social media influenced their health protective behaviors in response to haze, particularly wearing a PM2.5 anti-haze mask, we conducted a longitudinal web-based survey of mainland Chinese. The results from the structural equation modeling showed that (a) attitude and descriptive norm positively mediated the relationships between using Weibo for health information and behavioral intention while descriptive norm negatively mediated the relationship between using WeChat for health information and intention, and that (b) attitude, descriptive norm, and injunctive norm significantly predicted behavioral intention and wearing mask, but perceived behavior control did not. Theoretical and practical implications are discussed.

This study applied the comprehensive model of information seeking (CMIS) to online cancer information and extended the model by incorporating an exogenous variable: interest in online health information exchange with health providers. A nationally representative sample from the Health Information National Trends Survey 4 Cycle 4 was analyzed to examine the extended CMIS in predicting online cancer information seeking. Findings from a structural equation model supported most of the hypotheses derived from the CMIS, as well as the extension of the model related to interest in online health information exchange. In particular, socioeconomic status, beliefs, and interest in online health information exchange predicted utility. Utility, in turn, predicted online cancer information seeking, as did information-carrier characteristics. An unexpected but important finding from the study was the significant, direct relationship between cancer worry and online cancer information seeking. Theoretical and practical implications are discussed.

We proposed a conceptual model to predict health information-seeking behaviors (HISBs) from three different sources (family, the Internet, doctors). To test the model, a structural equation modeling (SEM) analysis was conducted using data from the 2012 Annenberg National Health Communication Survey (ANHCS) (N = 3,285). Findings suggest higher social support from family predicts higher trust in health information from family members (abbreviated as trust in this article). Trust is positively related to HISBs from all three sources, with the path linking trust to HISB from family being the strongest. The effect of social support on HISB from family is partially mediated by trust, while effect of social support on HISBs from the Internet/doctors is fully mediated by trust. Implications of the study are discussed.