Web-based tailored intervention programs show considerable promise in effecting health-promoting behaviors and improving health outcomes across a variety of medical conditions and patient populations. This meta-analysis compares the effects of tailored versus nontailored web-based interventions on health behaviors and explores the influence of key moderators on treatment outcomes. Forty experimental and quasi-experimental studies (N =20,180) met criteria for inclusion and were analyzed using meta-analytic procedures. The findings indicated that web-based tailored interventions effected significantly greater improvement in health outcomes as compared with control conditions both at posttesting, d =.139 (95% CI = .111, .166, p <.001, k =40) and at follow-up, d =.158 (95% CI = .124, .192, p <.001, k =21). The authors found no evidence of publication bias. These results provided further support for the differential benefits of tailored web-based interventions over nontailored approaches. Analysis of participant/descriptive, intervention, and methodological moderators shed some light on factors that may be important to the success of tailored interventions. Implications of these findings and directions for future research are discussed.

Tailored health communication research represents a very promising line of inquiry that has the potential to produce major impacts on lifestyle behaviors. This study defines tailoring and discusses how tailored interventions operate, including comparing/ contrasting different tailoring channels. Next, the authors review the literature on tailored interventions to change lifestyle behaviors, with a focus on smoking cessation, dietary change, and physical activity, as well as interventions that address multiple lifestyle behaviors. Finally, future directions for tailoring research are discussed. To date, a large literature has amassed showing the promise of tailored programs delivered via print, Internet, local computer/kiosk, telephone, and interpersonal channels. Numerous studies demonstrate that these programs are capable of significant impacts on smoking cessation, dietary change, physical activity, and multiple behavior change. It is concluded that the potential of tailoring will be more fully realized as (a) the field builds a more cumulative science of tailoring and (b) greater dissemination of efficacious tailored programs takes place.

Background As mobile technology continues expanding, researchers have been using mobile phones to conduct health interventions (mobile health—mHealth—interventions). The multiple features of mobile phones 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 d =−0.62 to 1.65). Objective The study aimed to generate cumulative knowledge that informs mHealth intervention research. The aims were twofold: (1) to calculate an overall effect magnitude for mHealth interventions compared with alternative interventions or conditions, and (2) 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, conference proceedings, and dissertations and theses. Search queries were formulated using a combination of search terms: “intervention” (Title or Abstract) AND “health” (Title or 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 or Abstract). Cohen d was computed as the basic unit of analysis, and the variance-weighted analysis was implemented to compute the overall effect size under a random-effects model. Analysis of variance–like and meta-regression models were conducted to analyze categorical and continuous moderators, respectively. Results The search resulted in 3424 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 64 studies were included in the current meta-analysis. Results showed that mHealth interventions are relatively more effective than comparison interventions or conditions, with a small but significant overall weighted effect size (Cohen d =0.31). In addition, the effects of interventions are moderated by theoretical paradigm, 3 engagement types (ie, 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 mode...

This study examines direct and indirect effects of interactive communication in an antismoking social media campaign. To that end, we pose a multitheoretical framework that integrates communication mediation models and the Theory of Planned Behavior. To test the theorized model, we conducted an experiment using a two-group pretest-posttest design. Participants (N = 201) were randomly assigned into two experimental conditions: "campaign message reception only" as a control group and "message reception and social interaction" as a treatment group, in which the participants contributed to the antismoking campaign by posting their own campaign ideas and information they found through mediated and interpersonal communication. The findings show that interactive communication catalyzes the participants' information searching behaviors through diverse communication channels. In turn, increased media use plays a crucial role in changing their attitudes and perceived social norms about smoking behaviors, and eventually reducing smoking intention. This study affirms that the theory of planned behavior is effective in predicting behavioral intention and demonstrates the usefulness of a multitheoretical approach in interactive campaign research on social media.

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.