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BackgroundOnline social networks are popular components of behavior-change websites. Research has identified the participation of certain network members who assume leadership roles by providing support, advice, and direction to other members. In the literature, these individuals have been variously defined as key players, posters, active users, or caretakers. Despite their identification, very little research has been conducted on the contributions or demographic characteristics of this population. For this study, we collectively categorized key players, posters, active users, and caretakers as superusers.ObjectivesTo analyze data from two large but distinct Web-assisted tobacco interventions (WATI) to help gain insight into superuser demographic characteristics and how they use social networks.MethodsWe extracted cross-sectional data sets containing posting behaviors and demographic characteristics from a free, publicly funded program (the Canadian Cancer Society’s Smokers’ Helpline Online: SHO), and a free, privately run program (StopSmokingCenter.net: SSC).ResultsWithin the reporting period (SHO: June 26, 2008 to October 12, 2010; SSC: May 17, 2007 to October 12, 2010), 21,128 individuals registered for the SHO and 11,418 registered for the SSC. Within the same period, 1670 (7.90%) registrants made at least one post in the SHO social network, and 1627 (14.25%) registrants made at least one post in the SSC social network. SHO and SSC superusers accounted for 0.4% (n = 95) and 1.1% (n = 124) of all registrants, and 5.7% (95/1670) and 7.62% (124/1627) of all social network participants, and contributed to 34.78% (29,422/84,599) and 46.22% (61,820/133,753) of social network content, respectively. Despite vast differences in promotion and group management rules, and contrary to the beliefs of group moderators, there were no statistically significant differences in demographic characteristics between the two superuser groups.ConclusionsTo our knowledge, this is the first study that compared demographic characteristics and posting behavior from two separate eHealth social networks. Despite vast differences in promotional efforts and management styles, both WATI attracted superusers with similar characteristics. As superusers drive network traffic, organizations promoting or supporting WATI should dedicate resources to encourage superuser participation. Further research regarding member dynamics and optimization of social networks for health care purposes is required.

Background29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans.ObjectiveDigital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies.MethodsGrounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence.ResultsOut of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%).ConclusionsThis study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus...

RIPPLE may enhance parents' awareness of children's weight status and motivation to change their children's lifestyle behaviors but should be improved prior to implementation. Findings from this research directly informed revisions to our SBIRT, which will undergo preliminary testing in a randomized controlled trial.

An MEG experiment was carried out in order to compare the processing of lexical-tonal and intonational contrasts, based on the tonal dialect of Roermond (the Netherlands). A set of words with identical phoneme sequences but distinct pitch contours, which represented different lexical meanings or discourse meanings (statement vs. question), were presented to native speakers as well as to a control group of speakers of Standard Dutch, a non-tone language. The stimuli were arranged in a mismatch paradigm, under three experimental conditions: in the first condition (lexical), the pitch contour differences between standard and deviant stimuli reflected differences between lexical meanings; in the second condition (intonational), the stimuli differed in their discourse meaning; in the third condition (combined), they differed both in their lexical and discourse meaning. In all three conditions, native as well as non-native responses showed a clear MMNm (magnetic mismatch negativity) in a time window from 150 to 250 ms after the divergence point of standard and deviant pitch contours. In the lexical condition, a stronger response was found over the left temporal cortex of native as well as non-native speakers. In the intonational condition, the same activation pattern was observed in the control group, but not in the group of native speakers, who showed a right-hemisphere dominance instead. Finally, in the combined (lexical and intonational) condition, brain reactions appeared to represent the summation of the patterns found in the other two conditions. In sum, the lateralization of pitch processing is condition-dependent in the native group only, which suggests that language experience determines how processes should be distributed over both temporal cortices, according to the functions available in the grammar.