BackgroundThe dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change.ObjectiveThe intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions.MethodsEight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where “population” included child or adult populations, including healthy and disease populations; “intervention” involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; “comparator” was either a control group or within subject in the case of pre-post study designs; “outcomes” included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and “study design” included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen’s d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized.ResultsA total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from −0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity).ConclusionsTo date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustain...

Background: Popular media, health experts and researchers talk about a paediatric 'obesity epidemic' with exponentially increasing rates of obesity and overweight. However, some recent reports suggest that prevalence may have plateaued. This study examined trends in the prevalence of Australian childhood overweight and obesity since 1985. Specifically, it aimed to determine whether there have been (a) overall increases in average body mass index (BMI), (b) differential patterns of change within age groups and (c) increases in BMI within each weight-status category. Method: Forty-one Australian studies of childhood weight status conducted between 1985 and 2008 were reviewed. The studies included data on 264 905 Australians aged 2-18 years, with raw data being available on 70 758 children (27%). Children were classified as overweight or obese based on BMI using the criteria of Cole et al. (BMJ, 2000). The prevalence estimates were adjusted for age and sex, and plotted against measurement year using Lowess plots and two-linear-segment models. Where raw data were available, BMI z-scores (UK 1990 standard) were plotted against measurement year for all children and children in various age groups. Lowess plots and two-linear-segment models were used to assess secular trends in BMI z-scores pre-and post-1996 within age, gender and weight-status categories. Results: There has been a plateau, or only slight increase, in the percentage of boys and girls classified as overweight or obese, with almost no change over the last 10 years. In boys and girls, prevalence rates have settled around 21-25% for overweight and obesity together, and 5-6% for obesity alone. Similar trends were found for BMI z-scores. These patterns were fairly consistent across the age span. Within each weight-status category, average BMI has not increased. Conclusions: Although levels of Australian paediatric overweight remain high, the prevalence of overweight and obesity seems to have flattened and has not followed the anticipated exponential trajectory.

® T t STUDY DESIGN: Systematic review. T t BACKGROUND: Despite improvements inself-reported symptoms and perceived functional ability after total hip arthroplasty (THA) and total knee arthroplasty (TKA), it is unclear whether changes in objectively measured physical activity (PA) occur after surgery. T t OBJECTIVE:To determine if objectively measured PA increases after THA and TKA in adults with osteoarthritis. T t METHODS:Five electronic databases were searched from inception to March 3, 2015. All study designs objectively measuring PA before and after THA or TKA were eligible, including randomized controlled trials, cohort studies, and case-control studies. Two reviewers independently screened abstracts and full texts and extracted study demographic, PA, and clinical outcome data. Standardized mean differences (SMDs) and 95% confidence intervals were calculated for accelerometer-and pedometer-derived estimates of PA. Risk of methodological bias was assessed with Critical Appraisal Skills Programme checklists. T t RESULTS:Eight studies with a total of 373 participants (238 TKA, 135 THA) were included. Findings were mixed regarding improvement in objectively measured PA at 6 months after THA (SMDs, -0.20 to 1.80) and TKA (SMDs, -0.36 to 0.63). Larger improvements from 2 studies at 1 year postsurgery were generally observed after THA (SMDs, 0.39 to 0.79) and TKA (SMDs, 0.10 to 0.85). However, at 1 year, PA levels were still considerably lower than those of healthy controls (THA SMDs, -0.25 to -0.77; TKA SMDs, -1.46 to -1.80). Risk-of-bias scores ranged from 3 to 9 out of 11 (27%-82%) for cohort studies, and from 3 to 8 out of 10 (30%-80%) for case-control studies. T t CONCLUSION:The best available evidence indicates negligible changes in PA at 6 months after THA or TKA, with limited evidence for larger changes at 1 year after surgery. In the 4 studies that reported control-group data, postoperative PA levels were still considerably less than those of healthy controls. Improved perioperative strategies to instill behavioral change are required to narrow the gap between patient-perceived functional improvement and the actual amount of PA undertaken after THA and TKA. Registered with PROSPE-RO (registration number CRD42014010155). T t LEVEL OF EVIDENCE:Therapy, level 2a.

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Background Mobile ecological momentary assessment (mEMA) permits real-time capture of self-reported participant behaviors and perceptual experiences. Reporting of mEMA protocols and compliance has been identified as problematic within systematic reviews of children, youth, and specific clinical populations of adults. Objective This study aimed to describe the use of mEMA for self-reported behaviors and psychological constructs, mEMA protocol and compliance reporting, and associations between key components of mEMA protocols and compliance in studies of nonclinical and clinical samples of adults. Methods In total, 9 electronic databases were searched (2006-2016) for observational studies reporting compliance to mEMA for health-related data from adults (>18 years) in nonclinical and clinical settings. Screening and data extraction were undertaken by independent reviewers, with discrepancies resolved by consensus. Narrative synthesis described participants, mEMA target, protocol, and compliance. Random effects meta-analysis explored factors associated with cohort compliance (monitoring duration, daily prompt frequency or schedule, device type, training, incentives, and burden score). Random effects analysis of variance (P≤.05) assessed differences between nonclinical and clinical data sets. Results Of the 168 eligible studies, 97/105 (57.7%) reported compliance in unique data sets (nonclinical=64/105 [61%], clinical=41/105 [39%]). The most common self-reported mEMA target was affect (primary target: 31/105, 29.5% data sets; secondary target: 50/105, 47.6% data sets). The median duration of the mEMA protocol was 7 days (nonclinical=7, clinical=12). Most protocols used a single time-based (random or interval) prompt type (69/105, 65.7%); median prompt frequency was 5 per day. The median number of items per prompt was similar for nonclinical (8) and clinical data sets (10). More than half of the data sets reported mEMA training (84/105, 80%) and provision of participant incentives (66/105, 62.9%). Less than half of the data sets reported number of prompts delivered (22/105, 21%), answered (43/105, 41%), criterion for valid mEMA data (37/105, 35.2%), or response latency (38/105, 36.2%). Meta-analysis (nonclinical=41, clinical=27) estimated an overall compliance of 81.9% (95% CI 79.1-84.4), with no significant difference between nonclinical and clinical data sets or estimates before or after data exclusions. Compliance was associated with prompts per day and items per prompt for nonclinical data sets. Although widespread heterogeneity existed across analysis (I2>90%), no compelling relationship was identified between key features of mEMA protocols representing burden and mEMA compliance. Conclusions In this 10-year sample of studies using the mEMA of self-reported health-related behaviors and psychological constructs in adult nonclinical and clinical populations, mEMA was applied across contexts and health conditions and to collect a range of health-related data. There was inconsistent reporting of compliance and key features within protocols, which limited the ability to confidently identify components of mEMA schedules likely to have a specific impact on compliance.