IntroductionAmazon’s Mechanical Turk (MTurk) is frequently used to administer health-related surveys and experiments at a low cost, but little is known about its representativeness with regards to health status and behaviors.MethodsA cross-sectional survey comprised of questions from the nationally-representative 2014 Behavioral Risk Factor Surveillance System (BRFSS) and 2014 National Health and Nutrition Examination Survey (NHANES) was administered to 591 MTurk workers and 393 masters in 2016. Health status (asthma, depression, BMI, and general health), health behaviors (influenza vaccination, health insurance, smoking, and physical activity), and demographic characteristics of the two MTurk populations (workers and masters) were compared to each other and, using Poisson regression, to a nationally-representative BRFSS and NHANES samples.ResultsWorkers and master demographics were similar. MTurk users were more likely to be aged under 50 years compared to the national sample (86% vs. 55%) and more likely to complete a college degree than the national sample (50% vs. 26%). Adjusting for covariates, MTurk users were less likely to be vaccinated for influenza, to smoke, to have asthma, to self-report being in excellent or very good health, to exercise, and have health insurance but over twice as likely to screen positive for depression relative to a national sample. Results were fairly consistent among different age groups.ConclusionsMTurk workers are not a generalizable population with regards to health status and behaviors; deviations did not follow a trend. Appropriate health-related uses for MTurk and ways to improve upon the generalizability of MTurk health studies are proposed.

Introduction Child care is an important setting for the promotion of physical activity (PA) in early childhood. The purpose of this study was to examine the associations between specific PA environments and recommended practices in child care settings as well as the degree to which child care settings met recommended standards for total PA time. Methods In 2013, all programs licensed to care for children ages 2 to 5 in WA state were surveyed about their PA related practices. Logistic regression was used to determine odds of meeting best-practice standards for outdoor time and PA. Results The response rate was 45.8% from centers (692/1,511) and 32.1% from homes (1,281/3,991). Few programs reported meeting best-practice standards for the amount of time children spend being physically active (centers: 12.1%, homes: 20.1%) and outdoor time (centers: 21.8%, homes: 21.7%). Programs where children go outside regardless of weather and those reporting more adult-led PA had higher odds of meeting best-practice standards for both PA and outdoor time. Meeting best-practice standards for outdoor time was the strongest predictor of meeting best-practice standards for total PA time (centers: OR 15.9 (9.3 – 27.2), homes: OR 5.2 (3.8–7.1)). Conclusions for Practice There is considerable room for improvement in licensed child care settings in WA to meet best-practice standards for young children’s outdoor and PA time. Initiatives that create policies and environments encouraging outdoor play and adult-led physical activity in child care have the potential to increase physical activity in substantial numbers of young children.

Two pilot randomized clinical trials suggest parents-as-peer interventionists in FBT may be feasible, efficacious, and delivered at lower costs, with perhaps some additional benefits to serving as a peer interventionist. More robust investigation is warranted of peer treatment delivery models for pediatric weight management.