Suchergebnisse

This study examined the efficacy of the Jawbone UP platform for increasing physical activity and improving sleep quality among African American college women using a randomized controlled trial. Participants were college-aged (19.9 ± 1.7 years) African American women ( N = 69) at a southeastern midsize university in United States. The trial began in September 2013 and concluded in February 2014. Each group received similar brief training to use the respective platforms and weekly emails encouraged regular continued engagement. There was a significant difference at the 8-week follow-up, such that the intervention group decreased step counts relative to the comparison app (9,378 vs. 11,287 steps; p = .02). For sleep, neither group demonstrated any changes in sleep duration, sleep onset latency, wakefulness after sleep onset, or sleep efficiency at the 6-week posttest or 8-week follow-up. This study found no evidence for initial efficacy as a stand-alone tool for increasing physical activity or improving sleep.

AbstractEstimation of microorganism concentration in samples (bacterial cells or viral particles) has been a focal point in biomedical experiments for more than a century. Serial dilution of the samples is often used to estimate the target concentrations in immunology, virology, and pharmaceutical industry. A new methodology, called joint likelihood estimation (JLE), is proposed to estimate particles such as the number of microorganisms in a sample from counts obtained by serially diluting the sample. It models count data from the entire single dilution series rather than using only specific dilutions. The theoretical framework is based on the binomial and the Poisson distributions and is consistent with the actual experimental process. The estimator of the target concentration is obtained by MLE with derived joint likelihood functions of the observed counts including right‐censored values. Simulations demonstrated that the new JLE method significantly increases precision and accuracy of the estimate compared to the existing methods. It can be applied to a variety of studies with similar experimental designs, especially when the number of particles in the neat sample is very large.