Bayesian mixture model estimation of aerosol particle size distributions

In this paper, we examine approaches to estimate a Bayesian mixture model at both single and multiple time points for a sample of actual and simulated aerosol particle size distribution (PSD) data. For estimation of a mixture model at a single time point, we use Reversible Jump Markov Chain Monte Carlo (RJMCMC) to estimate mixture model parameters including the number of components which is assumed to be unknown. We compare the results of this approach to a commonly used estimation method in the aerosol physics literature. As PSD data is often measured over time, often at small time intervals, we also examine the use of an informative prior for estimation of the mixture parameters which takes into account the correlated nature of the parameters. The Bayesian mixture model offers a promising approach, providing advantages both in estimation and inference.

Monitoring temporal changes in use of two cathinones in a large urban catchment in Queensland, Australia

Wastewater analysis was used to examine prevalence and temporal trends in the use of two cathinones, methylone and mephedrone, in an urban population (>200,000 people) in South East Queensland, Australia. Wastewater samples were collected from the inlet of the sewage treatment plant that serviced the catchment from 2011 to 2013. Liquid chromatography coupled with tandem mass spectrometry was used to measure mephedrone and methylone in wastewater sample using direct injection mode. Mephedrone was not detected in any samples while methylone was detected in 45% of the samples. Daily mass loads of methylone were normalized to the population and used to evaluate methylone use in the catchment. Methylone mass loads peaked in 2012 but there was no clear temporal trend over the monitoring period. The prevalence of methylone use in the catchment was associated with the use of MDMA, the more popular analogue of methylone, as indicated by other complementary sources. Methylone use was stable in the study catchment during the monitoring period whereas mephedrone use has been declining after its peak in 2010. More research is needed on the pharmacokinetics of emerging illicit drugs to improve the applicability of wastewater analysis in monitoring their use in the population.

The psychometric properties of the Kessler Psychological Distress Scale (K6) in a general population sample of adolescents

The 6-item Kessler Psychological Distress Scale (K6; Kessler et al., 2002) is a screener for psychological distress that has robust psychometric properties among adults. Given that a significant proportion of adolescents experience mental illness, there is a need for measures that accurately and reliably screen for mental disorders in this age group. This study examined the psychometric properties of the K6 in a large general population sample of adolescents (N = 4,434; mean age = 13.5 years; 44.6% male). Factor analyses were conducted to examine the dimensionality of the K6 in adolescents and to investigate sex-based measurement invariance. This study also evaluated the K6 as a predictor of scores on the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997). The K6 demonstrated high levels of internal consistency, with the 6 items loading primarily on 1 factor. Consistent with previous research, females reported higher mean levels of psychological distress when compared with males. The identification of sex-based measurement noninvariance in the item thresholds indicated that these mean differences most likely represented reporting bias in the K6 items rather than true differences in the underlying psychological distress construct. The K6 was a fair to good predictor of abnormal scores on the SDQ, but predictive utility was relatively low among males. Future research needs to focus on refining and augmenting the K6 scale to maximize its utility in adolescents. (PsycINFO Database Record (c) 2015 APA, all rights reserved)