Using naturalistic driving data, this study explored the prevalence of engagement in secondary tasks whilst driving through intersections, and investigated whether drivers manage and self-regulate such behaviour in response to variations in roadway and environmental conditions. Video recordings of in-vehicle and external scenes were coded for precisely defined categories of secondary tasks and related contextual variables. The findings indicated that nearly one-quarter of the total driving time at intersections was spent on secondary activities and that lower engagement occurred within intersections compared to phases immediately upstream or downstream. Drivers were less likely to occupy themselves with secondary tasks when their vehicles were moving than when they were stationary. https://www.selleckchem.com/products/dx3-213b.html Elderly drivers showed less inclination to perform secondary tasks than did younger drivers. Lastly, drivers tended to perform secondary tasks less frequently at intersections managed by traffic signs than those controlled by traffic lights, when they did not have priority compared to when they had priority, and in adverse weather conditions compared to fine weather conditions. In conclusion, drivers appeared to self-regulate secondary task engagement in response to roadway and environmental conditions. Specifically, they exercised self-regulation by reducing their secondary task engagement when the driving task was more challenging. The findings from this study provide preliminary evidence for targeting the education and training of drivers and media campaigns related to safe driving strategies and managing distractions. INTRODUCTION Lack of participation in cervical cancer screening in underserved populations has been attributed to access to care, particularly among women in rural areas. Federally Qualified Health Centers (FQHCs) were created to address this need in medically underserved populations. This study observed proximity to three health centers in relation to cervical cancer screening rates in South Carolina. METHODS Data were obtained from FQHC patient visits (from 3 centers) between 2007-2010 and were limited to women eligible for cervical cancer screening (n = 24,393). ArcGIS was used to geocode patients addresses and FQHC locations, and distance was calculated. Modified Poisson regression was used to estimate relative risk of obtaining cervical cancer screening within one yearor ever, stratified by residential area. RESULTS Findings differed markedly by center and urban/rural status. At two health clinics, rural residents living the furthest away from the clinic (∼9 miles difference between quartile 4 and quartile 1) were more likely to be ever screened (RRs = 1.05 and 1.03, p-values less then 0.05), while urban residents living the furthest away were less likely to be ever screened (RR = 0.85, p-value less then 0.05). At the third center, only urban residents living the furthest away were more likely to be ever screened (RR = 1.02, p-value less then 0.05). CONCLUSIONS Increased travel distance significantly increased the likelihood of cervical cancer screening at two FQHC sites while significantly decreasing the likelihood of screening at the 3rd site. These findings underscore the importance of contextual and environmental factors that impact use of cervical cancer screening services. Triclosan (TCS), an antimicrobial agent widely used in personal care products and ubiquitously exists in environment, has drawn increasing concern due to its potential to exert multiple adverse effects, ranging from endocrine disruption to carcinogenesis. However, the mechanism of these adverse effects is still not fully elucidated. More and more studies have shown that chemical reactive metabolites (RMs) covalently binding to proteins is a possible reason for these adverse effects, but there is still a lack of appropriate methods to predict or evaluate these adverse effects due to the extremely low abundance of the modified proteins in complex biological samples. In this study, we attempted to address this problem and investigate the possible mechanism of TCS adverse effects by a shotgun proteomics approach based on three-dimensional-liquid chromatography-mass spectrometry (3D-LC-MS). First, the in vitro incubation with model amino acids and protein in microsomes showed that TCS could react with cysteine residue of proteins through 3 types of RMs. Then, a 3D-LC-MS approach was developed to sensitively determine the low abundant modified proteins, which resulted in the identification of 45 TCS-modified proteins, including albumin, haptoglobin and NR1I2, in rats. STRING analysis indicated that these modified proteins mainly were involved in reproductive and development system, endocrine and immune system, and carcinogenesis, which were in accord with the main reported TCS-induced adverse effects and suggested that the covalent modification of TCS RMs for proteins might affect their activities and functions, thus inducing serious adverse effects. This study provided a new insight into the mechanism of TCS adverse effects and may serve as a valuable method to predict or evaluate adverse effects of ubiquitous chemicals. Research has identified heterogeneous subgroups of individuals based on posttraumatic stress disorder (PTSD) and depression symptoms. Using data collected from military personnel in India (N = 146) and U.S. (N = 194), we examined (1) the best-fitting latent class solution; (2) multi-group invariance of the class solution; and (3) construct validity of optimal class solution. Results indicated that the optimal 4-class solution differed in severity and severity/type in the India and U.S. samples respectively. With similarity in the optimal number of classes across cultural samples, the meaning/nature of classes differed. In the India sample, anxiety severity predicted the Low Severity Class vs. all other classes, and the Moderately High Severity/High Severity Classes vs. the Moderately Low Severity Class; number of traumas predicted the High Severity Class vs. other classes; and resilience predicted the Moderately Low Severity Class vs. the Moderately High Severity Class. In the U.S. sample, alcohol use predicted the High Severity Class vs.