Exceptions to High School Dropout Predictions in a Low-Income Sample: Do Adults Make a Difference?

Adult–child relationship factors were examined to determine whether they differentiated between individuals who follow expected versus unexpected educational pathways. Low-income participants (96 men, 83 women) in the United States were followed from birth through age 23. Individuals were identified who followed expected versus unexpected pathways to high school graduation or dropping out based on academic achievement and behavioral problems. Patterns of parental involvement in school were significantly different between expected dropouts and unexpected graduates in middle childhood. In contrast, expected graduates had higher levels of parent involvement in middle childhood, more supportive parent–child relationships in early adolescence, and higher levels of social competence with adults than unexpected dropouts .     

A GIS Analysis of East Asian Care Gaps in Residential and Assisted Living Facilities in Vancouver,Canada

Residential care and assisted living services provide support to seniors who may not have the ability to live independently. However, East Asian residents often do not have sufficient access to culturally specific activities, which may result in psychosocial stress and isolation. This study presents a geographic analysis method to evaluate spatial distribution of culturally tailored senior care facilities in Metro Vancouver. We identify geographical disparities, indicating that many East Asian seniors have poor local access to a culturally tailored facility. We recommend the use of geographical analysis techniques to improve the analysis and planning for senior care in an increasingly diverse population.     

Invisible Scars: Comparing the Mental Health of LGB and Heterosexual Intimate Partner Violence Survivors

Intimate partner violence (IPV) affects countless women and men in lesbian, gay, and bisexual (LGB) as well as heterosexual relationships, but few studies have examined how such abuse is associated with the mental health of LGB victims. The present study addresses this issue using data from the 2006 Behavioral Risk Factor Surveillance System (BRFSS) survey to examine differences in depression and anxiety among IPV victims in LGB and heterosexual partnerships. The findings indicate LGB IPV victims are much more likely to have a history of depression (OR 1.70, p < .05) and anxiety (OR 1.70, p < .05) than heterosexual victims. These differences are slightly mediated by the victim’s perceived emotional support but not the type of abuse experienced. Our findings accentuate the need for greater inclusion of LGB persons in the IPV and mental health discourse, as well as the importance of social support for IPV victims. Policy implications for members of the LGB community are discussed.     

Variance estimation for integrated population models

State-space models are widely used in ecology. However, it is well known that in practice it can be difficult to estimate both the process and observation variances that occur in such models. We consider this issue for integrated population models, which incorporate state-space models for population dynamics. To some extent, the mechanism of integrated population models protects against this problem, but it can still arise, and two illustrations are provided, in each of which the observation variance is estimated as zero. In the context of an extended case study involving data on British Grey herons, we consider alternative approaches for dealing with the problem when it occurs. In particular, we consider penalised likelihood, a method based on fitting splines and a method of pseudo-replication, which is undertaken via a simple bootstrap procedure. For the case study of the paper, it is shown that when it occurs, an estimate of zero observation variance is unimportant for inference relating to the model parameters of primary interest. This unexpected finding is supported by a simulation study.     

Young adults and casual sex: the relevance of college drinking settings

This study investigated the relevance of college drinking settings on the likelihood of students having sexual intercourse with a stranger. A random sample of 7,414 undergraduates at 14 public California universities responded to questions regarding frequency of attendance at six different setting types since the beginning of the semester (e.g., Greek, residence-hall parties, and bars or restaurants), drinking behavior, and sexual activity. Multi-level modeling examined the association between each setting type and the occurrence of alcohol-related sexual intercourse with a stranger. Findings indicated strong, positive associations between frequency of attendance at Greek parties, residence-hall parties, off-campus parties, and the occurrence of alcohol-related sex with a stranger. Frequency of attending the six settings and proportion of times drunk at the settings were also positively associated with alcohol-related sex with a stranger. Efforts aimed at preventing outcomes associated with casual sex (e.g., pregnancy, sexually transmitted infections, or mental health) should target specific drinking settings where students might be at high risk for risky alcohol use and unsafe sex behaviors.     

Designing and analyzing clinical trials for personalized medicine via Bayesian models

Patients with different characteristics (e.g., biomarkers, risk factors) may have different responses to the same medicine. Personalized medicine clinical studies that are designed to identify patient subgroup treatment efficacies can benefit patients and save medical resources. However, subgroup treatment effect identification complicates the study design in consideration of desired operating characteristics. We investigate three Bayesian adaptive models for subgroup treatment effect identification: pairwise independent, hierarchical, and cluster hierarchical achieved via Dirichlet Process (DP). The impact of interim analysis and longitudinal data modeling on the personalized medicine study design is also explored. Interim analysis is considered since they can accelerate personalized medicine studies in cases where early stopping rules for success or futility are met. We apply integrated two-component prediction method (ITP) for longitudinal data simulation, and simple linear regression for longitudinal data imputation to optimize the study design. The designs' performance in terms of power for the subgroup treatment effects and overall treatment effect, sample size, and study duration are investigated via simulation. We found the hierarchical model is an optimal approach to identifying subgroup treatment effects, and the cluster hierarchical model is an excellent alternative approach in cases where sufficient information is not available for specifying the priors. The interim analysis introduction to the study design lead to the trade-off between power and expected sample size via the adjustment of the early stopping criteria. The introduction of the longitudinal modeling slightly improves the power. These findings can be applied to future personalized medicine studies with discrete or time-to-event endpoints.     

The Effects of Progressively Thinning High-Preference Item Delivery on Responding in Employees

The use of mixed-preference reinforcer delivery (i.e., the random delivery of a set of items with varying degrees of preference for each individual) with employees has been found to produce moderate levels of responding in an analog setting; however, mixed reinforcer delivery may not conform to the recommendations made by some popular writers in organizational behavior management. The current investigation used a progressively thinning high-preference stimulus delivery procedure to investigate the use of mixed reinforcer delivery with 5 employees. Results indicated that most participants did not reliably complete work when the percent chance of earning a high-preference item dropped below 100%. These results do not support the use of varied reinforcers in applied settings.