Identifying Mental Disorder from the Faces of Women with Borderline Personality Disorder

Although appearance-based cues can help to diagnose physical illness, visual manifestations of mental disorder may be more elusive. Here, we investigated whether individuals could distinguish women with a serious mental disorder (borderline personality disorder) from demographically- and IQ-matched non-psychiatric controls. Participants rated mentally ill targets as more likely to have a mental disorder from photos more accurately than chance, despite not believing that such judgments were possible. The configuration of facial cues played an important role in these judgments, as interfering with the spatial relationships between facial features reduced participants’ accuracy to chance guessing. Further investigation showed similar results when participants rated the targets for specific mental disorders (borderline personality disorder, major depressive disorder) and rated the mentally ill targets as more depressed, angry, anxious, disgusted, emotionally unstable, distressed, and less happy. Moreover, the depression ratings significantly correlated with the targets’ actual depressive symptoms. Thus, individuals may be able to infer aspects of mental disorder from minimal facial cues.     

U.S. CREDIT UNIONS: SURVIVAL,CONSOLIDATION, AND GROWTH

This study uses hazard function estimations and time‐series and cross‐sectional growth regressions to examine the impact of exit through merger and acquisition (M&A) or failure, and internally generated growth, on the firm‐size distribution within the U.S. credit union sector. Consolidation through M&A was the principal cause of a reduction in the number of credit unions, but impact on concentration was small. Divergence between the average internally generated growth of smaller and larger credit unions was the principal driver of the rise in concentration. (JEL G21)     

Split Hamiltonian Monte Carlo

We show how the Hamiltonian Monte Carlo algorithm can sometimes be speeded up by “splitting” the Hamiltonian in a way that allows much of the movement around the state space to be done at low computational cost. One context where this is possible is when the log density of the distribution of interest (the potential energy function) can be written as the log of a Gaussian density, which is a quadratic function, plus a slowly-varying function. Hamiltonian dynamics for quadratic energy functions can be analytically solved. With the splitting technique, only the slowly-varying part of the energy needs to be handled numerically, and this can be done with a larger stepsize (and hence fewer steps) than would be necessary with a direct simulation of the dynamics. Another context where splitting helps is when the most important terms of the potential energy function and its gradient can be evaluated quickly, with only a slowly-varying part requiring costly computations. With splitting, the quick portion can be handled with a small stepsize, while the costly portion uses a larger stepsize. We show that both of these splitting approaches can reduce the computational cost of sampling from the posterior distribution for a logistic regression model, using either a Gaussian approximation centered on the posterior mode, or a Hamiltonian split into a term that depends on only a small number of critical cases, and another term that involves the larger number of cases whose influence on the posterior distribution is small.     

An Examination of the Communication Styles Associated with Psychopathy and Their Influence on Observer Impressions

Psychopathic individuals are characterized as “intra-species predators”—callous, impulsive, aggressive, and proficient at interpersonal manipulation. For example, despite their high risk for re-offending, psychopathic offenders often receive early release on parole. While reputed to be social chameleons, research suggests that even naive observers can accurately infer high levels of psychopathic traits in others with very brief exposures to behavior, but accuracy degrades with extended observation. We utilized a lens model approach to examine the communication styles (emotional facial expressions, body language, and verbal content) of offenders varying in levels of psychopathic traits using “thin slice” video clips of psychological assessment interviews and to reveal which cues observers use to inform their evaluations of psychopathy. Psychopathic traits were associated with more (a) Duchenne smiles, (b) negative (angry) emotional language, and (c) hand gestures (illustrators). Further, psychopathy was associated with a marked behavioral incongruence; when individuals scoring high in psychopathic traits engaged in Duchenne smiles they were also more likely to use angry language. Naïve observers relied on each of these valid behavioral signals to quickly and accurately detect psychopathic traits. These findings provide insight into psychopathic communication styles, opportunities for improving the detection of psychopathic personality traits, and may provide an avenue for understanding successful psychopathic manipulation.     

Modeling probability density through ultraspherical polynomial transformations

We present a method for fitting parametric probability density models using an integrated square error criterion on a continuum of weighted Lebesgue spaces formed by ultraspherical polynomials. This approach is inherently suitable for creating mixture model representations of complex distributions and allows fully autonomous cluster analysis of high-dimensional datasets. The method is also suitable for extremely large sets, allowing post facto model selection and analysis even in the absence of the original data. Furthermore, the fitting procedure only requires the parametric model to be pointwise evaluable, making it trivial to fit user-defined models through a generic algorithm.     

VIF-based adaptive matrix perturbation method for heteroskedasticity-robust covariance estimators in the presence of multicollinearity

In this study, we investigate linear regression having both heteroskedasticity and collinearity problems. We discuss the properties related to the perturbation method. Important observations are summarized as theorems. We then prove the main result that states the heteroskedasticity-robust variances can be improved and that the resulting bias is minimized by using the matrix perturbation method. We analyze a practical example for validation of the method.     

The Moderating Effect of Living with a Child Before Incarceration on Postrelease Outcomes Related to a Prison-Based Parent Management Training Program

ABSTRACT

With the rapid growth in incarceration in the United States over the past few decades came dramatic growth in the number of the incarcerated parents with at least one minor child. Parental incarceration places extra stresses and strains on families and children. Almost all of those incarcerated will eventually be released. However, the majority of those released from prison will be rearrested within a year. Finding interventions that can decrease the likelihood of returning to crime and to incarceration are of utmost importance. Using a social bond theory framework, the authors examine the moderating effect of living with a child before incarceration on program outcomes related to a prison-based parent management training program. A significant effect was found. Implications for these findings are discussed for future research and practice.     

Structural and Contextual Factors Regarding the Accessibility of Elective Office for Women of Color at the Local Level

Different from the majority of past research on gender gaps in political officeholding, we adopt an intersectionality framework and move beyond traditional individual factors to explore what implications certain elements in the political opportunity structure may have for women and men of color elected officials serving in county, municipal, and local school board offices. We argue that structural and contextual factors, such as type of institutions, election systems, and jurisdictional racial makeup, may influence the calculations women of color make concerning the accessibility of elective office. Using data from the Gender and Multiracial Leadership (GMCL) project, we find county offices to be the least, and seats on school boards the most, accessible to women of color. Of the types of electoral arrangements, we find multimember districts (MMD) to be the most significant variable predicting the likelihood of women of color in office. Although both Black and Latina women benefit from having a significant share of coethnics or nonwhites in jurisdictions, the two groups of women have an opposite relationship to their racial constituent makeup than that held by their male counterparts.     

Impact of physical activity and sedentary behaviour on fall risks in older people: a systematic review and meta-analysis of observational studies

The objective of this work was to summarise and evaluate the evidence showing that physical activity is a protector factor as regards falls in older people. Relevant studies were identified through a systematic search in the MEDLINE and Cochrane Library, under the keywords of accidental fall/numerical data and risk factors, and with the bibliographies of retrieved papers. The combined odds ratio (OR) [95% confidence interval] for physical activity was 0.75 [0.64, 0.88] with moderate heterogeneity (I ²?=?33%). For fall injury, it was 0.59 [0.47, 0.74] and, for falls in general, it rose to 0.94 [0.76, 1.17] with nil heterogeneity. The combined OR for sedentary factors was 1.14 [1.10, 1.82] with moderate heterogeneity (I ²?=?36%). Regular physical activity in daily life yields significant reduction in falls in older people, especially falls with injuries.     

The Nigerian Civil Registration and Vital Statistics System: Contexts,Institutions, Operation

Civil Registration and Vital Statistics (CRVS) Systems are playing increasing roles in national and global data infrastructure, facilitating the achievement of key developmental goals. The performance of CRVS systems in many developing countries including Nigeria is sub optimal and information on their structure and operations scanty. This paper characterizes the statutory, institutional, and operational elements and social contexts of the Nigerian CRVS System. It includes a context analysis of the system and a review of improvement strategies and interventions. The paper shows that the Nigerian CRVS System is built on viable statutory and institutional platforms—the constitutional enshrinement of: universal, compulsory and continuous civil registration and, a central registration institution—the National Population Commission (NPC). NPC has registration hierarchy and infrastructure deployed at every level of political administration and mechanisms for efficient coordination of registration and production of vital statistics on live-births, deaths and stillbirths amongst other vital events. The major weaknesses of the system include inadequate financing and deployment of registration facilities, conflicting statutes and institutional arrangements for the registration of key events like death and stillbirths. Other weaknesses include intra-organizational conflicts in resource allocation and weak ICT infrastructure within the NPC. These are compounded by overarching contextual issues namely registration unfriendly sociocultural norms, weak national data infrastructure, systemic corruption, poverty and undeveloped civic culture. Domestic initiatives and interventions to improve the system have focused on birth registration, while multilateral interventions have only made a modest impact on the system. Thus, holistic in-country improvement initiatives supported with robust interventions are imperative to overcome weaknesses in the Nigerian CRVS system. However fundamental improvements in CRVS systems in developing countries like Nigeria may likely only follow sustainable solutions to overarching contextual issues especially poor infrastructure, weak institutions, poverty and systemic corruption.