Causal Attributions of Dementia Among Korean American Immigrants

To better understand conceptualizations of dementia, this study explored causal attributions of dementia among 209 Korean Americans, using a self-administered questionnaire in Korean. Findings show that Korean Americans endorsed various causal attributions. Factor analysis yielded 3 dimensions of their attributions including psychological, physical/environmental, and cognitive/social. Bivariate analyses showed that younger age and higher education were related to more physical/environmental attributions, and younger age was related to more cognitive/social attributions. The study provides an understanding of causal attributions of dementia that practitioners need to understand to provide culturally competent practice and highlights a need to customize public education messages by specific ethnic groups.     

An mHealth Approach to Extend a Brief Intervention for Adolescent Alcohol Use and Suicidal Behavior: Qualitative Analyses of Adolescent and Parent Feedback

Abstract

Mobile health (mHealth) tools that supplement inpatient psychiatric care can maintain and enhance intervention effects following hospitalization. Adolescents hospitalized following a suicidal event represent a vulnerable population who could greatly benefit from such an mHealth intervention. In specific, suicidal adolescents who drink alcohol are in need of robust interventions that address the bidirectional relationship between alcohol use and suicidal thoughts and behaviors, because it puts them at especially high risk for suicide upon discharge. The purpose of this study was to conduct qualitative interviews to gather feedback to improve a brief alcohol intervention provided to suicidal adolescents during psychiatric hospitalization, and to develop a mHealth tool to extend care after discharge. Participants, eight adolescents and their parents, identified the need for a smartphone application to deliver intervention content to adolescents and parents during the posthospitalization period. Adolescents sought support in meeting alcohol- and mood-related goals, while parents desired general resources as well as tips for conversations with their adolescent about mood and alcohol use.     

Parental transfer of financial knowledge and later credit outcomes among low- and moderate-income homeowners

It is well established that acquiring financial skills during childhood is linked with better savings in adulthood. Little is known, however, about the relationship between parental teaching of money management early in life and children's financial outcomes in adulthood. This is particularly true for low- and moderate-income (LMI) households. Using data from Community Advantage Program survey data for 2,389 LMI homeowners, we find that adults who report receiving high levels of money-management teaching in childhood from their parents are associated with higher credit scores and lower credit card debt in adulthood. We also find that the level of parental financial teaching influences the relationship between children's later educational attainment and credit scores. These findings suggest implications for initiatives promoting financial capability for parents and children.     

I’m not like everybody else: urbanization factors shaping spatial distribution of native and invasive ants are species-specific

Urbanization is a major global change inducing complex and multiple modifications of landscapes and ecosystems. The spatial distributions of organisms experiencing these modifications will likely shift specifically, depending on each species’ response to each environmental modification induced by urbanization. We sampled two ant genera (Lasius and Tetramorium) at 1248 locations along an urbanization gradient in Lyon, France and used high resolution spatial layers for 18 spatial (e.g., open habitat fragmentation, bioclimatic data and surface temperatures) and temporal (e.g., comparison of Normalized Difference Vegetation Index between 1986 and 2015) environmental variables associated with urbanization. Coupling two different analytical methods (Outlying Mean Index and Boosted Regression Trees), we showed that each species’ distribution was influenced by its own combination of environmental factors. Two morphologically cryptic Tetramorium species (T. sp.E and T. sp.U2) were both highly abundant but with opposite responses to urbanization: while T. sp.E was favored by urbanized habitat, T. sp.U2 avoided urbanized areas. Among Lasius species, we detected 63 occurrences of the invasive ant Lasius neglectus, the distribution of which was favored only by embankments along roads. We found that, even at this reduced spatial scale, climatic effects influenced most species and interacted with urbanization factors.     

A SAEM algorithm for the estimation of template and deformation parameters in medical image sequences

This paper is about object deformations observed throughout a sequence of images. We present a statistical framework in which the observed images are defined as noisy realizations of a randomly deformed template image. In this framework, we focus on the problem of the estimation of parameters related to the template and deformations. Our main motivation is the construction of estimation framework and algorithm which can be applied to short sequences of complex and highly-dimensional images. The originality of our approach lies in the representations of the template and deformations, which are defined on a common triangulated domain, adapted to the geometry of the observed images. In this way, we have joint representations of the template and deformations which are compact and parsimonious. Using such representations, we are able to drastically reduce the number of parameters in the model. Besides, we adapt to our framework the Stochastic Approximation EM algorithm combined with a Markov Chain Monte Carlo procedure which was proposed in 2004 by Kuhn and Lavielle. Our implementation of this algorithm takes advantage of some properties which are specific to our framework. More precisely, we use the Markovian properties of deformations to build an efficient simulation strategy based on a Metropolis-Hasting-Within-Gibbs sampler. Finally, we present some experiments on sequences of medical images and synthetic data.     

Adoptive Mothers' and Fathers' Psychological Distress: Parenting Teens Adopted from Birth

Abstract

This study tests pathways to adoptive parents' psychological distress over time and then examines gender differences in psychological distress. Participants included 190 adoptive mothers and 190 adoptive fathers from the longitudinal Minnesota/Texas Adoption Research Project, a study of U.S. domestic infant adoptions. The majority of adoptive parents reported low psychological distress 10 to 20?years post-adoption. Some struggled throughout their adopted youth’s childhood and adolescence. This study utilizes data allowing an examination of parenting during middle childhood and adolescence. For adoptive mothers and fathers, outside stressors significantly predicted psychological distress. For adoptive fathers, perceived parent–child incompatibility was also predictive.     

Stochastic proximal-gradient algorithms for penalized mixed models

Motivated by penalized likelihood maximization in complex models, we study optimization problems where neither the function to optimize nor its gradient has an explicit expression, but its gradient can be approximated by a Monte Carlo technique. We propose a new algorithm based on a stochastic approximation of the proximal-gradient (PG) algorithm. This new algorithm, named stochastic approximation PG (SAPG) is the combination of a stochastic gradient descent step which—roughly speaking—computes a smoothed approximation of the gradient along the iterations, and a proximal step. The choice of the step size and of the Monte Carlo batch size for the stochastic gradient descent step in SAPG is discussed. Our convergence results cover the cases of biased and unbiased Monte Carlo approximations. While the convergence analysis of some classical Monte Carlo approximation of the gradient is already addressed in the literature (see Atchadé et al. in J Mach Learn Res 18(10):1–33, 2017), the convergence analysis of SAPG is new. Practical implementation is discussed, and guidelines to tune the algorithm are given. The two algorithms are compared on a linear mixed effect model as a toy example. A more challenging application is proposed on nonlinear mixed effect models in high dimension with a pharmacokinetic data set including genomic covariates. To our best knowledge, our work provides the first convergence result of a numerical method designed to solve penalized maximum likelihood in a nonlinear mixed effect model.

     

SELECTING SATISFACTORY SECRETARIES

The probability of selecting the ath best out of n applicants in the secretary problem is evaluated by probabilistic arguments for monotone order k stopping rules. This leads to an explicit optimizing function for selecting (with payoffs) one of the k best applicants. This optimization problem can be solved directly both for a finite and for an unlimited number of applicants, yielding a variety of numerical results. Extensions are given for two choices with success if two applicants are selected from among the k best.