Schizotypal Personality Disorder: A Clinical Social Work Perspective

Schizotypal personality disorder (SPD) is considered to be a “schizophrenia spectrum disorder” as evidenced in part by its cross-listing in that chapter of the DSM-5. SPD is considered to be a condition with limited potential for positive change because one of its major features is the presence of a biologically based cognitive deficit. This assumption, however, is an example of the medical model’s creating a bias against psychosocial features that are always involved in character development. The social work profession’s bio-psycho-social perspectives focus more comprehensively on all features of the condition and promote a more optimistic view of clients’ change potentials. The purposes of this paper are to examine SPD from a social work perspective and to demonstrate, with a case example, how effective intervention can be organized and delivered.     

Bayes shrinkage estimator for consistency assessment of treatment effects in multi-regional clinical trials

The primary objective of a multi-regional clinical trial is to investigate the overall efficacy of the drug across regions and evaluate the possibility of applying the overall trial result to some specific region. A challenge arises when there is not enough regional sample size. We focus on the problem of evaluating applicability of a drug to a specific region of interest under the criterion of preserving a certain proportion of the overall treatment effect in the region. We propose a variant of James-Stein shrinkage estimator in the empirical Bayes context for the region-specific treatment effect. The estimator has the features of accommodating the between-region variation and finiteness correction of bias. We also propose a truncated version of the proposed shrinkage estimator to further protect risk in the presence of extreme value of regional treatment effect. Based on the proposed estimator, we provide the consistency assessment criterion and sample size calculation for the region of interest. Simulations are conducted to demonstrate the performance of the proposed estimators in comparison with some existing methods. A hypothetical example is presented to illustrate the application of the proposed method.     

The precision of regression-type estimator for incremental cost–effectiveness ratio

The estimation of incremental cost–effectiveness ratio (ICER) has received increasing attention recently. It is expressed in terms of the ratio of the change in costs of a therapeutic intervention to the change in the effects of the intervention. Despite the intuitive interpretation of ICER as an additional cost per additional benefit unit, it is a challenge to estimate the distribution of a ratio of two stochastically dependent distributions. A vast literature regarding the statistical methods of ICER has developed in the past two decades, but none of these methods provide an unbiased estimator. Here, to obtain the unbiased estimator of the cost–effectiveness ratio (CER), the zero intercept of the bivariate normal regression is assumed. In equal sample sizes, the Iman–Conover algorithm is applied to construct the desired variance–covariance matrix of two random bivariate samples, and the estimation then follows the same approach as CER to obtain the unbiased estimator of ICER. The bootstrapping method with the Iman–Conover algorithm is employed for unequal sample sizes. Simulation experiments are conducted to evaluate the proposed method. The regression-type estimator performs overwhelmingly better than the sample mean estimator in terms of mean squared error in all cases.     

Work,parenting and gender: the care–work negotiations of three couple relationships in the UK

Changes globally mean that there are now record numbers of mothers in paid employment and a reported prevalence of involved fathering. This poses challenges to mothers and fathers as they negotiate care–work practices within their relationships. Focusing on interviews with three heterosexual couples (taken from a wider UK qualitative project on working parents), the paper considers care–work negotiations of three couples, against a backdrop of debates about intensive mothering and involved fathering. It aims to consider different configurations of work and care within three different couple relationships. We found that power within the relationships was negotiated along differential axis of gender and working status (full- or part-time paid work). We present qualitatively rich insights into these negotiations. Framed by a critical discursive psychological approach, we call on other researchers to think critically about dominant discourses and practices of working, caring and parenting, pointedly how couples situated around the world operationalise these discourses in talking about themselves as worker and carers.     

Generalizing the standardized hazard ratio to multivariate proportional hazards regression,with an application to clinical~genomic studies

The standardized hazard ratio for univariate proportional hazards regression is generalized as a scalar to multivariate proportional hazards regression. Estimators of the standardized log hazard ratio are developed, with corrections for bias and for regression to the mean in high-dimensional analyses. Tests of point and interval null hypotheses and confidence intervals are constructed. Cohort sampling study designs, commonly used in prospective–retrospective clinical genomic studies, are accommodated.     

基于可能自我概念的高职生心理健康教育

可能自我概念属于心理学范畴，本文通过分析当前环境下高职生的心理特点，结合可能自我横向和纵向两个方面的内容及其形成原因，介绍了在实际学生工作中如何利用这一概念做好思想教育工作，改善高职生自我认知，从根本上对这一群体给予心灵和行为上的关怀。     

Utilizing Bayesian predictive power in clinical trial design

The Bayesian paradigm provides an ideal platform to update uncertainties and carry them over into the future in the presence of data. Bayesian predictive power (BPP) reflects our belief in the eventual success of a clinical trial to meet its goals. In this paper we derive mathematical expressions for the most common types of outcomes, to make the BPP accessible to practitioners, facilitate fast computations in adaptive trial design simulations that use interim futility monitoring, and propose an organized BPP-based phase II-to-phase III design framework.     

Time‐Space Distanciation: An Interdisciplinary Account of How Culture Shapes the Implicit and Explicit Psychology of Time and Space

The growing body of research on temporal and spatial experience lacks a comprehensive theoretical approach. Drawing on Giddens’ framework, we present time‐space distanciation (TSD) as a construct for theorizing the relations between culture, time, and space. TSD in a culture may be understood as the extent to which (1) time and space are abstracted as separate dimensions and (2) activities are extended and organized across time and space. After providing a historical account of its development, we outline a multi‐level conceptualization of TSD supported by research on cultural differences in the experience of time and space. We impact this conceptualization by examining two ethnographic case studies. We conclude by highlighting future research directions. TSD is an integrative, interdisciplinary, multi level construct with the potential to guide the burgeoning social science of time and space.     

中国文化心理学论要

中国文化心理学的意义在于其作为一种话语，能够促进心理学体系间的对话和发展。中国文化心理学的核心内容在于关注现实的社会心理生活，提供理解和改变心理生活的独特视角。在方法论层面，中国文化心理学研究必须坚持多维一体、实用主义的研究方式。     

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.