Examining the interactive effects of coach-created empowering and disempowering climate dimensions on athletes’ health and functioning

Based in Duda’s (2013) hierarchical and multidimensional conceptualisation of the motivational climate, the purpose of this study was to examine whether a coach-created empowering motivational climate moderated the debilitating effects of a disempowering motivational climate on athletes’ health and optimal functioning. Athletes (N = 406, M age = 23.1 years; 67% male) completed questionnaires assessing their perceptions of coach-created empowering and disempowering climates created in training and competition, enjoyment in sport, burnout symptoms, global self-worth, and symptoms of physical ill-health. Following the recommendations of Hayes (2013) and Dawson (2014), and using PROCESS (Hayes), moderated regression analyses showed that the interaction between disempowering and empowering climate dimensions was significant and predicted 1% unique variance in 3 outcome variables (i.e., enjoyment, reduced accomplishment, and physical symptoms). The Johnson-Neyman technique was employed to plot and probe the significant interactions, which revealed moderately strong to strong values of an empowering climate tempered the significant relationship between a disempowering climate and the three outcome variables. The findings from this study have implications for coach education and suggest programmes that train coaches to understand how to create empowering climates and avoid (or dramatically reduce) disempowering climates are warranted.     

A New Multilevel CART Algorithm for Multilevel Data with Binary Outcomes

The multilevel logistic regression model (M-logit) is the standard model for modeling multilevel data with binary outcomes. However, many assumptions and restrictions should be considered when applying this model for unbiased estimation. To overcome these limitations, we proposed a multilevel CART (M-CART) algorithm which combines the M-logit and single level CART (S-CART) within the framework of the expectation-maximization. Simulation results showed that the proposed M-CART provided substantial improvements on classification accuracy, sensitivity, and specific over the M-logit, S-CART, and single level logistic regression model when modeling multilevel data with binary outcomes. This benefit of using M-CART was consistently found across different conditions of sample size, intra-class correlation, and when relationships between predictors and outcomes were nonlinear and nonadditive.     

Support gaps in parent‐emerging adult dyads: The role of support quality

This study used a support gap approach to examine parental support to college‐going emerging adults. Based on data from 156 parent–child dyads, this study investigated whether discrepancies between the amounts of support that children received from parents and what they desired would be associated with both persons’ perceived support quality and individual and relational well‐being. Using polynomial regressions with response surface modeling, analyses demonstrated that, generally, support deficits (i.e., receiving less support than desired) were associated with poorer outcomes. However, support surpluses (i.e., receiving more support than desired) were not necessarily problematic, and children and parents exhibited different viewpoints regarding support surpluses. In addition, child‐reported support quality mediated several associations between support gaps and relationship satisfaction reported by both persons.     

Linking property crime using offender crime scene behaviour: A comparison of methods

This study compared the ability of seven statistical models to distinguish between linked and unlinked crimes. The seven models utilised geographical, temporal, and modus operandi information relating to residential burglaries (n = 180), commercial robberies, (n = 118), and car thefts (n = 376). Model performance was assessed using receiver operating characteristic analysis and by examining the success with which the seven models could successfully prioritise linked over unlinked crimes. The regression‐based and probabilistic models achieved comparable accuracy and were generally more accurate than the tree‐based models tested in this study. The Logistic algorithm achieved the highest area under the curve (AUC) for residential burglary (AUC = 0.903) and commercial robbery (AUC = 0.830) and the SimpleLogistic algorithm achieving the highest for car theft (AUC = 0.820). The findings also indicated that discrimination accuracy is maximised (in some situations) if behavioural domains are utilised rather than individual crime scene behaviours and that the AUC should not be used as the sole measure of accuracy in behavioural crime linkage research.     

FROM EXTENSION TO REVOLUTIONARY CHANGE IN CLINICAL PSYCHOANALYSIS: THE RADICAL INFLUENCE OF BION AND WINNICOTT

This paper addresses the radical departure of late Bion's and Winnicott's clinical ideas and practices from traditional psychoanalytic work, introducing a revolutionary change in clinical psychoanalysis. The profound significance and implications of their thinking are explored, and in particular Bion's conception of transformation in O and Winnicott's clinical‐technical revision of analytic work, with its emphasis on regression in the treatment of more disturbed patients. The author specifically connects the unknown and unknowable emotional reality‐O with unthinkable breakdown (Winnicott) and catastrophe (Bion). The author suggests that the revolutionary approach introduced by the clinical thinking of late Bion and Winnicott be termed quantum psychoanalysis. She thinks that this approach can coexist with classical psychoanalysis in the same way that classical physics coexists with quantum physics.     

《黄帝内经》阴阳二十五人分型的数学建模

目的:应用数学建模的方法探索<黄帝内经>阴阳二十五人分型的相应关系.方法:根据<黄帝内经>理论对阴阳(X1)、五行(X2)、五音(X3)和阴阳二十五人健康状态(Y)进行量化,通过SAS循环程序进行数据模拟,建立多元回归模型.结果:多元线性回归方程为Y=7452.24162+625 X1+25X2+0.09832X3.结论:方程揭示了阴阳、五行和五音与阴阳二十五人健康状态的理论关系,为进一步求证阴阳、五行、五音与健康的关系提供了一个数学模型.     

单病种平均住院日影响因素分析

为探讨单病种平均住院日的影响因素,采用多元逐步回归分析,对住院构成前5位病种的平均住院日影响因素进行分析。结果显示,有10个影响因素进入回归方程,不同病种平均住院日影响因素略有不同,是否转科对平均住院日影响最大。在医院管理过程中,需不断加强医院流程管理与改造,实施临床路径,合理制定医院平均住院日指标。     

二次响应面回归方法及其在个体-环境匹配研究中的使用

二次响应面回归分析是指二次多项式回归与响应面分析相结合的一种研究方法, 该方法在工业与组织心理学领域起源于个体&#8722;环境(P-E)匹配研究。它使用对个体&#8722;环境进行间接匹配测量的策略, 考察二者间的最佳匹配以及与结果变量的复杂关系, 并在三维空间对其进行检验和解释。该文在分析以往P-E匹配研究方法(例如差异分数)缺陷性的基础上, 阐述了二次响应面回归方法的产生与发展, 逻辑思想, 统计分析方法, 并以实例演示其操作步骤与结果解释, 以及相对于其他方法的优势与不足。     

行动控制在农村教师工作压力与工作倦怠中的作用:PSI理论的分析视角

采用logistic回归分析,考察了322名农村中小学教师的人口学变量和工作压力、行动控制风格、行动控制策略对其工作倦怠的风险预测能力,并借助结构方程模型进一步分析了各心理变量间的关系,从PSI理论角度诠释了倦怠形成的机制。结果发现:中专、高级职称、中高压力水平、低行动控制策略和状态导向是导致中小学教师工作倦怠的危险性因素;行动导向者的工作压力、工作倦怠及行动控制策略运用水平显著好于状态导向者;工作压力、行动控制风格对工作倦怠的直接效应显著;行动控制风格和行动控制策略在工作压力和工作倦怠间起中介作用。因此,PSI视角下的工作压力-工作倦怠模型能够更有效地解释工作倦怠的形成机制;借助PSI理论构建的干预训练,有助于预防和缓解工作倦怠。