The Longevity Effects of Religious and Nonreligious Participation: A Meta‐Analysis and Meta‐Regression

Scholars have long argued that the reduced mortality risk associated with frequent participation in religious services derives from two sources: social participation and religious belief efficacy. In contrast, the reduced mortality risk associated with participation in nonreligious groups is thought to derive solely from the social participation component. This study tests the religious efficacy hypothesis by comparing the effects of religious participation with nonreligious participation using meta‐analyses of 312 mortality risk estimates from 74 publications (providing data on more than 300,000 persons). We found no significant difference between the mean hazard ratio (HR) for low religious participation (HR, 1.32; 95% CI, 1.24–1.41) and the mean HR for low nonreligious participation (HR, 1.25; 95% CI, 1.17–1.33). These findings suggest that the positive health effects of religious participation may largely be attributed to the social participation component, rather than to the religious component of the act.     

Meta-Analysis of Pragmatic and Theoretical Research: A Critique

Meta-analysis refers to a set of statistical procedures used to summarize and integrate many empirical studies that focus on one issue. This numerical method of integrating research findings is said to be superior to the narrative type of reviews because it is more objective, reliable, and rigorous. Moreover, the meta-analytic approach is supposedly capable of resolving research controversies, strengthening empirical hypotheses, and discovering new relationships among variables. In this study, these claims are examined and found to be wanting. Some objections to the use of meta-analysis as a means of substantiating theoretical assertions are raised with reference to the rationale of experimentation and to how knowledge evolves. It is concluded that it is inappropriate to apply meta-analysis to integrate theoretical research.     

A Data Analysis Method for Using Longitudinal Binary Outcome Data from a SMART to Compare Adaptive Interventions

Sequential multiple assignment randomized trials (SMARTs) are a useful and increasingly popular approach for gathering information to inform the construction of adaptive interventions to treat psychological and behavioral health conditions. Until recently, analysis methods for data from SMART designs considered only a single measurement of the outcome of interest when comparing the efficacy of adaptive interventions. Lu et al. proposed a method for considering repeated outcome measurements to incorporate information about the longitudinal trajectory of change. While their proposed method can be applied to many kinds of outcome variables, they focused mainly on linear models for normally distributed outcomes. Practical guidelines and extensions are required to implement this methodology with other types of repeated outcome measures common in behavioral research. In this article, we discuss implementation of this method with repeated binary outcomes. We explain how to compare adaptive interventions in terms of various summaries of repeated binary outcome measures, including average outcome (area under the curve) and delayed effects. The method is illustrated using an empirical example from a SMART study to develop an adaptive intervention for engaging alcohol- and cocaine-dependent patients in treatment. Monte Carlo simulations are provided to demonstrate the good performance of the proposed technique.     

Religious belief and intelligence: Worldwide evidence

Is there a positive impact of intelligence on religious disbelief after we account for the fact that both average intelligence and religious disbelief tend to be higher in more developed countries? We carry out four beta regression analyses and conclude that the answer is yes. We also compute impact curves that show how the effect of intelligence on atheism changes with average intelligence quotients. The impact is stronger at lower intelligence levels, peaks somewhere between 100 and 110, and then weakens. Bootstrap standard errors for our point estimates and bootstrap confidence intervals are also computed.     

Towards a Relational Affective Theory of personality disorder

This paper introduces a Relational Affective Formulation of severe narcissistic and borderline disorders. The formulation is grounded in psychoanalytic and neuroscientific theory, clinical observation and therapeutic work with hospitalised patients. It provides a conceptual framework for psychodynamic psychiatrists, therapists and psychosocial practitioners working in teams. Paying particular attention to the central place of affect, projective and introjective processes, claustro-agoraphobic phenomena, regression and the place of both deficits and dynamic defences in the failure of symbolisation, the case is made that this framework is suited to therapeutic work with patients who are highly suicidal and complex. The application of this formulation to service design and treatment pathways is described along with a summary of the body of psychoanalytic thinking which contributed to its development. The formulation is the cornerstone of a practice guide currently under development.     

The impact of the health professional on the individual's experience of cancer: A psychodynamic perspective

Abstract

This paper examines how interactions with health professionals may come to influence the patient's experience of cancer. It considers the idea that the experience of cancer returns an individual to a state of dependence and lack of integration similar to that of the young infant. The subsequent interactions with health professionals can then be considered in light of its ability to hold the patient's un-integrated self and facilitate its re-integration.     

Change management: Time for a change!

We discuss some core issues in the field of change management. We use these topics to identify some mindsets that dominate the practice of change management, and argue that these should be replaced by some alternatives. The alternatives are drawn largely from operations management and sociotechnical thinking. We characterize existing approaches as partial, and speculate that this may be one of the reasons why so many change initiatives are ineffective at meeting their goals. We identify some of the reasons why existing mindsets are sustained. We also point to some ways forward, focusing on changes in the mindsets and language we use. We speculate that these would improve the effectiveness of change initiatives.     

The use of artificial neural networks and multiple linear regression in modelling work–health relationships: Translating theory into analytical practice

Although psychological theory acknowledges the existence of complex systems and the importance of nonlinear effects, linear statistical models have been traditionally used to examine relationships between environmental stimuli and outcomes. The way we analyse these relationships does not seem to reflect the way we conceptualize them. The present study investigated the application of connectionism (artificial neural networks) to modelling the relationships between work characteristics and employee health by comparing it with a more conventional statistical linear approach (multiple linear regression) on a sample of 1003 individuals in employment. Comparisons of performance metrics indicated differences in model fit, with neural networks to some extent outperforming the linear regression models, such that R ² for worn-out and job satisfaction were significantly higher in the neural networks. Most importantly, comparisons revealed that the predictors in the two approaches differed in their relative importance for predicting outcomes. The improvement is attributed to the ability of the neural networks to model complex nonlinear relationships. Being unconstrained by assumptions of linearity, they can provide a better approximation of such psychosocial phenomena. Nonlinear approaches are often better fitted for purpose, as they conform to the need for correspondence between theory, method, and data.     

工作记忆中央执行成分对估算表现的影响

工作记忆中央执行成分在计算加工的诸多过程中发挥重要影响。以82名大学生为被试,采用双任务实验范式考察工作记忆中央执行成分对估算表现的影响。结果发现：1）估算过程需要中央执行成分的参与,增加中央执行成分负荷会导致估算准确率下降;2）无论是否增加中央执行负荷,问题大小效应在估算中均不明显;3）乘法个位数大小顺序会影响估算值的准确性,在有中央执行负荷时数字顺序效应明显。     

Reflections on coma: Man deprived of his consciousness

In this paper the authors reflect on the phenomena produced by the surprising communication between the unconscious of a therapist and that of a comatose patient. In a particularly disturbing context, when the patient’s sternum is open and exposed, the therapist communicates empathically with the comatose person, identifying the patient’s inexpressible experience and generating signs of a response from him in the form of the blinking of his eyelids. The absence of any reaction to pain, a pathognomonic sign of the comatose condition, could be related to the splitting‐off of the trauma, as if the situation were frozen, through a denial of the sensory and neurological perception of pain – a kind of self‐anaesthesia as a defence against the catastrophic anxieties raised by the threat of the return of the primary trauma. Starting from this encounter a relationship is formed whose guiding thread emerges in the shared illusion of a regression that makes it possible. It involves a process of returning to the past and a re‐actualization of the past that includes the question of its change through representation.