Using Indirect Measurement Tasks to Assess the Self‐concept of Personality: A Systematic Review and Meta‐analyses

This systematic review presents the current state of research investigating the implicit self‐concept of personality. First, we present results on meta‐analyses estimating internal consistency, reliability coefficients, the implicit–explicit consistency and the single association predictive effect of implicit self‐concept of personality measures. To do this, studies were aggregated over personality domains. Second, for each of the Five Factor personality domains, different aspects of construct validity and predictive validity are reviewed in a narrative way. Results show that implicit self‐concept of personality measures are reliable, and there is evidence for the construct and predictive validity of these implicit measures, especially in the extraversion and agreeableness domains of personality. However, it must be kept in mind that clear evidence for publication bias was found for studies examining the single association predictive pattern. Finally, this systematic review identifies some achievable improvements that are needed in future research. Large cross‐lab efforts are important in this respect. Moreover, the implicit self‐concept of personality field must move from an ‘ad hoc’ to a ‘validation’ approach in developing new indirect measurement tasks. By adopting these research objectives, the information processing account of personality will increase its potential to become integrated into mainstream personality theory and research. Copyright © 2017 European Association of Personality Psychology     

Information needs in groundwater protection policy: Agenda-setting for knowledge development

Water policymaking strongly depends on expert knowledge, and yet there is a gap between policy makers and research professionals. This article addresses this issue by presenting a conceptual framework and method for identification of information needs in a particular policymaking context. The framework deduces information needs not only from pertaining laws and regulations, but also from strategic stakeholder behavior that can be anticipated in this context. The outcome is then matched with empirically observed information needs and available knowledge. Framework and method have been applied to the Dutch groundwater protection policy situation, establishing their effectiveness in exploring strategies to stimulate knowledge development to match stakeholder information needs. specializing in water management. He recently graduated on the main subject of policy analysis (MSc in 2001). He did his thesis research project at the Netherlands Institute of Geological Science TNO—National Geological Survey. Educated in the field of computer science at Leiden University (MSc in 1985), his research interests have moved from decision support systems (PhD from Delft University of Technology in 1989) to methods and tools for policy analysis in general. He currently focuses on the development of Dynamic Actor Network Analysis (DANA) and a Modeling Environment for Design Impact Assessment (MEDIA).     

Actual neurosis as the underlying psychic structure of panic disorder, somatization, and somatoform disorder: an integration of Freudian and attachment perspectives

Starting from a contemporary critique of the DSM-IV, this paper argues that the diagnostic categories of panic disorder somatization, and undifferentiated somatoform disorders can be understood as belonging to a common type of psychopathology--i.e., the Freudian actual neuroses. In addition to their strong clinical similarity, these disorders share an etiological similarity; and the authors propose a combination of Freud's focus on this type of patient's inability to represent an endogenous drive arousal with the post-Freudian focus on separation anxiety. An etiological hypothesis is put forward based on contemporary psychoanalytic attachment theory, highlighting mentalization. Concrete implications for a psychoanalytically based treatment are proposed.     

Open answer set programming for the semantic web

We extend answer set programming (ASP) with, possibly infinite, open domains. Since this leads to undecidable reasoning, we restrict the syntax of programs, while carefully guarding knowledge representation mechanisms such as negation as failure and inequalities. Reasoning with the resulting extended forest logic programs (EFoLPs) can be reduced to finite answer set programming, for which reasoners are available.We argue that extended forest logic programming is a useful tool for uniformly representing and reasoning with both ontological and rule-based knowledge, as they can capture a large fragment of the OWL DL ontology language equipped with DL-safe rules. Furthermore, EFoLPs enable nonmonotonic reasoning, a desirable feature in locally closed subareas of the Semantic Web.     

The factorial structure of the Dutch translation of the inventory of interpersonal problems: a test of the long and short versions

In this article, the authors study the factorial structure of 2 versions (64 items and 32 items) of the Dutch translation of the Inventory of Interpersonal Problems (IIP; L. M. Horowitz, L. E. Alden, J. S. Wiggins, & A. L. Pincus, 2000) in both a clinical sample (n = 382) and a student sample (n = 287). First, the authors test whether both inventories are constituted by correlated uni-dimensional subscales, and they conclude that this is true only for the short version. Second, the authors study whether the correlations between the subscales follow a circumplex pattern. This proves to be true for both versions. Coefficients alpha and correlations between the IIP-64 and IIP-32 subscales are discussed.     

The Future of the Christian Past: Marcel Gauchet and Charles Taylor on the Essence of Religion and its Evolution

This article explores the differences between Marcel Gauchet and Charles Taylor with respect to their theories of secularization. It starts by looking at their resemblances; it continues by distinguishing a two‐fold difference in their approach. The variation within their similar methodologies is examined, and then the consequences of these divergent definitions of religion are investigated. We focus on four themes: the role of the Axial religions, the significance of Incarnation and Reformation, the significance of Christianity as the ‘religion of the departure from religion’, and the possibility of religious ‘conversion’. Taylor's and Gauchet's views on the future of religion diverge as a function of their different interpretations of ‘fulfilment’ and ‘hunger for meaning’.     

The Effect of Intuitive Advice Justification on Advice Taking

How do you respond when receiving advice from somebody with the argumentation “my gut tells me so” or “this is what my intuition says”? Most likely, you would find this justification insufficient and disregard the advice. Are there also situations where people do appreciate such intuitive advice and change their opinion accordingly? A growing number of authors write about the power of intuition in solving problems, showing that intuitively made decisions can be of higher quality than decisions based on analytical reasoning. We want to know if decision makers, when receiving advice based on an intuitive cognitive process, also recognize the value of such advice. Is advice justified by intuition necessarily followed to a lesser extent than an advice justified by analysis? Furthermore, what are the important factors influencing the effect of intuitive justification on advice taking? Participants across three studies show that utilization of intuitive advice varies depending on advisor seniority and type of task for which the advice is given. Summarizing, the results suggest that decision makers a priori doubt the value of intuitive advice and only assess it as accurate if other cues in the advice setting corroborate this. Intuitively justified advice is utilized more if it comes from a senior advisor. In decision tasks with experiential products, intuitively justified advice can even have more impact than analytically justified advice. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessing moderated mediation in linear models requires fewer confounding assumptions than assessing mediation

It is well known from the mediation analysis literature that the identification of direct and indirect effects relies on strong no unmeasured confounding assumptions of no unmeasured confounding. Even in randomized studies the mediator may still be correlated with unobserved prognostic variables that affect the outcome, in which case the mediator's role in the causal process may not be inferred without bias. In the behavioural and social science literature very little attention has been given so far to the causal assumptions required for moderated mediation analysis. In this paper we focus on the index for moderated mediation, which measures by how much the mediated effect is larger or smaller for varying levels of the moderator. We show that in linear models this index can be estimated without bias in the presence of unmeasured common causes of the moderator, mediator and outcome under certain conditions. Importantly, one can thus use the test for moderated mediation to support evidence for mediation under less stringent confounding conditions. We illustrate our findings with data from a randomized experiment assessing the impact of being primed with social deception upon observer responses to others’ pain, and from an observational study of individuals who ended a romantic relationship assessing the effect of attachment anxiety during the relationship on mental distress 2 years after the break‐up.     

Estimation of Controlled Direct Effects in Longitudinal Mediation Analyses with Latent Variables in Randomized Studies

Abstract

In a randomized study with longitudinal data on a mediator and outcome, estimating the direct effect of treatment on the outcome at a particular time requires adjusting for confounding of the association between the outcome and all preceding instances of the mediator. When the confounders are themselves affected by treatment, standard regression adjustment is prone to severe bias. In contrast, G-estimation requires less stringent assumptions than path analysis using SEM to unbiasedly estimate the direct effect even in linear settings. In this article, we propose a G-estimation method to estimate the controlled direct effect of treatment on the outcome, by adapting existing G-estimation methods for time-varying treatments without mediators. The proposed method can accommodate continuous and noncontinuous mediators, and requires no models for the confounders. Unbiased estimation only requires correctly specifying a mean model for either the mediator or the outcome. The method is further extended to settings where the mediator or outcome, or both, are latent, and generalizes existing methods for single measurement occasions of the mediator and outcome to longitudinal data on the mediator and outcome. The methods are utilized to assess the effects of an intervention on physical activity that is possibly mediated by motivation to exercise in a randomized study.