Alternatives to the fixed-set model: A review of appraisal models of emotion

Over several decades, appraisal theory has emerged as a prominent theoretical framework explaining the elicitation and differentiation of emotions, and has stimulated a great deal of theorising and empirical research. Despite the large amount of research in this area, there are many aspects of appraisal theory and research that remain unclear or problematic. In this review, we identify a common assumption of many appraisal theories—the fixed appraisal set—and argue that this assumption, combined with a lack of explicit theorising about the predicted relationship between appraisals and emotions, leads to a lack of clarity in both appraisal models and the empirical testing of those models. We recommend that appraisal theorists move in a direction already taken by a small number of theorists, and adopt the starting assumption of a variable appraisal set. We further suggest that theories of concepts and categorisation may inform theorising about appraisal–emotion relationships.     

The Generalized Quantum Episodic Memory Model

Recent evidence suggests that experienced events are often mapped to too many episodic states, including those that are logically or experimentally incompatible with one another. For example, episodic over‐distribution patterns show that the probability of accepting an item under different mutually exclusive conditions violates the disjunction rule. A related example, called subadditivity, occurs when the probability of accepting an item under mutually exclusive and exhaustive instruction conditions sums to a number >1. Both the over‐distribution effect and subadditivity have been widely observed in item and source‐memory paradigms. These phenomena are difficult to explain using standard memory frameworks, such as signal‐detection theory. A dual‐trace model called the over‐distribution (OD) model (Brainerd & Reyna, 2008) can explain the episodic over‐distribution effect, but not subadditivity. Our goal is to develop a model that can explain both effects. In this paper, we propose the Generalized Quantum Episodic Memory (GQEM) model, which extends the Quantum Episodic Memory (QEM) model developed by Brainerd, Wang, and Reyna (2013). We test GQEM by comparing it to the OD model using data from a novel item‐memory experiment and a previously published source‐memory experiment (Kellen, Singmann, & Klauer, 2014) examining the over‐distribution effect. Using the best‐fit parameters from the over‐distribution experiments, we conclude by showing that the GQEM model can also account for subadditivity. Overall these results add to a growing body of evidence suggesting that quantum probability theory is a valuable tool in modeling recognition memory.     

A Social Learning Perspective on Childhood Trauma and Same‐Sex Intimate Partner Violence

The family violence and childhood trauma literature has suggested that early adverse experiences create risk factors for intimate partner violence (IPV). Thus, this study used a sample of lesbian, gay, and bisexual (LGB) college students (N = 266) to explore differences among childhood trauma, same‐sex IPV, and IPV acceptance. The authors used survey methodology and multivariate analysis of variance. Results indicated that LGB individuals reporting childhood trauma also reported higher rates of IPV, suggesting implications for research and practice.     

Relational‐Cultural Theory and Reality Therapy: A Culturally Responsive Integrative Framework

The authors propose an integration of relational‐cultural theory and reality therapy. The authors contend that the traditional assumptions of reality therapy are consistent with the relational aspects of relational‐cultural theory and together provide a culturally responsive approach for diverse clients. The authors also include an overview of the 2 theories as well as highlight the convergences and divergences. In addition, the authors present a case illustration depicting the integration method in practice.     

THE PROBLEM OF “GOD” IN PSYCHOLOGY OF RELIGION: LONERGAN'S “COMMON SENSE” (RELIGION) VERSUS “THEORY” (THEOLOGY)

The emphasis on God in American psychology of religion generates the problem of explaining divine‐versus‐natural causality in “spiritual experiences.” Especially “theistic psychology” champions divine involvement. However, its argument exposes a methodological error: to pit popular religious opinions against technical scientific conclusions. Countering such homogenizing “postmodern agnosticism,” Bernard Lonergan explained these two as different modes of thinking: “common sense” and “theory”—which resolves the problem: When theoretical science is matched with theoretical theology, “the God‐hypothesis” explains the existence of things whereas science explains their natures; and, barring miracles, God is irrelevant to natural science. A review of the field shows that the problem is pervasive; attention to “miracles”—popularly so‐named versus technically—focuses the claims of divine‐versus‐natural causality; and specifications of the meaning of spiritual, spirituality, science, worldview, and meaning itself (suffering that same ambiguity: personal import versus cognitive content) offer further clarity. The problem is not naturalism versus theism, but commonsensical versus theoretical thinking. This solution demands “hard” social science.     

Implications of an initial empirical victory for the truth of the theory and additional empirical victories

Psychologists take two propositions for granted. Specifically, empirical verification of predictions derived from a theory (a) support that the theory is more likely to be true and (b) support that additional predictions derived from the theory have an increased probability of being sustained if subjected to empirical testing. In contrast, I argue that both propositions depend strongly on whether auxiliary assumptions are taken into account. When auxiliary assumptions are not taken into account, the first proposition is valid but the second is not. When auxiliary assumptions are taken into account, the first proposition is not valid, and the second proposition encounters additional problems. I use Venn diagrams and Bayesian principles to demonstrate these conclusions.     

Action: a bridge between vocational and mental health counselling*

A theory of goal-directed action is proposed as a conceptual link between vocational and mental health counselling. Originally emerging from the vocational counselling field, contextual action theory is presented as a critical conceptual link not only between mental health and occupational life but also between counselling practices in these domains. This specific application of goal-directed action to vocational and mental health counselling is addressed by describing counselling as goal-directed action, the five tasks of counselling it invites, and tools for supporting client goals, such as the self-confrontation interview.     

Categories of Large Numbers in Line Estimation

How do people stretch their understanding of magnitude from the experiential range to the very large quantities and ranges important in science, geopolitics, and mathematics? This paper empirically evaluates how and whether people make use of numerical categories when estimating relative magnitudes of numbers across many orders of magnitude. We hypothesize that people use scale words—thousand, million, billion—to carve the large number line into categories, stretching linear responses across items within each category. If so, discontinuities in position and response time are expected near the boundaries between categories. In contrast to previous work (Landy, Silbert, & Goldin, 2013) that suggested only that a minority of college undergraduates employed categorical boundaries, we find that discontinuities near category boundaries occur in most or all participants, but that accurate and inaccurate participants respond in opposite ways to category boundaries. Accurate participants highlight contrasts within a category, whereas inaccurate participants adjust their responses toward category centers.     

How Well Do We Know Our Inner Daredevil? Probing the Relationship Between Self‐Report and Behavioral Measures of Risk Taking

To measure a person's risk‐taking tendency, research has relied interchangeably on self‐report scales (e.g., “Indicate your likelihood of engaging in the risky behavior”) and more direct measures, such as behavioral tasks (e.g., “Do you accept or reject the risky option?”). It is currently unclear, however, how the two approaches map upon each other. We examined the relationship between self‐report likelihood ratings for risky choice in a monetary gamble task and actual choice, and tested how the relationship is affected by task ambiguity (i.e., when part of the information about risks and benefits is missing) and age. Five hundred participants (aged 19–85 years) were presented with 27 gambles, either in an unambiguous or an ambiguous condition. In a likelihood rating task, participants rated for each gamble the likelihood that they would accept it. In a separate choice task, they were asked to either accept or reject each gamble. Analyses using a signal‐detection approach showed that people's likelihood ratings discriminated between accept and reject cases in their choices rather well. However, task ambiguity weakened the association between likelihood ratings and choice. Further, older adults' likelihood ratings anticipated their choices more poorly than younger adults'. We discuss implications of these findings for existing approaches to the study of risk‐taking propensity, which have often relied on self‐reported risk tendency for ambiguous activities. Copyright © 2016 John Wiley & Sons, Ltd.