Why Improvement Can Trump Consistent Strong Performance: The Role of Effort Perceptions

How do evaluators form comparative judgments of improved versus consistently strong performance records with equivalent recent performance? We propose that evaluators judge those with improved records to be more deserving of future opportunities (e.g., a promotion) and that this can be explained – at least in part – by perceptions of effort investments. Specifically, evaluators rely on improvement to judge effort and hence devalue consistent strong performance. Five studies supported these propositions. Evaluators perceived greater effort investment and trait effort in individuals with improved profiles than those with consistent profiles and consequently thought that those with improved profiles were more deserving of future opportunities. We discuss implications of these results across various decision contexts. Copyright © 2017 John Wiley & Sons, Ltd.     

Evidence for Opportunity Cost Neglect in the Poor

People often neglect opportunity costs: They do not fully take into account forgone alternatives outside of a particular choice set. Several scholars have suggested that poor people should be more likely to spontaneously consider opportunity costs, because budget constraints should lead to an increased focus on trade‐offs. We did not find support for this hypothesis in five high‐powered experiments (total N = 2325). The experiments used different products (both material and experiential) with both high and low prices (from $8.50 to $249.99) and different methods of reminding participants of opportunity costs. High‐income and low‐income participants showed an equally strong decrease in willingness to buy when reminded of opportunity costs, implying that both the rich and the poor neglect opportunity costs. © 2017 The Authors Journal of Behavioral Decision Making Published by John Wiley & Sons Ltd.     

The Role of Anticipated Regret in Advice Taking

Across five studies, we demonstrate that anticipated future regret influences receptiveness to advice. While making a revision to one's own judgment based on advice, people can anticipate two kinds of future regret: (a) the regret of following non‐beneficial advice and (b) the regret of ignoring beneficial advice. In studies 1a (scenario task) and 1b (judgment task), we find that anticipated regret from erring after following advice is greater than anticipated regret from erring after ignoring advice. Furthermore, receptiveness decreases as the difference between anticipated regret from following and from ignoring advice increases. In study 2, we demonstrate that perceived justifiability of one's own initial decision is greater than that of advice. This difference in perceived justifiability influences anticipated regret and that, in turn, influences receptiveness. In study 3, we investigate the effect of advisor's expertise on perceived justifiability, anticipated regret, and receptiveness. In study 4, we propose and test an intervention to improve receptiveness based on self‐generation of advice justifications. Participants who were asked to self‐generate justifications for the advice were more receptive to it. This effect was mediated by perceived justifiability and anticipated regret. These findings shed further light on what prevents people from being receptive to advice and how this can be improved. Copyright © 2017 John Wiley & Sons, Ltd.     

Are Decisions Made by Group Representatives More Risk Averse? The Effect of Sense of Responsibility

We tested the hypothesis that a sense of responsibility drives group representatives' decisions to be more risk averse compared with decisions made by individuals. The hypothesis was supported when the monetary considerations (i.e., payoff inequality and the magnitude effect) were controlled for in the potential gain domain as well as in the potential loss domain. Evidence showed that this is because the group representatives were concerned about how they would view themselves (e.g., guilt and self‐blame) and also how they would be viewed by others (i.e., to avoid being blamed and looked down upon by others). This study provided new insights into understanding group representatives' decision making under risk. Copyright © 2017 John Wiley & Sons, Ltd.     

It is written all over your face: Socially rejected people display microexpressions that are detectable after training in the Micro Expression Training Tool (METT)

Social rejection is a powerful negative emotional experience, yet rejected people often appear stoic and unmoved. That is, their macroexpressions of emotion are not accurate reflections of their emotional states. Yet, there is reason to believe that rejected people exhibit involuntary microexpressions of negative emotion. We contrasted people's macroexpressions of emotion with their microexpressions subsequent to an acceptance or rejection experience. Observers coded microexpressions after being trained with the Micro Expression Training Tool. Rejected participants expressed more sad and angry microexpressions than did accepted participants. This research demonstrates that socially rejected people display negative microexpressions that are detectable by observers trained in the Micro Expression Training Tool.     

Letting Go: Conceptualizing Intervention De‐implementation in Public Health and Social Service Settings

The discontinuation of interventions that should be stopped, or de‐implementation, has emerged as a novel line of inquiry within dissemination and implementation science. As this area grows in human services research, like public health and social work, theory is needed to help guide scientific endeavors. Given the infancy of de‐implementation, this conceptual narrative provides a definition and criteria for determining if an intervention should be de‐implemented. We identify three criteria for identifying interventions appropriate for de‐implementation: (a) interventions that are not effective or harmful, (b) interventions that are not the most effective or efficient to provide, and (c) interventions that are no longer necessary. Detailed, well‐documented examples illustrate each of the criteria. We describe de‐implementation frameworks, but also demonstrate how other existing implementation frameworks might be applied to de‐implementation research as a supplement. Finally, we conclude with a discussion of de‐implementation in the context of other stages of implementation, like sustainability and adoption; next steps for de‐implementation research, especially identifying interventions appropriate for de‐implementation in a systematic manner; and highlight special ethical considerations to advance the field of de‐implementation research.     

Discounting model selection with area‐based measures: A case for numerical integration

A novel method for analyzing delay discounting data is proposed. This newer metric, a model‐based Area Under Curve (AUC) combining approximate Bayesian model selection and numerical integration, was compared to the point‐based AUC methods developed by Myerson, Green, and Warusawitharana (2001) and extended by Borges, Kuang, Milhorn, and Yi (2016). Using data from computer simulation and a published study, comparisons of these methods indicated that a model‐based form of AUC offered a more consistent and statistically robust measurement of area than provided by using point‐based methods alone. Beyond providing a form of AUC directly from a discounting model, numerical integration methods permitted a general calculation in cases when the Effective Delay 50 (ED50) measure could not be calculated. This allowed discounting model selection to proceed in conditions where data are traditionally more challenging to model and measure, a situation where point‐based AUC methods are often enlisted. Results from simulation and existing data indicated that numerical integration methods extended both the area‐based interpretation of delay discounting as well as the discounting model selection approach. Limitations of point‐based AUC as a first‐line analysis of discounting and additional extensions of discounting model selection were also discussed.     

Integrating Covariates into Social Relations Models: A Plausible Values Approach for Handling Measurement Error in Perceiver and Target Effects

The Social Relations Model (SRM) is a conceptual and analytical approach to examining dyadic behaviors and interpersonal perceptions within groups. In an SRM, the perceiver effect describes a person's tendency to perceive other group members in a certain way, whereas the target effect measures the tendency to be perceived by others in certain ways. In SRM research, it is often of interest to relate these individual SRM effects to covariates. However, the estimated individual SRM effects might not provide a very reliable measure of the true, unobserved SRM effects, resulting in distorted estimates of associations with other variables. This article introduces a plausible values approach that allows users to correct for measurement error when assessing the association of individual SRM effects with other individual difference variables. In the plausible values approach, the latent, true individual SRM effects are treated as missing values and are imputed from an imputation model by applying Bayesian estimation techniques. In a simulation study, the statistical properties of the plausible values approach are compared with two approaches that have been used in previous research. A data example from educational psychology is presented to illustrate how the plausible values approach can be implemented with the software WinBUGS.     

The Role of Character Strengths and Importance of Family on Mexican American College Students' Career Decision Self‐Efficacy

This study examined how character strengths and the importance of family influenced Mexican American college students' (N = 129) career decision self‐efficacy. Findings from a multiple regression analysis indicated that psychological grit and curiosity were significant predictors of career decision self‐efficacy. The authors discuss the importance of these findings and provide recommendations for future research.     

Object-Tool-Actor Interaction: Object Information Drives Intended Action

Tool use is typically explored via actor-tool interactions. However, the target-object (that which is being acted on) may influence perceived action possibilities and thereby guide action. Three different tool-target-object pairings were tested (Experiment 1). The hammering action demonstrated the greatest sensitivity and therefore subsequently used to further investigate target-object pairings. The hammer was removed as an option and instructions were provided using pictorial (Experiment 2), written (Experiment 3), and both pictorial and written formats (Experiment 4). The designed tool is chosen when available (Experiment 1) and when removed as a choice (i.e., the hammer), participants perform the same action associated with the designed tool (i.e., hammering) regardless of instruction method (Experiments 2, 3, and 4).