Preparing Nurse Educator Students for the New National Council of State Boards of Nursing NCLEX and AACN Essentials

BACKGROUND

Graduate nursing education students are required to complete essential core content (such as education theory, accreditation, evidence-based teaching strategies, and evaluation methods) to prepare them to transition into independent practice. The 2021-2022 academic year required a monumental change in the existing curriculum to incorporate the 2021 American Association of Colleges of Nursing Essentials and the Next Gen National Council Licensure Examination (NCLEX) content.

METHOD

An innovative, prioritized, learner-centered, backward design was used to update the existing curriculum to add the new core content to the nursing education student curriculum.

RESULTS

The end of program comprehensive exams revealed that the students were able to successfully develop a test blueprint, utilizing case studies with Next Gen NCLEX question types designed to measure clinical judgment, and map to the 2021 AACN Essentials.

CONCLUSION

The timely implementation of the curriculum revisions resulted in the achievement of desired student learning outcomes. [J Nurs Educ. 2024;63(3):192-196.].

Does variety in hedonic spending improve happiness? Testing alternative causal mechanisms between hedonic variety and subjective well-being

Previous research has found only a small, inconsistent association between hedonic consumption and subjective well-being, often attributed to individuals adapting to the happiness gains from their purchases. Given that diverse experiences can reduce or avert hedonic adaptation, we hypothesized that variety in hedonic spending would be associated with greater well-being. This hypothesis was tested in four studies (total N = 2,920), using both self-reported and objective bank-reported spending data. In our correlational analyses, hedonic spending variety was uniquely associated with well-being, even after controlling for total hedonic spending and other financial variables. Our investigation also explored the directional relationship between hedonic spending variety and well-being, yielding mixed results for both causal pathways in two time-lagged panel studies. Additionally, in two parallel experiments, participants reported that varied hedonic spending contributed more to happiness than uniform hedonic spending. These findings have implications for basic well-being science by testing how varied consumption behaviors and well-being are interrelated.

Reward Sensitivity Predicts the Response to Cognitive Behavioral Therapy for Children with Autism and Anxiety

OBJECTIVE

Cognitive-behavioral therapy (CBT) is an effective treatment for anxiety in youth with autism spectrum disorder (ASD). However, research has yet to examine what cognitive characteristics may influence treatment response. The current study investigated decision-making ability and social cognition as potential (a) predictors of differential treatment response to two versions of CBT and (b) moderators of the effect of treatment condition.

METHOD

The study included 148 children (mean age = 9.8 years) with interfering anxiety and a diagnosis of ASD who were enrolled in a randomized clinical trial comparing two versions of CBT for anxiety (standard and adapted for ASD). Participants completed pretreatment measures of decision-making ability (adapted Iowa Gambling Task) and social cognition (Strange Stories) and analyses tested whether task performance predicted treatment response across and between (moderation) treatment conditions.

RESULTS

Our findings indicate that decision-making ability moderated treatment outcomes in youth with ASD and anxiety, with a better decision-making performance being associated with higher post-treatment anxiety scores for those who received standard, not adapted, CBT.

CONCLUSIONS

Children with ASD and anxiety who are more sensitive to reward contingencies and reinforcement may benefit more from adapted CBT approaches that work more explicitly with reward.

From Integrated Care to Integrating Care: A Conceptual Framework of Behavioural Processes Underlying Effective Collaboration in Care

Introduction

At all levels, effective collaboration between actors with different backgrounds lies at the heart of integrated care. Much attention has been given to the structural features underlying integrated care, but even under structurally similar circumstances, the effectiveness of collaboration varies largely.

Theory and methods

Social and organizational psychological research shows that the extent to which collaboration is effective depends on actors' behaviours. We leverage insights from these two research fields and build a conceptual framework that helps untangle the behavioural processes underlying effective collaboration.

Results

We delineate that effective collaboration can be realized when actors (1) speak up about their interests, values, and perspectives (voice behaviour), (2) listen to the information that is shared by others, and (3) thoroughly process this information. We describe these behaviours and explain the motivations and conditions driving these. In doing so, we offer a conceptual framework that can be used to explain what makes actors collaborate effectively and how collaboration can be enhanced.

Discussion and conclusion

Fostering effective collaboration takes time and adequate conditions, fitting the particular context. As this context continuously changes, the processes and conditions require continuous attention. Integrated care, therefore, actually requires a carefully designed process of integrating care.

Adult Avoidant Attachment, Attention Bias, and Emotional Regulation Patterns: An Eye-Tracking Study

Proximity-seeking in distress situations is one of attachment theory's primary strategies; insecure individuals often also develop secondary strategies. The mechanisms implied in attachment deactivation constitute a key issue in the current debate related to their role in support-seeking. The main aim of this study is to investigate the attachment deactivation strategy and the processes of proximity/support-seeking under distress conditions by analyzing the attentional processes (i.e., an essential emotion-regulation strategy), using eye-tracking techniques. Seventy-two participants (45 female; Mage 23.9 ± 3.97) responded to the ECR-R questionnaire in order to identify their attachment style. They participated in an experimental situation in which they had to choose between pictures of care or pictures of food, following the presentation of threatening or neutral prime conditions (via the pictures' stimuli). Results showed that a care-consistency response pattern was the most frequent pattern of response, particularly under a threatening condition; on the contrary, only avoidant individuals showed a lower care-consistency response pattern by choosing food pictures. The overall findings demonstrate that avoidant individuals used the deactivation strategy to process comfort-related attachment pictures, suggesting that they considered these stimuli to be threatening. The implications for attachment theory and particularly for avoidant strategies are discussed.

The repulsion effect in preferential choice and its relation to perceptual choice

People rely on the choice context to guide their decisions, violating fundamental principles of rational choice theory and exhibiting phenomena called context effects. Recent research has uncovered that dominance relationships can both increase or decrease the choice share of the dominating option, marking the two ends of an attraction-repulsion continuum. However, empirical links between the two opposing effects are scarce and theoretical accounts are missing altogether. The present study (N = 55) used eye tracking alongside a within-subject design that contrasts a perceptual task and a preferential-choice analog in order to bridge this gap and uncover the underlying information-search processes. Although individuals differed in their perceptual and preferential choices, they generally engaged in alternative-wise comparisons and a repulsion effect was present in both conditions that became weaker the more predominant the attribute-wise comparisons were. Altogether, our study corroborates the notion that repulsion effects are a robust and general phenomenon that theoretical accounts need to take seriously.

Assessing Driving Risk at the Second Phase of Overtaking on Two-Lane Highways for Young Novice Drivers Based on Driving Simulation

Overtaking on two-lane highways is a complex and multi-phase maneuver associated with high collision risk, especially for young novice drivers. Most of the relevant studies, however, focused mainly on the first phase, i.e., the lane-changing phase, such as willingness to overtake, while the second phase, i.e., the back-to-lane phase, has not been investigated systematically. It is a risky phase in which a driver faces the risk of collision with not only the approaching vehicle on the opposite lane but also the impeding vehicle at the original lane. In this study, by designing and conducting a driving simulator experiment, we assess the driving risk of 47 young novice drivers during their second phase of overtaking on two-lane highways. The time-to-collision (TTC) values at the two critical positions are calculated from a micro-geometric point of view, based on which a two-dimensional risk index is proposed and the fuzzy C-means clustering algorithm is applied to group all the samples and to assess their overtaking risk. Furthermore, a multi-class logistic model is developed to understand the potential factors related to the risky overtaking maneuvers at this phase. The results show that most of the young novice drivers cannot make accurate judgments during their second phase of overtaking. When turning back to the original lane, they are more likely to be aware of the opposite vehicle that is approaching them, while how to correctly avoid the collision risk with the impeding vehicle at this phase is probably a more critical issue for young novice drivers.

Cognitive and neural principles of a memory bias on preferential choices

Value-based decisions depend on different forms of memory. However, the respective roles of memory and valuation processes that give rise to these decisions are often vaguely described and have rarely been investigated jointly. In this review article, we address the problem of memory-based decision making from a neuroeconomic perspective. We first describe the neural and cognitive processes involved in decisions requiring memory processes, with a focus on episodic memory. Based on the results of a systematic research program, we then spotlight the phenomenon of the memory bias, a general preference for choice options that can be retrieved from episodic memory more successfully. Our findings indicate that failed memory recall biases neural valuation processes as indicated by altered effective connectivity between the hippocampus and ventromedial prefrontal cortex. This bias can be attributed to meta-cognitive beliefs about the relationship between subjective value and memory as well as to uncertainty aversion. After summarizing the findings, we outline potential future research endeavors to integrate the two research traditions of memory and decision making.

Establishing the laws of preferential choice behavior

Mathematical and computational decision models are powerful tools for studying choice behavior, and hundreds of distinct decision models have been proposed over the long interdisciplinary history of decision making research. The existence of so many models has led to theoretical fragmentation and redundancy, obscuring key insights into choice behavior, and preventing consensus about the essential properties of preferential choice. We provide a synthesis of formal models of risky, multiattribute, and intertemporal choice, three important domains in decision making. We identify recurring insights discovered by scholars of different generations and different disciplines across these three domains, and use these insights to classify over 150 existing models as involving various combinations of eight key mathematical and computational properties. These properties capture the main avenues of theoretical development in decision making research and can be used to understand the similarities and differences between decision models, aiding both theoretical analyses and empirical tests.

Comparisons Inform Me Who I Am: A General Comparative-Processing Model of Self-Perception

People's self-concept contributes to their sense of identity over time. Yet self-perception is motivated and serves survival and thus does not reflect stable inner states or accurate biographical accounts. Research indicates that different types of comparison standards act as reference frames in evaluating attributes that constitute the self. However, the role of comparisons in self-perception has been underestimated, arguably because of lack of a guiding framework that takes into account relevant aspects of comparison processes and their interdependence. I propose a general comparative model of self-perception that consists of a basic comparison process involving the individual's prior mental representation of the target dimension, the construal of the comparison standard, and the comparison outcome representing the posterior representation of the target dimension. The generated dimensional construal is then appraised with respect to one's motives and controllability and goes on to shape emotional, cognitive, and behavioral responses. Contextual and personal factors influence the comparison process. This model may be informative in better understanding comparison processes in people's everyday lives and their role in shaping self-perception and in designing interventions to assist people overcome undesirable consequences of comparative behavior.

From data mining to wisdom mining

The knowledge gained from data mining is highly dependent on the experience of an expert for further analysis to increase effectiveness and wise decision-making. This mined knowledge requires actionability enhancement before it can be applied to real-world problems. The literature highlights the reasons that emerged the need to incorporate human wisdom in decision-making for complex problems. To solve this problem, a domain called ‘Wisdom Mining’ is recommended, proposing a set of algorithms parallel to the algorithms proposed by the data mining. In wisdom mining, a process to extract wisdom needs to be defined with less influence from an expert. This review proposed improvements to data mining techniques and their applications in the real world and emphasised the need to seek ways to harness wisdom from data. This study covers the diverse definitions and different perspectives of wisdom within philosophy, psychology, management and computer science. This comprehensive literature review served as a foundation for constructing a wise decision framework that aided in identifying the wisdom factors like context, utility, location and time. The inclusion of these wisdom factors in existing data mining algorithms makes the transition from data mining to wisdom mining possible. This research includes the relationship between these two mining process that facilitated further elucidation of the wisdom mining process. Potential research trends in the domain are also seen as a potential endeavour to improve the analysis and use of data.

A method for estimating the time of initiating correct categorization in mouse-tracking

Mouse-tracking facilitates exploration of the mental processes underlying decision-making. As the cognitive system works to settle on a decision, response competition manifests in the motor movements of the hand, bringing the mouse relatively closer to one alternative versus the other. Many metrics provide insight into decision-making processes by indexing the shape or complexity of the mouse trajectory. Lacking, however, is a metric that estimates the point in time when a participant begins to correctly categorize a stimulus. We rectify this absence by introducing a metric we refer to as time of initiating correct categorization (TICC), which is the point in time when people began moving relatively closer to the selected target relative to the distractor. We briefly review existing approaches to measuring time in mouse-tracking before describing the TICC and demonstrating its utility in three data sets.

Theory Integration for Lifestyle Behavior Change in the Digital Age: An Adaptive Decision-Making Framework

Despite the growing popularity of digital health interventions, limitations of traditional behavior change theories and a lack of theory integration hinder theory-driven behavior change applications. In this paper, we aim to review theories relevant to lifestyle behavior change from the broader psychology literature and then integrate these theories into a new theoretical framework called adaptive decision-making to address two specific problems. First, our framework represents lifestyle behaviors at two levels-one of individual daily decisions (action level) and one of larger behavioral episodes (reflection level)-to more closely match the temporal characteristics of lifestyle behaviors and their associated digital data. Second, the framework connects decision-making theories and learning theories to explain how behaviors and cognitive constructs dynamically influence each other, making it a suitable scaffold for building computational models. We map common digital intervention techniques onto the behavioral and cognitive processes in the framework and discuss possible contributions of the framework to both theory development and digital intervention design.

From high- to one-dimensional dynamics of decision making: testing simplifications in attractor models

Computational models introduce simplifications that need to be understood and validated. For attractor models of decision making, the main simplification is the high-level representation of different sub-processes of the complex decision system in one dynamic description of the overall process dynamics. This simplification implies that the overall process dynamics of the decision system are independent from specific values handled in different sub-processes. Here, we test the validity of this simplification empirically by investigating choice perseveration in a nonverbal, value-based decision task. Specifically, we tested whether choice perseveration occurred irrespectively of the attribute dimension as suggested by a simulation of the computational model. We find evidence supporting the validity of the simplification. We conclude that the simplification might capture mechanistic aspects of decision-making processes, and that the summation of the overall process dynamics of decision systems into one single variable is a valid approach in computational modeling. Supplement materials such as empirical data, analysis scripts, and the computational model are publicly available at the Open Science Framework (osf.io/7fb5q).

Judgment and Decision Making

The science of judgment and decision making involves three interrelated forms of research: analysis of the decisions people face, description of their natural responses, and interventions meant to help them do better. After briefly introducing the field's intellectual foundations, we review recent basic research into the three core elements of decision making: judgment, or how people predict the outcomes that will follow possible choices; preference, or how people weigh those outcomes; and choice, or how people combine judgments and preferences to reach a decision. We then review research into two potential sources of behavioral heterogeneity: individual differences in decision-making competence and developmental changes across the life span. Next, we illustrate applications intended to improve individual and organizational decision making in health, public policy, intelligence analysis, and risk management. We emphasize the potential value of coupling analytical and behavioral research and having basic and applied research inform one another.

Vicarious Rewards Modulate the Drift Rate of Evidence Accumulation From the Drift Diffusion Model

Taking other people's interests into account is a fundamental ability allowing humans to maintain relationships. Yet, the mechanisms by which monetary incentives for close others influence perceptual decision-making processes remain elusive. Here, we compared perceptual decisions motivated by payoffs for oneself or a close relative. According to drift diffusion models (DDMs), perceptual decisions are made when sensory evidence accumulated over time - with a given drift rate - reaches one of the decision boundaries. We used these computational models to identify whether the drift rate of evidence accumulation or the decision boundary is affected by these two sources of motivation. Reaction times and sensitivity were modulated by three factors: the Difficulty (motion coherence of the moving dots), the Payoff associated with, and the Beneficiary of the decision. Reaction times (RTs) were faster for easy compared to difficult trials and faster for high payoffs as compared to low payoffs. More interestingly, RTs were also faster for self than for other-affecting decisions. Finally, using DDM, we found that these faster RTs were linked to a higher drift rate of the decision variable. This study offers a mechanistic understanding of how incentives for others and motion coherence influence decision-making processes.

Choice perseveration in value-based decision making: The impact of inter-trial interval and mood

In a series of decisions, people tend to show choice perseveration, that is, they repeat their choices. This choice perseveration is assumed to emerge due to residual activity from the previous decision. Here, we use a computational model with attractor dynamics to describe this process and to predict how choice perseveration can be modulated. We derive two qualitative predictions: Choice perseveration should decrease under longer (vs. shorter) inter-trial intervals and positive (vs. negative) mood. We test these predictions in a dynamic decision task where we modulate decisions across trials via sequentially manipulated reward options. Our findings replicate our previous study in showing choice perseveration in value-based decision making. Furthermore, choice perseveration decreased with increasing inter-trial interval as predicted by the model. However, we did not find clear evidence supporting mood effects on choice perseveration. We discuss how integrating decision process dynamics by the means of applying the neural attractor model can increase our understanding of the evolution of decision outcomes and therefore complement the psychophysical perspective on decision making.

VAMP (Voting Agent Model of Preferences): A computational model of individual multi-attribute choice

This paper proposes an original account of decision anomalies and a computational alternative to existing dynamic models of multi-attribute choice. To date, most models attempting to account for the "Big Three" decision anomalies (similarity, attraction, and compromise effects) are variants of evidence accumulation models, or rational Bayesian analysis. This paper provides an existence proof of a new approach in the form of a multi-agent system based on the principles of voting geometry. Assuming there are a number of neural systems (agents) within an individual's brain, the Big Three decision anomalies can arise as a natural consequence of aggregating preferences across these agents. We operationalize these principles in VAMP, (Voting Agent Model of Preferences), and compare its performance to existing computational models as well as to empirical data. This provides a fundamentally different lens for understanding decision anomalies in multi-attribute choice.

Effect of warning placement on the information processing of college students reading an OTC drug facts panel

OBJECTIVE

To compare three over-the-counter (OTC) Drug Facts panel versions for information processing optimization among college students.

PARTICIPANTS

University of Houston students (N = 210) participated in a cross-sectional survey from January to May 2010.

METHODS

A current FDA label was compared to two experimental labels developed using the theory of CHREST to test information processing by re-positioning the warning information within the Drug Facts panel. Congruency was defined as placing like information together. Information processing was evaluated using the OTC medication Label Evaluation Process Model (LEPM): label comprehension, ease-of-use, attitude toward the product, product evaluation, and purchase intention.

RESULTS

Experimental label with chunked congruent information (uses-directions-other information-warnings) was rated significantly higher than the current FDA label and had the best average scores among the LEPM information processing variables.

CONCLUSION

If replications uphold these findings, the FDA label design might be revised to improve information processing.

The contrast effect in reading general conditionals

To adjudicate between deterministic and probabilistic accounts of the meaning of conditionals, we examined the influence of context on the reading of general conditionals. Context was varied with the contrast context, where participants judged uncertain conditionals after certain conditionals, and the control context, where participants judged only uncertain conditionals. Experiment 1 had participants to judge whether a set of truth table cases was possible for the conditional. Experiment 2 had participants to judge whether the conditional was true for a set of truth table cases. The findings are as follows. Possibility and truth judgments showed a similar response pattern. The reading of general conditionals varied with conditional contexts. The predominant reading was deterministic in the contrast context but was probabilistic in the control context. Conditional contexts yielded a significant contrast effect. Meanwhile, conditional probability P( q| p) made a smaller difference to the acceptance rate in the contrast context than in the control context. The overall pattern is beyond both the deterministic and probabilistic accounts. Alternatively, we propose a dynamic-threshold account for the relative reading of general conditionals.

Noisy preferences in risky choice: A cautionary note

We examine the effects of multiple sources of noise in risky decision making. Noise in the parameters that characterize an individual's preferences can combine with noise in the response process to distort observed choice proportions. Thus, underlying preferences that conform to expected value maximization can appear to show systematic risk aversion or risk seeking. Similarly, core preferences that are consistent with expected utility theory, when perturbed by such noise, can appear to display nonlinear probability weighting. For this reason, modal choices cannot be used simplistically to infer underlying preferences. Quantitative model fits that do not allow for both sorts of noise can lead to wrong conclusions. (PsycINFO Database Record

Why computer models help to understand developmental processes

It is argued that simulating psychological processes by means of computer models is a valuable technique to increase our understanding of adolescent developmental processes. Modelling offers possibilities to test hypotheses that cannot be reached by designing empirical studies only and it allows us to investigate adolescent development as the complex and non-linear process that it is.

Memory retrieval processes help explain the incumbency advantage

Voters prefer political candidates who are currently in office (incumbents) over new candidates (challengers). Using the premise of query theory (Johnson, Häubl & Keinan, 2007), we clarify the underlying cognitive mechanisms by asking whether memory retrieval sequences affect political decision making. Consistent with predictions, Experiment 1 (N= 256) replicated the incumbency advantage and showed that participants tended to first query information about the incumbent. Experiment 2 (N= 427) showed that experimentally manipulating participants’ query order altered the strength of the incumbency advantage. Experiment 3 (N= 713) replicated Experiment 1 and, in additional experimental conditions, showed that the effects of incumbency can be overridden by more valid cues, like the candidates’ ideology. Participants queried information about ideologically similar candidates earlier and also preferred these ideologically similar candidates. This is initial evidence for a cognitive, memory-retrieval process underling the incumbency advantage and political decision making.

The Argumentative Theory: Predictions and Empirical Evidence

The argumentative theory of reasoning suggests that the main function of reasoning is to exchange arguments with others. This theory explains key properties of reasoning. When reasoners produce arguments, they are biased and lazy, as can be expected if reasoning is a mechanism that aims at convincing others in interactive contexts. By contrast, reasoners are more objective and demanding when they evaluate arguments provided by others. This fundamental asymmetry between production and evaluation explains the effects of reasoning in different contexts: the more debate and conflict between opinions there is, the more argument evaluation prevails over argument production, resulting in better outcomes. Here I review how the argumentative theory of reasoning helps integrate a wide range of empirical findings in reasoning research.

Professional Decision-Making in Research (PDR): The Validity of a New Measure

In this paper, we report on the development and validity of the Professional Decision-Making in Research (PDR) measure, a vignette-based test that examines decision-making strategies used by investigators when confronted with challenging situations in the context of empirical research. The PDR was administered online with a battery of validity measures to a group of NIH-funded researchers and research trainees who were diverse in terms of age, years of experience, types of research, and race. The PDR demonstrated adequate reliability (alpha = .84) and parallel form correlation (r = .70). As hypothesized, the PDR was significantly negatively correlated with narcissism, cynicism, moral disengagement, and compliance disengagement; it was not correlated with socially desirable responding. In regression analysis, the strongest predictors of higher PDR scores were low compliance disengagement, speaking English as a native language, conducting clinical research with human subjects, and low levels of narcissism. Given that the PDR was written at an eighth grade reading level to be suitable for use with English as a second language participants and that only one-fourth of items focused on clinical research, further research into the possible roles of culture and research ethics training across specialties is warranted. This initial validity study demonstrates the potential usefulness of the PDR as an educational outcome assessment measure and a research instrument for studies on professionalism and integrity in research.

The dynamics of deferred decision

Decision makers are often unable to choose between the options that they are offered. In these settings they typically defer their decision, that is, delay the decision to a later point in time or avoid the decision altogether. In this paper, we outline eight behavioral findings regarding the causes and consequences of choice deferral that cognitive theories of decision making should be able to capture. We show that these findings can be accounted for by a deferral-based time limit applied to existing sequential sampling models of preferential choice. Our approach to modeling deferral as a time limit in a sequential sampling model also makes a number of novel predictions regarding the interactions between choice probabilities, deferral probabilities, and decision times, and we confirm these predictions in an experiment. Choice deferral is a key feature of everyday decision making, and our paper illustrates how established theoretical approaches can be used to understand the cognitive underpinnings of this important behavioral phenomenon.

Annual Research Review: Transdiagnostic neuroscience of child and adolescent mental disorders--differentiating decision making in attention-deficit/hyperactivity disorder, conduct disorder, depression, and anxiety

BACKGROUND

Ineffective decision making is a major source of everyday functional impairment and reduced quality of life for young people with mental disorders. However, very little is known about what distinguishes decision making by individuals with different disorders or the neuropsychological processes or brain systems underlying these. This is the focus of the current review.

SCOPE AND METHODOLOGY

We first propose a neuroeconomic model of the decision-making process with separate stages for the prechoice evaluation of expected utility of future options; choice execution and postchoice management; the appraisal of outcome against expectation; and the updating of value estimates to guide future decisions. According to the proposed model, decision making is mediated by neuropsychological processes operating within three domains: (a) self-referential processes involved in autobiographical reflection on past, and prospection about future, experiences; (b) executive functions, such as working memory, inhibition, and planning, that regulate the implementation of decisions; and (c) processes involved in value estimation and outcome appraisal and learning. These processes are underpinned by the interplay of multiple brain networks, especially medial and lateralized cortical components of the default mode network, dorsal corticostriatal circuits underpinning higher order cognitive and behavioral control, and ventral frontostriatal circuits, connecting to brain regions implicated in emotion processing, that control valuation and learning processes.

FINDINGS AND CONCLUSION

Based on clinical insights and considering each of the decision-making stages in turn, we outline disorder-specific hypotheses about impaired decision making in four childhood disorders: attention-deficit/hyperactivity disorder (ADHD), conduct disorder (CD), depression, and anxiety. We hypothesize that decision making in ADHD is deficient (i.e. inefficient, insufficiently reflective, and inconsistent) and impulsive (biased toward immediate over delayed alternatives). In CD, it is reckless and insensitive to negative consequences. In depression, it is disengaged, perseverative, and pessimistic, while in anxiety, it is hesitant, risk-averse, and self-deprecating. A survey of current empirical indications related to these disorder-specific hypotheses highlights the limited and fragmentary nature of the evidence base and illustrates the need for a major research initiative in decision making in childhood disorders. The final section highlights a number of important additional general themes that need to be considered in future research.