Models of quantitative estimations: Rule-based and exemplar-based processes compared.

The cognitive processes underlying quantitative estimations vary. Past research has identified task-contingent changes between rule-based and exemplar-based processes (P. Juslin, L. Karlsson, & H. Olsson, 2008). B. von Helversen and J. Rieskamp (2008), however, proposed a simple rule-based model—the mapping model—that outperformed the exemplar model in a task thought to promote exemplar-based processing. This raised questions about the assumptions of rule-based versus exemplar-based models that underlie the notion of task contingency of cognitive processes. Rule-based models, such as the mapping model, assume the abstraction of explicit task knowledge. In contrast, exemplar models should profit if storage and activation of the exemplars is facilitated. Two studies tested the importance of the two models’ assumptions. When knowledge about cues existed, the rule-based mapping model predicted quantitative estimations best. In contrast, when knowledge about the cues was difficult to gain, participants’ estimations were best described by an exemplar model. The results emphasize the task contingency of cognitive processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Causal client models in selecting effective interventions: A cognitive mapping study.

An important reason to choose an intervention to treat psychological problems of clients is the expectation that the intervention will be effective in alleviating the problems. The authors investigated whether clinicians base their ratings of the effectiveness of interventions on models that they construct representing the factors causing and maintaining a client's problems. Forty clinical child psychologists drew causal models and rank ordered interventions according to their expected effectiveness for 2 cases. The authors found that different clinicians constructed different causal models for the same client. Also, the authors found low to moderate agreement about the effectiveness of different interventions. Nevertheless, the authors could predict clinicians' ratings of effectiveness from their individual causal models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Predicting sentencing for low-level crimes: Comparing models of human judgment.

Laws and guidelines regulating legal decision making are often imposed without taking the cognitive processes of the legal decision maker into account. In the case of sentencing, this raises the question of whether the sentencing decisions of prosecutors and judges are consistent with legal policy. Especially in handling low-level crimes, legal personnel suffer from high case loads and time pressure, which can make it difficult to comply with the often complex rulings of the law. To understand the cognitive processes underlying sentencing decisions, an analysis of trial records in cases of larceny, fraud, and forgery was conducted. Applying a Bayesian approach, five models of human judgment were tested against each other to predict the sentencing recommendations of the prosecution and to identify the crucial factors influencing sentencing decisions. The factors influencing sentencing were broadly consistent with the penal code. However, the prosecutors considered only a limited number of factors and neglected factors that were legally relevant and rated as highly important. Furthermore, testing the various cognitive judgment models against each other revealed that the sentencing process was apparently not consistent with the judgment policy recommended by the legal literature. Instead, the results show that prosecutors’ sentencing recommendations were best described by the mapping model, a heuristic model of quantitative estimation. According to this model, sentencing recommendations rely on a categorization of cases based on the cases’ characteristics. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluating cognitive theory: A joint modeling approach using responses and response times.

In current psychological research, the analysis of data from computer-based assessments or experiments is often confined to accuracy scores. Response times, although being an important source of additional information, are either neglected or analyzed separately. In this article, a new model is developed that allows the simultaneous analysis of accuracy scores and response times of cognitive tests with a rule-based design. The model is capable of simultaneously estimating ability and speed on the person side as well as difficulty and time intensity on the task side, thus dissociating information that is often confounded in current analysis procedures. Further, by integrating design matrices on the task side, it becomes possible to assess the effects of design parameters (e.g., cognitive processes) on both task difficulty and time intensity, offering deeper insights into the task structure. A Bayesian approach, using Markov Chain Monte Carlo methods, has been developed to estimate the model. An application of the model in the context of educational assessment is illustrated using a large-scale investigation of figural reasoning ability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Integrating neural networks into decision-making and motivational theory: Rethinking VIE theory.

[Correction Notice: An erratum for this article was reported in Vol 44(3) of Canadian Psychology/Psychologie Canadienne (see record 2007-16858-001). The paper by Lord, Henges and Godfrey, referred to in some of the commentaries (this issue), was accepted as part of the Special Section on psychology without boundaries. However, it was inadvertently published in a previous issue. The full reference is: Lord, R. G., Hanges, P. J., & Godfrey, E. G. (2003). Integrating neural networks into decision-making and motivational theory: Rethinking VIE theory. Canadian Psychology, 44 (1), 21-38.] Uses a reformulation of V. H. Vroom's (1964) VIE (Valence-Instrumentality-Expectancy) theory to illustrate the potential value of neuropsychologically based models of cognitive processes. Vroom's theory posits that people's decisions are determined by their affective reactions to certain outcomes (valences), beliefs about the relationship between actions and outcomes (expectancies), and perceptions of the association between primary and secondary outcomes (instrumentalities). One of the major criticisms of this type of theory is that the computations it requires are unrealistically time-consuming and often exceed working memory capacity. In this paper, the authors maintain that if an individual has extensive experience with a problem situation, he or she can process decisions about that situation using neural networks that operate implicitly so that cognitive resources are not exhausted by simple computations; instead, the computations are performed implicitly by neural networks. By thinking about VIE from a neural network standpoint, at least one of its problems is eliminated, and several new insights into decision-making are provided. The authors use simulation methodology to show that such a model is both viable and can reflect the effects of current goals on choice processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A formal cognitive model of the go/no-go discrimination task: Evaluation and implications.

This article proposes and tests a formal cognitive model for the go/no-go discrimination task. In this task, the performer chooses whether to respond to stimuli and receives rewards for responding to certain stimuli and punishments for responding to others. Three cognitive models were evaluated on the basis of data from a longitudinal study involving 400 adolescents. The results show that a cue-dependent model presupposing that participants can differentiate between cues was the most accurate and parsimonious. This model has 3 parameters denoting the relative impact of rewards and punishments on evaluations, the rate that contingent payoffs are learned, and the consistency between learning and responding. Commission errors were associated with increased attention to rewards; omission errors were associated with increased attention to punishments. Both error types were associated with low choice consistency. The parameters were also shown to have external validity: Attention to rewards was associated with externalizing behavior problems on the Achenbach scale, and choice consistency was associated with low Welsh anxiety. The present model can thus potentially improve the sensitivity of the task to differences between clinical populations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Some implications of the new cognitive theory for projective tests.

Projective tests are examined in the light of information theory, decision theory, and computer-stimulation techniques. It is argued that (a) more attention needs to be paid to stimulus variables and that decision theory offers an approach to stimulus definition, (b) a different interpretative tactic is implied by decision theory, and (c) the problem of criterion definition is reopened in the light of decision theory. A simple cognitive model based on computer-simulation approaches is presented in order to demonstrate how an informational analysis might cope with projective responses. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Tradeoffs and theory: The double-mediation model.

[Correction Notice: An erratum for this article was reported in Vol 135(4) of Journal of Experimental Psychology: General (see record 2006-20327-004). This article was inadvertently printed with the incorrect title. A clarification regarding the correct title is provided in the erratum.] Most theories of decision making suggest that, when options imply tradeoffs between their attributes, conflict increases as tradeoff size increases, because greater sacrifices are to be incurred in choosing one option instead of another. An alternative view is that conflict decreases as tradeoff size increases, because stronger arguments can be made for any decision. The authors propose a unified model, the double-mediation model, which combines the mediating effects of sacrifice and argumentation. Our model generally predicts an inverse U-shaped relation between tradeoff size and conflict. Results support this prediction. Also, when the decision situation increases the mediating effect of sacrifice relative to that of argumentation, the relation between tradeoff size and conflict changes in an upward direction; conversely, when the decision situation increases the mediating effect of argumentation relative to that of sacrifice, the relation changes in a downward direction. Results support these predictions as well. Commonalities and differences between our model and other formulations are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Cognitive Substrate of Subjective Probability.

The prominent cognitive theories of probability judgment were primarily developed to explain cognitive biases rather than to account for the cognitive processes in probability judgment. In this article the authors compare 3 major theories of the processes and representations in probability judgment: the representativeness heuristic, implemented as prototype similarity, relative likelihood, or evidential support accumulation (ESAM; D. J. Koehler, C. M. White, & R. Grondin, 2003); cue-based relative frequency; and exemplar memory, implemented by probabilities from exemplars (PROBEX; P. Juslin & M. Persson, 2002). Three experiments with different task structures consistently demonstrate that exemplar memory is the best account of the data whereas the results are inconsistent with extant formulations of the representativeness heuristic and cue-based relative frequency. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

"Integrating neural networks into decision-making and motivational theory: Rethinking VIE theory": Erratum.

Reports an error in "Integrating neural networks into decision-making and motivational theory: Rethinking VIE theory" by Robert G. Lord, Paul J. Hanges and Ellen G. Godfrey (Canadian Psychology/Psychologie Canadienne, 2003[Feb], Vol 44[1], 21-38). The paper by Lord, Henges and Godfrey, referred to in some of the commentaries (this issue), was accepted as part of the Special Section on psychology without boundaries. However, it was inadvertently published in a previous issue. The full reference is: Lord, R. G., Hanges, P. J., & Godfrey, E. G. (2003). Integrating neural networks into decision-making and motivational theory: Rethinking VIE theory. Canadian Psychology, 44 (1), 21-38. (The following abstract of the original article appeared in record 2003-01537-005.) Uses a reformulation of V. H. Vroom's (1964) VIE (Valence-Instrumentality-Expectancy) theory to illustrate the potential value of neuropsychologically based models of cognitive processes. Vroom's theory posits that people's decisions are determined by their affective reactions to certain outcomes (valences), beliefs about the relationship between actions and outcomes (expectancies), and perceptions of the association between primary and secondary outcomes (instrumentalities). One of the major criticisms of this type of theory is that the computations it requires are unrealistically time-consuming and often exceed working memory capacity. In this paper, the authors maintain that if an individual has extensive experience with a problem situation, he or she can process decisions about that situation using neural networks that operate implicitly so that cognitive resources are not exhausted by simple computations; instead, the computations are performed implicitly by neural networks. By thinking about VIE from a neural network standpoint, at least one of its problems is eliminated, and several new insights into decision-making are provided. The authors use simulation methodology to show that such a model is both viable and can reflect the effects of current goals on choice processes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The role of uncertainty in cognitive change.

Cognitive change was hypothesized to be related to level of S's feeling of uncertainty. Judgments of a photographic stimulus under varying conditions of feedback and quality of stimulus were elicited. The results indicated that change in judgment (cognitive change) is associated with change in level of uncertainty, and the conditions of cognitive change were similar to the Lewinian conceptualization of social change. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The problem state: A cognitive bottleneck in multitasking.

The main challenge for theories of multitasking is to predict when and how tasks interfere. Here, we focus on interference related to the problem state, a directly accessible intermediate representation of the current state of a task. On the basis of Salvucci and Taatgen’s (2008) threaded cognition theory, we predict interference if 2 or more tasks require a problem state but not when only one task requires one. This prediction was tested in a series of 3 experiments. In Experiment 1, a subtraction task and a text entry task had to be carried out concurrently. Both tasks were presented in 2 versions: one that required maintaining a problem state and one that did not. A significant overadditive interaction effect was observed, showing that the interference between tasks was maximal when both tasks required a problem state. The other 2 experiments tested whether the interference was indeed due to a problem state bottleneck, instead of cognitive load (Experiment 2: an alternative subtraction and text entry experiment) or a phonological loop bottleneck (Experiment 3: a triple-task experiment that added phonological processing). Both experiments supported the problem state hypothesis. To account for the observed behavior, computational cognitive models were developed using threaded cognition within the context of the cognitive architecture ACT-R (Anderson, 2007). The models confirm that a problem state bottleneck can explain the observed interference. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Crisis decision theory: Decisions in the face of negative events.

How do people respond to negative life events? Crisis decision theory combines the strengths of coping theories with research on decision making to predict the responses people choose under negative circumstances. The theory integrates literatures on coping, health behavior, and decision making, among others, into 3 stages that describe the process of responding to negative events: (a) assessing the severity of the negative event, (b) determining response options, and (c) evaluating response options. The author reviews and organizes the relevant research on factors that shape information processing at each stage and that ultimately predict decisions in the face of negative events. Finally, the author presents a critique of crisis decision theory and discusses areas for future research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Decision making and the avoidance of cognitive demand.

Behavioral and economic theories have long maintained that actions are chosen so as to minimize demands for exertion or work, a principle sometimes referred to as the law of less work. The data supporting this idea pertain almost entirely to demands for physical effort. However, the same minimization principle has often been assumed also to apply to cognitive demand. The authors set out to evaluate the validity of this assumption. In 6 behavioral experiments, participants chose freely between courses of action associated with different levels of demand for controlled information processing. Together, the results of these experiments revealed a bias in favor of the less demanding course of action. The bias was obtained across a range of choice settings and demand manipulations and was not wholly attributable to strategic avoidance of errors, minimization of time on task, or maximization of the rate of goal achievement. It is remarkable that the effect also did not depend on awareness of the demand manipulation. Consistent with a motivational account, avoidance of demand displayed sensitivity to task incentives and covaried with individual differences in the efficacy of executive control. The findings reported, together with convergent neuroscientific evidence, lend support to the idea that anticipated cognitive demand plays a significant role in behavioral decision making. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A neurocognitive model of the ethical decision-making process: Implications for study and practice.

The field of business ethics is entrenched in a cognitive approach that portrays the ethical decision-making process as a completely deliberate and reasoned exercise. In light of growing concerns about the veracity of this approach, I build upon current knowledge of how the brain functions to present a neurocognitive model of ethical decision making. The model suggests that ethical decision making involves 2 interrelated yet functionally distinct cycles, a reflexive pattern matching cycle and a higher order conscious reasoning cycle, and thereby describes not only reasoned analysis, but also the intuitive and retrospective aspects of ethical decision making. The model sparks research in new areas, holds significant implications for the study of ethical decision making, and provides suggestions for improving ethical behavior in organizations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The intentionality model: A theoretical integration of psychodynamic talking and relating with cognitive–behavioral interventions.

The intentionality model is a model for integrative practice that links the awareness of clients to the interventions of therapists. The model is experientially based because psychological distress is assessed in terms of mental processes, or intentionalities, which create complex outcomes of emotion, repetitive patterns of maladaptive relating, and persistently negative mood. Intentionality refers to the many ways in which consciousness is aware. Accordingly, psychological interventions become recognizable as preparing for and creating changes in meaning by helping clients obtain new experiences and occupy new perspectives on what already exists. The intellectual background is the classical phenomenological psychology of Edmund Husserl, a theory of mind. Given that psychological suffering and health concern the awareness of meaning, and the intentionality of consciousness refers to the many ways in which people can be conscious of the same object of attention, it is argued that therapy concerns making changes in the forms of being aware. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Age, executive function and social decision making: A dorsolateral prefrontal theory of cognitive aging.

Current neuropsychological models propose that some age-related cognitive changes are due to frontal-lobe deterioration. However, these models have not considered the possible subdivision of the frontal lobes into the dorsolateral and ventromedial regions. This study assessed the age effects on 3 tasks of executive function and working memory, tasks dependent on dorsolateral prefrontal dysfunction; and 3 tasks of emotion and social decision making, tasks dependent on ventromedial prefrontal dysfunction. Age-related differences in performance were found on all tasks dependent on dorsolateral prefrontal dysfunction. In contrast, age-related differences were not found on the majority of the tasks dependent on ventromedial prefrontal dysfunction. The results support a specific dorsolateral prefrontal theory of cognitive changes with age, rather than a global decline in frontal-lobe function. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Social cognitive theory and cancer patients' quality of life: A meta-analysis of psychosocial intervention components.

Social cognitive theory (SCT) provides a theoretical framework to evaluate improved quality-of-life (QOL) outcomes through interventions with cancer patients. To assess whether inclusion of SCT components predicted better outcomes, focused comparisons were used to integrate results from 38 randomized studies. Interventions with more SCT components had significantly larger effect sizes than studies with fewer or no SCT components for the overall analysis (Z = 3.72, p