Variability in aphasic patients' response times

Response time studies of acquired language disorders are plagued by tremendous variability in patients' response times. In this brief report we demonstrate how variability itself may provide informative data. Lexical decision response times, generated by nine patients, illustrate how within-patient variability may estimate stability in cognitive dynamics.     

Gender is a dimension of face recognition

In an experiment, the authors investigated the impact of gender categorization on face recognition. Participants were familiarized with composite androgynous faces labeled with either a woman's first name (Mary) or a man's first name (John). The results indicated that participants more quickly eliminated faces of the opposite gender than faces of the same gender than the face they were looking for. This gender effect did not result from greater similarity between faces of the same gender. Rather, early gender categorization of a face during face recognition appears to speed up the comparison process between the perceptual input and the facial representation. Implications for face recognition models are discussed.     

Human cognition and 1/f scaling

Ubiquitous 1/f scaling in human cognition and physiology suggests a mind-body interaction that contradicts commonly held assumptions. The intrinsic dynamics of psychological phenomena are interaction dominant (rather than component dominant), and the origin of purposive behavior lies with a general principle of self-organization (rather than a special neurocognitive mechanism). E.-J. Wagenmakers, S. Farrell, and R. Ratcliff (2005) raised concerns about the kinds of data and analyses that support generic 1/f scaling. This reply is a defense that furthermore questions the model that Wagenmakers and colleagues endorse and their strategy for addressing complexity.     

Juror decision-making in a mock sexually violent predator trial: gender differences in the impact of divergent types of expert testimony

Despite widespread use of mental health testimony in cases where violence risk is at issue, relatively little is known about the impact of such information on juror decision-making. This study addressed the effects of testimony based on three types of risk assessment instrument or method (clinical opinion, actuarial assessment, and ratings of psychopathy) to examine whether they would have differential impact on jurors' perceptions of the defendant. In a mock sexually violent predator civil commitment trial, 172 undergraduates were presented a case summary that included prosecution and defense expert testimony related to violence risk based on one of the three methods noted above. Consistent with earlier research, the hypothesis that a defendant described as a "high risk psychopath" by the prosecution would be judged more severely than a defendant judged as "high risk" based on other evaluation procedures was supported, but only among female jurors. Unlike prior studies, little support was found for the hypothesis that clinical opinion testimony would be more influential than actuarially based testimony for either gender. Mechanisms that may underlie the observed gender differences are discussed, as are the potential implications of these findings for civil commitment proceedings.     

Factors differentiating successful versus unsuccessful malingerers.

Relatively little is known about the processes in which "successful" malingerers engage to avoid detection. This study summarizes the response strategies used by participants (N = 540) instructed to feign a specific mental disorder while completing various self-report instruments designed to detect faking. Postexperiment questionnaires indicated that those who were able to appear symptomatic while avoiding being detected as feigning (n = 60) were more likely to endorse a lower rate of legitimate symptoms, to avoid overly unusual or bizarre items, and to base their responses on their own personal experiences.     

Does Risk Assessment Make a Difference? Results of Implementing the SAVRY in Juvenile Probation

An effective approach to reducing recidivism is, first, to identify a youth's risk of reoffending and then to match the intensity of interventions to that risk level. This pre-post quasi-experimental, prospective study compared 247 (pre) with 217 (post) adjudicated youths to examine the implementation of the Structured Assessment of Violence Risk in Youth (SAVRY) and its effects on case management practices in Louisiana's Caddo parish probation office. The results indicated that placement rates dropped by 50%, use of maximum levels of supervision dropped by almost 30%, and use of community services decreased except for high-risk youths, but only after the SAVRY was properly implemented. This shift towards more appropriate allocation of resources that are matched to risk level occurred without a significant increase in reoffending. The implications for implementation and for use of risk/needs assessment in juvenile probation are discussed. Copyright ? 2012 John Wiley & Sons, Ltd.     

An optimal adjustment procedure to minimize experiment time in decisions with multiple alternatives

Decisions between multiple alternatives typically conform to Hick’s Law: Mean response time increases log-linearly with the number of choice alternatives. We recently demonstrated context effects in Hick’s Law, showing that patterns of response latency and choice accuracy were different for easy versus difficult blocks. The context effect explained previously observed discrepancies in error rate data and provided a new challenge for theoretical accounts of multialternative choice. In the present article, we propose a novel approach to modeling context effects that can be applied to any account that models the speed–accuracy trade-off. The core element of the approach is “optimality” in the way an experimental participant might define it: minimizing the total time spent in the experiment, without making too many errors. We show how this approach can be included in an existing Bayesian model of choice and highlight its ability to fit previous data as well as to predict novel empirical context effects. The model is shown to provide better quantitative fits than a more flexible heuristic account.