Behavioral Norms for Condensed Moral Vignettes.” SCAN

Moral judgment is an evaluation of the actions and character of a person made with respect to societal norms. Although many types of vignettes have been used in previous studies on moral beliefs and judgment, what is missing is a set of standardized common vignettes based in real life. The goal of this study was to provide researchers with stimuli that have values on several dimensions pertaining to moral judgment and whose underlying components are known. These values will allow researchers to select stimuli based on standardized ratings rather than on the results of pilot studies, while avoiding the limitations of the classic, abstract moral scenarios. Our study was composed of three phases, (i) collecting and shortening the vignettes, (ii) obtaining ratings of the vignettes on several dimensions including emotional intensity, degree of social norm violation, and level of harm or benefit caused and (iii) determining the underlying components of the vignettes by performing a factor analysis. We found three components that accounted for most of the variance: norm violation, social affect and intention. The resulting vignettes can be used in future parametric studies on moral judgment in behavioral, neuropsychological and functional imaging experiments

Depression and sickness behavior are Janus-faced responses to shared inflammatory pathways

It is of considerable translational importance whether depression is a form or a consequence of sickness behavior. Sickness behavior is a behavioral complex induced by infections and immune trauma and mediated by pro-inflammatory cytokines. It is an adaptive response that enhances recovery by conserving energy to combat acute inflammation. There are considerable phenomenological similarities between sickness behavior and depression, for example, behavioral inhibition, anorexia and weight loss, and melancholic (anhedonia), physio-somatic (fatigue, hyperalgesia, malaise), anxiety and neurocognitive symptoms. In clinical depression, however, a transition occurs to sensitization of immuno-inflammatory pathways, progressive damage by oxidative and nitrosative stress to lipids, proteins, and DNA, and autoimmune responses directed against self-epitopes. The latter mechanisms are the substrate of a neuroprogressive process, whereby multiple depressive episodes cause neural tissue damage and consequent functional and cognitive sequelae. Thus, shared immuno-inflammatory pathways underpin the physiology of sickness behavior and the pathophysiology of clinical depression explaining their partially overlapping phenomenology. Inflammation may provoke a Janus-faced response with a good, acute side, generating protective inflammation through sickness behavior and a bad, chronic side, for example, clinical depression, a lifelong disorder with positive feedback loops between (neuro)inflammation and (neuro)degenerative processes following less well defined triggers

Bilingualism, social cognition and executive functions:A tale of chickens and eggs

AbstractThe influence of bilingualism on cognitive functioning is currently a topic of intense scientific debate. The strongest evidence for a cognitive benefit of bilingualism has been demonstrated in executive functions. However, the causal direction of the relationship remains unclear: does learning other languages improve executive functions or are people with better executive abilities more likely to become bilingual?To address this, we examined 90 male participants of the Lothian Birth Cohort 1936; 26 were bilingual, 64 monolingual. All participants underwent an intelligence test at age 11 years and were assessed on a wide range of executive and social cognition tasks at age 74. The only notable differences between both groups were found for the Simon Effect (which indexes stimulus-response conflict resolution; β=−.518, p=0.025) and a trend effect for the Faux Pas task (a measure of complex theory of mind; ToM, β=0.432, p=0.060). Controlling for the influence of childhood intelligence, parental and own social class significantly attenuated the bilingual advantage on the Faux Pas test (β=0.058, p=0.816), whereas the Simon task advantage remained (β=−.589, p=0.049).We find some weak evidence that the relationship between bilingualism and cognitive functions may be selective and bi-directional. Pre-existing cognitive and social class differences from childhood may influence both ToM ability in older age and the likelihood of learning another language; yet, bilingualism does not appear to independently contribute to Faux Pas score. Conversely, learning a second language is related to better conflict processing, irrespective of initial childhood ability or social class

Preferring one taste over another without recognizing either

Stimuli can be discriminated without being consciously perceived and can be preferred without being remembered. Here we report a subject with a previously unknown dissociation of abilities: a strong behavioral preference for the taste of sugar over saline, despite a complete failure of recognition. The pattern of brain damage responsible for the dissociation suggests that reliable behavioral choice among tastes can occur in the absence of the gustatory cortex necessary for taste recognition

Clarifying the relationship between mental illness and recidivism using machine learning: A retrospective study.

ObjectiveThere is currently inconclusive evidence regarding the relationship between recidivism and mental illness. This retrospective study aimed to use rigorous machine learning methods to understand the unique predictive utility of mental illness for recidivism in a general population (i.e.; not only those with mental illness) prison sample in the United States.MethodParticipants were adult men (n = 322) and women (n = 72) who were recruited from three prisons in the Midwest region of the United States. Three model comparisons using Bayesian correlated t-tests were conducted to understand the incremental predictive utility of mental illness, substance use, and crime and demographic variables for recidivism prediction. Three classification statistical algorithms were considered while evaluating model configurations for the t-tests: elastic net logistic regression (GLMnet), k-nearest neighbors (KNN), and random forests (RF).ResultsRates of substance use disorders were particularly high in our sample (86.29%). Mental illness variables and substance use variables did not add predictive utility for recidivism prediction over and above crime and demographic variables. Exploratory analyses comparing the crime and demographic, substance use, and mental illness feature sets to null models found that only the crime and demographics model had an increased likelihood of improving recidivism prediction accuracy.ConclusionsDespite not finding a direct relationship between mental illness and recidivism, treatment of mental illness in incarcerated populations is still essential due to the high rates of mental illnesses, the legal imperative, the possibility of decreasing institutional disciplinary burden, the opportunity to increase the effectiveness of rehabilitation programs in prison, and the potential to improve meaningful outcomes beyond recidivism following release

Behavioral norms for condensed moral vignettes

Moral judgment is an evaluation of the actions and character of a person made with respect to societal norms. Although many types of vignettes have been used in previous studies on moral beliefs and judgment, what is missing is a set of standardized common vignettes based in real life. The goal of this study was to provide researchers with stimuli that have values on several dimensions pertaining to moral judgment and whose underlying components are known. These values will allow researchers to select stimuli based on standardized ratings rather than on the results of pilot studies, while avoiding the limitations of the classic, abstract moral scenarios. Our study was composed of three phases, (i) collecting and shortening the vignettes, (ii) obtaining ratings of the vignettes on several dimensions including emotional intensity, degree of social norm violation, and level of harm or benefit caused and (iii) determining the underlying components of the vignettes by performing a factor analysis. We found three components that accounted for most of the variance: norm violation, social affect and intention. The resulting vignettes can be used in future parametric studies on moral judgment in behavioral, neuropsychological and functional imaging experiments

The “Best of Both Worlds”: Building an authentic and equitable community-academic partnership for research with legal system-impacted individuals

Equitable and sustained community-academic partnerships are crucial for research on improving health outcomes among criminal legal system-impacted individuals. This paper was co-written by members of a unique research team consisting of academic researchers and community partners, including formerly incarcerated individuals. Drawing from meeting notes, panel presentations, and informal conversations, we describe the opportunities and challenges that emerged through a year-long pilot project intended to adapt a mental health intervention for correctional settings. The somewhat narrow focus of this project expanded dramatically over the course of the year as team members adapted to working together and realized the potential for the sustained impact of a long-term collaboration. Through this process, team members developed deep respect for one another’s ideas and expertise, whether rooted in academic training or lived experiences. Our experiences offer lessons for other researchers interested in community-engaged research that centers the perspective of legal system-impacted individuals

Posterior probabilities for main model comparisons.

The vertical dotted line represents equal performance (i.e., no difference in accuracy) between the associated augmented and compact model. A) There is a 38.76% chance that adding both the mental illness and substance use feature sets improves model performance above and beyond the crime and demographic feature sets. B) There is a 60.32% chance that adding the mental illness feature set would improve model performance above and beyond the crime, demographic, and substance use feature sets. C) There is a 53.11% chance that adding the substance use feature set would improve model performance above and beyond the crime, demographic, and mental illness feature sets.</p