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Prison sentences that exceed the natural lifespan present a puzzle because they have no more power to deter or incapacitate than a single life sentence. In three survey experiments, we tested the extent to which participants support these longer-than-life sentences under different decision contexts. In Experiment 1, 130 undergraduates made hypothetical prison sentence-length recommendations for a serious criminal offender, warranting two sentences to be served either concurrently or consecutively. Using a nationally representative sample (N = 182) and an undergraduate pilot sample (N = 260), participants in Experiments 2 and 3 voted on a hypothetical ballot measure to either allow or prohibit the use of consecutive life sentences. Results from all experiments revealed that, compared to concurrent life sentences participants supported the use of consecutive life sentences for serious offenders. In addition, they adjusted these posthumous years in response to mitigating factors in a manner that was indistinguishable from ordinary sentences (Experiment 1), and their support for consecutive life sentencing policies persisted, regardless of the default choice and whether the policy was costly to implement (Experiments 2 and 3). These judgment patterns were most consistent with retributive punishment heuristics and have implications for sentencing policy and for theories of punishment behavior.

Advances in artificial intelligence (AI) raise important questions about whether people view moral evaluations by AI systems similarly to human-generated moral evaluations. We conducted a modified Moral Turing Test (m-MTT), inspired by Allen et al. (Exp Theor Artif Intell 352:24-28, 2004) proposal, by asking people to distinguish real human moral evaluations from those made by a popular advanced AI language model: GPT-4. A representative sample of 299 U.S. adults first rated the quality of moral evaluations when blinded to their source. Remarkably, they rated the AI's moral reasoning as superior in quality to humans' along almost all dimensions, including virtuousness, intelligence, and trustworthiness, consistent with passing what Allen and colleagues call the comparative MTT. Next, when tasked with identifying the source of each evaluation (human or computer), people performed significantly above chance levels. Although the AI did not pass this test, this was not because of its inferior moral reasoning but, potentially, its perceived superiority, among other possible explanations. The emergence of language models capable of producing moral responses perceived as superior in quality to humans' raises concerns that people may uncritically accept potentially harmful moral guidance from AI. This possibility highlights the need for safeguards around generative language models in matters of morality., (© 2024. The Author(s).)

Previous work in incarcerated boys and adult men and women suggest that individuals scoring high on psychopathic traits show altered resting-state limbic/paralimbic, and default mode functional network properties. However, it is unclear whether similar results extend to high-risk adolescent girls with elevated psychopathic traits. This study examined whether psychopathic traits [assessed via the Hare Psychopathy Checklist: Youth Version (PCL:YV)] were associated with altered inter-network connectivity, intra-network connectivity (i.e., functional coherence within a network), and amplitude of low-frequency fluctuations (ALFFs) across resting-state networks among high-risk incarcerated adolescent girls ( n = 40). Resting-state networks were identified by applying group independent component analysis (ICA) to resting-state fMRI scans, and a priori regions of interest included limbic, paralimbic, and default mode network components. We tested the association of psychopathic traits (PCL:YV Factor 1 measuring affective/interpersonal traits and PCL:YV Factor 2 assessing antisocial/lifestyle traits) to these three resting-state measures. PCL:YV Factor 1 scores were associated with increased low-frequency and decreased high-frequency fluctuations in components corresponding to the default mode network, as well as increased intra-network FNC in components corresponding to cognitive control networks. PCL:YV Factor 2 scores were associated with increased low-frequency fluctuations in sensorimotor networks and decreased high-frequency fluctuations in default mode, sensorimotor, and visual networks. Consistent with previous analyses in incarcerated adult women, our results suggest that psychopathic traits among incarcerated adolescent girls are associated with altered intra-network ALFFs-primarily that of increased low-frequency and decreased high-frequency fluctuations-and connectivity across multiple networks including paralimbic regions. These results suggest stable neurobiological correlates of psychopathic traits among women across development., Competing Interests: CA, JM, AG, BE, CH, NA, KH, and KK were employed by The Mind Research Network. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Allen, Maurer, Gullapalli, Edwards, Aharoni, Harenski, Anderson, Harenski, Calhoun and Kiehl.)

Background: Hematopoietic stem cell transplantation (HSCT) is the only curative option for many nonmalignant hematopoietic-derived diseases in pediatric patients. Survival after HSCT has improved in recent years and resulted in a 90% survival rate and cure in some nonmalignant diseases. Graft-vs.-host disease (GVHD) remains a frequent and major complication of HSCT, and a leading cause of morbidity and mortality. Prognosis of patients with high-grade GVHD is dismal, with survival rates varying from 25% in the adult population to 55% in pediatric patients., Methods: The main aim of this study is to evaluate the incidence, risk factors, and outcome of severe acute GVHD (AGVHD) in pediatric patients with nonmalignant diseases, following allogeneic HSCT. Clinical and transplant data were retrospectively collected for all pediatric patients who underwent allogeneic HSCT for nonmalignant diseases at the Hadassah Medical Center between 2008 and 2019. Patients who developed severe AGVHD were compared with those who did not., Results: A total of 247 children with nonmalignant diseases underwent 266 allogeneic HSCTs at Hadassah University Hospital over an 11-year period. Seventy-two patients (29.1%) developed AGVHD, 35 of them (14.1%) severe AGVHD (grade 3-4). Significant risk factors for developing severe AGVHD were unrelated donor ( p  < 0.001), mismatch donor ( p  < 0.001), and the use of peripheral blood stem cells (PBSCs) ( p  < 0.001). Survival rates of pediatric patients with severe AGVHD was 71.4%, compared with 91.9% among those with mild (grade 1-2) AGVHD and 83.4% among patients without AGVHD ( p  = 0.067)., Conclusions: These results demonstrate a high survival rate in pediatric patients with nonmalignant diseases despite severe GVHD. Significant mortality risk factors found in these patients were the source of donor PBSC ( p  = 0.016) and poor response to steroid treatment ( p  = 0.007)., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Zaidman, Even-Or, Aharoni, Averbuch, Dinur-Schejter, NaserEddin, Slae, Shadur and Stepensky.)

Scholars have proposed that incarceration rates might be reduced by a requirement that judges justify incarceration decisions with respect to their operational costs (e.g., prison capacity). In an Internet-based vignette experiment ( N = 214), we tested this prediction by examining whether criminal punishment judgments (prison vs. probation) among university undergraduates would be influenced by a prompt to provide a justification for one's judgment, and by a brief message describing prison capacity costs. We found that (1) the justification prompt alone was sufficient to reduce incarceration rates, (2) the prison capacity message also independently reduced incarceration rates, and (3) incarceration rates were most strongly reduced (by about 25%) when decision makers were asked to justify their sentences with respect to the expected capacity costs. These effects survived a test of robustness and occurred regardless of whether participants reported that prison costs should influence judgments of incarceration. At the individual crime level, the least serious crimes were most amenable to reconsideration for probation. These findings are important for policymakers attempting to manage high incarceration rates., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Aharoni, Nahmias, Hoffman and Fernandes.)

Judges are typically tasked to consider sentencing benefits but not costs. Previous research finds that both laypeople and prosecutors discount the costs of incarceration when forming sentencing attitudes, raising important questions about whether professional judges show the same bias during sentencing. To test this, we used a vignette-based experiment in which Minnesota state judges ( N  = 87) reviewed a case summary about an aggravated robbery and imposed a hypothetical sentence. Using random assignment, half the participants received additional information about plausible negative consequences of incarceration. As predicted, our results revealed a mitigating effect of cost exposure on prison sentence term lengths. Critically, these findings support the conclusion that policies that increase transparency in sentencing costs could reduce sentence lengths, which has important economic and social ramifications., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Aharoni, Kleider-Offutt, Brosnan and Hoffman.)

Previous research (Aharoni et al., 2013, 2014) found that hemodynamic activity in the dorsal anterior cingulate cortex (dACC) during error monitoring predicted non-violent felony rearrest in men released from prison. This article reports an extension of the Aharoni et al. (2013, 2014) model in a sample of women released from state prison (n = 248). Replicating aspects of prior work, error monitoring activity in the dACC, as well as psychopathy scores and age at release, predicted non-violent felony rearrest in women. Sex differences in the directionality of dACC activity were observed-high error monitoring activity predicted rearrest in women, whereas prior work found low error monitoring activity predicted rearrest in men. As in prior analyses, the ability of the dACC to predict rearrest outcomes declines with more generalized outcomes (i.e., general felony). Implications for future research and clinical and forensic risk assessment are discussed., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Inc.)

Prosecutors can influence judges' sentencing decisions by the sentencing recommendations they make-but prosecutors are insulated from the costs of those sentences, which critics have described as a correctional "free lunch." In a nationally distributed survey experiment, we show that when a sample of ( n =178) professional prosecutors were insulated from sentencing cost information, their prison sentence recommendations were nearly one-third lengthier than sentences rendered following exposure to direct cost information. Exposure to a fiscally equivalent benefit of incarceration did not impact sentencing recommendations, as predicted. This pattern suggests that prosecutors implicitly value incorporating sentencing costs but selectively neglect them unless they are made explicit. These findings highlight a likely but previously unrecognized contributor to mass incarceration and identify a potential way to remediate it., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Aharoni, Kleider-Offutt and Brosnan.)

Competing Interests: Competing interests: KAJS: none. GM: none. DJK: none. EA: device design, employee of VisionCare Ophthalmic Technologies.

Do people punish more than they would if the decision costs were more transparent? In two Internet-based vignette experiments, we tested whether juvenile sentencing recommendations among U.S. adults are responsive to variation in the salience of the taxpayer costs and public safety benefits of incarceration. Using a 2 Cost (present vs. absent) x 2 Benefit (present vs. absent) factorial design, Experiment 1 (N = 234) found that exposure to information about the direct costs of incarcerating the juvenile offender reduced sentencing recommendations by about 28%, but exposure to the public safety benefits had no effect on sentences. Experiment 2 (N = 301) manipulated cost-benefit salience by asking participants to generate their own list of costs of incarceration, benefits of incarceration, or an affectively neutral, unrelated word list. Results revealed a similar selective effect whereby sentencing recommendations were reduced in the cost condition relative to the benefits and control conditions, but sentences in the benefit condition did not differ from the control. This combined pattern suggests that laypeople selectively neglect to factor cost considerations into these judgments, thereby inflating their support for punishment, unless those costs are made salient. These findings contribute to the debate on transparency in sentencing., Competing Interests: The authors have declared that no competing interests exist.

Legal theorists have characterized physical evidence of brain dysfunction as a double-edged sword, wherein the very quality that reduces the defendant's responsibility for his transgression could simultaneously increase motivations to punish him by virtue of his apparently increased dangerousness. However, empirical evidence of this pattern has been elusive, perhaps owing to a heavy reliance on singular measures that fail to distinguish between plural, often competing internal motivations for punishment. The present study employed a test of the theorized double-edge pattern using a novel approach designed to separate such motivations. We asked a large sample of participants (N = 330) to render criminal sentencing judgments under varying conditions of the defendant's mental health status (Healthy, Neurobiological Disorder, Psychological Disorder) and the disorder's treatability (Treatable, Untreatable). As predicted, neurobiological evidence simultaneously elicited shorter prison sentences (i.e., mitigating) and longer terms of involuntary hospitalization (i.e., aggravating) than equivalent psychological evidence. However, these effects were not well explained by motivations to restore treatable defendants to health or to protect society from dangerous persons but instead by deontological motivations pertaining to the defendant's level of deservingness and possible obligation to provide medical care. This is the first study of its kind to quantitatively demonstrate the paradoxical effect of neuroscientific trial evidence and raises implications for how such evidence is presented and evaluated., Competing Interests: The authors have declared that no competing interests exist.

Age is one of the best predictors of antisocial behavior. Risk models of recidivism often combine chronological age with demographic, social and psychological features to aid in judicial decision-making. Here we use independent component analyses (ICA) and machine learning techniques to demonstrate the utility of using brain-based measures of cerebral aging to predict recidivism. First, we developed a brain-age model that predicts chronological age based on structural MRI data from incarcerated males ( n  = 1332). We then test the model's ability to predict recidivism in a new sample of offenders with longitudinal outcome data ( n  = 93). Consistent with hypotheses, inclusion of brain-age measures of the inferior frontal cortex and anterior-medial temporal lobes (i.e., amygdala) improved prediction models when compared with models using chronological age; and models that combined psychological, behavioral, and neuroimaging measures provided the most robust prediction of recidivism. These results verify the utility of brain measures in predicting future behavior, and suggest that brain-based data may more precisely account for important variation when compared with traditional proxy measures such as chronological age. This work also identifies new brain systems that contribute to recidivism which has clinical implications for treatment development.

Rearrest has been predicted by hemodynamic activity in the anterior cingulate cortex (ACC) during error-processing (Aharoni et al., 2013). Here, we evaluate the predictive power after adding an additional imaging modality in a subsample of 45 incarcerated males from Aharoni et al. (2013). Event-related potentials (ERPs) and hemodynamic activity were collected during a Go/NoGo response inhibition task. Neural measures of error-processing were obtained from the ACC and two ERP components, the error-related negativity (ERN/Ne) and the error positivity (Pe). Measures from the Pe and ACC differentiated individuals who were and were not subsequently rearrested. Cox regression, logistic regression, and support vector machine (SVM) neuroprediction models were calculated. Each of these models proved successful in predicting rearrest and SVM provided the strongest results. Multimodal neuroprediction SVM models with out of sample cross-validating accurately predicted rearrest (83.33%). Offenders with increased Pe amplitude and decreased ACC activation, suggesting abnormal error-processing, were at greatest risk of rearrest.

This article reviews the scientific literature on the epidemiology, prevention, and treatment of problematic Internet use (PIU) with the goal of informing Air Force policies aimed at mitigating PIU's negative impact on operations and the mental health of Airmen. The study is motivated by a recent RAND study estimating that 6 percent of Airmen have PIU. Individuals with PIU, similar to people with substance addictions, suffer from excessive and compulsive online activities, symptoms of tolerance and withdrawal, and functional impairment. PIU is also strongly associated with other mental health problems including major depression. However, at present there is no single accepted definition of PIU, and no up-to-date estimates of the prevalence of PIU in the general U.S. population are available. A range of prevention and treatment approaches have been developed, but none has been rigorously tested in clinical trials. Prevention programs rely on workplace Internet policies and strategies to help individuals self-regulate their Internet use. Treatment approaches that have proven feasible and acceptable to patients with PIU include adaptations of cognitive-behavioral therapy, an evidence-based treatment for depression and anxiety, to the specific symptoms of PIU. Based on our findings, we recommend: (1) increasing awareness of PIU among organizational leadership and mental health professionals, (2) incorporating content related to PIU into existing trainings related to mental health, (3) providing support for self-regulation of Internet use on the job by incorporating PIU management principles into Internet use policies, and (4) continuing monitoring of the emerging scientific literature on PIU.

Identification of factors that predict recurrent antisocial behavior is integral to the social sciences, criminal justice procedures, and the effective treatment of high-risk individuals. Here we show that error-related brain activity elicited during performance of an inhibitory task prospectively predicted subsequent rearrest among adult offenders within 4 y of release (N = 96). The odds that an offender with relatively low anterior cingulate activity would be rearrested were approximately double that of an offender with high activity in this region, holding constant other observed risk factors. These results suggest a potential neurocognitive biomarker for persistent antisocial behavior.

Motivation: Optimizing HIV therapies is crucial since the virus rapidly develops mutations to evade drug pressure. Recent studies have shown that genotypic information might not be sufficient for the design of therapies and that other clinical and demographical factors may play a role in therapy failure. This study is designed to assess the improvement in prediction achieved when such information is taken into account. We use these factors to generate a prediction engine using a variety of machine learning methods and to determine which clinical conditions are most misleading in terms of predicting the outcome of a therapy., Results: Three different machine learning techniques were used: generative-discriminative method, regression with derived evolutionary features, and regression with a mixture of effects. All three methods had similar performances with an area under the receiver operating characteristic curve (AUC) of 0.77. A set of three similar engines limited to genotypic information only achieved an AUC of 0.75. A straightforward combination of the three engines consistently improves the prediction, with significantly better prediction when the full set of features is employed. The combined engine improves on predictions obtained from an online state-of-the-art resistance interpretation system. Moreover, engines tend to disagree more on the outcome of failure therapies than regarding successful ones. Careful analysis of the differences between the engines revealed those mutations and drugs most closely associated with uncertainty of the therapy outcome., Availability: The combined prediction engine will be available from July 2008, see http://engine.euresist.org.