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John Monahan

Bio: John Monahan is an academic researcher from University of Virginia. The author has contributed to research in topics: Poison control & Risk assessment. The author has an hindex of 72, co-authored 313 publications receiving 21833 citations. Previous affiliations of John Monahan include University of California, San Francisco & City University of New York.


Papers
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Journal ArticleDOI
TL;DR: Preventing suicides, mental disorders, and noncombat‐related interpersonal violence during deployment are priorities of the US Army and actuarial models are developed to identify soldiers at high risk of these outcomes during combat deployment.
Abstract: BACKGROUND Preventing suicides, mental disorders, and noncombat-related interpersonal violence during deployment are priorities of the US Army. We used predeployment survey and administrative data to develop actuarial models to identify soldiers at high risk of these outcomes during combat deployment. METHODS The models were developed in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) Pre-Post Deployment Study, a panel study of soldiers deployed to Afghanistan in 2012-2013. Soldiers completed self-administered questionnaires before deployment and one (T1), three (T2), and nine months (T3) after deployment, and consented to administrative data linkage. Seven during-deployment outcomes were operationalized using the postdeployment surveys. Two overlapping samples were used because some outcomes were assessed at T1 (n = 7,048) and others at T2-T3 (n = 7,081). Ensemble machine learning was used to develop a model for each outcome from 273 predeployment predictors, which were compared to simple logistic regression models. RESULTS The relative improvement in area under the receiver operating characteristic curve (AUC) obtained by machine learning compared to the logistic models ranged from 1.11 (major depression) to 1.83 (suicidality).The best-performing machine learning models were for major depression (AUC = 0.88), suicidality (0.86), and generalized anxiety disorder (0.85). Roughly 40% of these outcomes occurred among the 5% of soldiers with highest predicted risk. CONCLUSIONS Actuarial models could be used to identify high risk soldiers either for exclusion from deployment or preventive interventions. However, the ultimate value of this approach depends on the associated costs, competing risks (e.g. stigma), and the effectiveness to-be-determined interventions.

15 citations

Journal ArticleDOI
TL;DR: If a system is developed to consolidate administrative predictors routinely, then predictions could be generated periodically to identify those in need of preventive intervention, whether this would be cost effective, though, would depend on intervention costs, effectiveness, and competing risks.

14 citations

01 Jan 2016
TL;DR: In this article, the authors synthesize the existing evidence base on the individual risk assessment of terrorism, focusing critical attention on recent developments in the identification of valid risk factors, including ideologies, affiliations, grievances, moral emotions, and identities.
Abstract: This chapter synthesizes the existing evidence base on the individual risk assessment of terrorism, focusing critical attention on recent developments in the identification of valid risk factors. The most promising candidates for such risk factors identified here include ideologies, affiliations, grievances, moral emotions, and identities. Risk factors for lone-actor terrorism may diverge significantly from those for group-based terrorism. The chapter also reflects on what must happen if research on the risk assessment of terrorism is to yield knowledge that is actionable in the context of national security, i.e., the use of case-control, known-groups research designs.

14 citations

Posted Content
TL;DR: In this paper, the authors reconceptualize gatekeeping analysis in scientific evidence cases based on the nature of science itself, specifically, the division between general and case-specific scientific findings.
Abstract: Fundamental to all evidence rules is the division of responsibility between the judge, who determines the admissibility of evidence, and the jury, which gauges its weight. In most evidence contexts, such as hearsay and character, threshold admissibility obligations are clear and relatively uncontroversial. The same is not true for scientific evidence. The complex nature of scientific inference, and in particular the challenges of reasoning from group data to individual cases, has bedeviled courts. As a result, courts vary considerably on how they define the judge’s gatekeeping task under Federal Rule of Evidence 702 and its state equivalents. This article seeks to reconceptualize gatekeeping analysis in scientific evidence cases based on the nature of science itself, specifically, the division between general and case-specific scientific findings. Because expert testimony describing basic science, “framework” science, and the scientific methods an expert uses to reach his or her conclusions transcend the case-at-hand, the validity of these preliminary facts ought to be determined by the judge. In contrast, when an expert claims to have used a methodology approved by the judge but there is a dispute as to whether he or she in fact did so, the question becomes one of credibility specific to the case, and is for the jury. This division between general and case-specific preliminary facts is simpler to administer than other admissibility/weight frameworks, which have relied primarily on problematic attempts to distinguish scientific methods from scientific conclusions. It is also fully consistent with, and helps implement, basic principles of both constitutional and evidentiary jurisprudence by ensuring that the trial judge — presumptively better attuned to matters of general import — decides reliability issues, while the jury — historically viewed as trier of the facts — is the ultimate arbiter of those case-specific matters requiring a credibility assessment. Because the general-specific divide likewise argues for a stiff standard of appellate review on scientific reliability issues, our alignment of evidence law with the nature of scientific research also provides the best court-monitored mechanism for ensuring that courtroom use of science is both sophisticated and consistent across cases.

14 citations


Cited by
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Journal ArticleDOI
TL;DR: The purpose of this article is to serve as an introduction to ROC graphs and as a guide for using them in research.

17,017 citations

Book
01 Jul 2002
TL;DR: In this article, a review is presented of the book "Heuristics and Biases: The Psychology of Intuitive Judgment, edited by Thomas Gilovich, Dale Griffin, and Daniel Kahneman".
Abstract: A review is presented of the book “Heuristics and Biases: The Psychology of Intuitive Judgment,” edited by Thomas Gilovich, Dale Griffin, and Daniel Kahneman.

3,642 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the implica- tions of individual differences in performance for each of the four explanations of the normative/descriptive gap, including performance errors, computational limitations, the wrong norm being applied by the experi- menter, and a different construal of the task by the subject.
Abstract: Much research in the last two decades has demon- strated that human responses deviate from the performance deemed normative according to various models of decision mak- ing and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be inter- preted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational limitations, (3) the wrong norm being applied by the experi- menter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implica- tions of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance er- rors are a minor factor in the gap; computational limitations un- derlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Un- expected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate.

3,068 citations

Journal ArticleDOI
TL;DR: There is general support for the hypothesis that children with poor peer adjustment are at risk for later life difficulties, and support is clearest for the outcomes of dropping out and criminality.
Abstract: In this review, we examine the oft-made claim that peer-relationship difficulties in childhood predict serious adjustment problems in later life. The article begins with a framework for conceptualizing and assessing children's peer difficulties and with a discussion of conceptual and methodological issues in longitudinal risk research. Following this, three indexes of problematic peer relationships (acceptance, aggressiveness, and shyness/withdrawal) are evaluated as predictors of three later outcomes (dropping out of school, criminality, and psychcpathology). The relation between peer difficulties and later maladjustment is examined in terms of both the consistency and strength of prediction. A review and analysis of the literature indicates general support for the hypothesis that children with poor peer adjustment are at risk for later life difficulties. Support is clearest for the outcomes of dropping out and criminality. It is also clearest for low acceptance and aggressiveness as predictors, whereas a link between shyness/withdrawal and later maladjustment has not yet been adequately tested. The article concludes with a critical discussion of the implicit models that have guided past research in this area and a set of recommendations for the next generation of research on the risk

3,055 citations

Posted Content
TL;DR: This article addresses the important questions of how to infuse needed "doses of feeling" into circumstances where lack of experience may otherwise leave us too "coldly rational"?
Abstract: Modern theories in cognitive psychology and neuroscience indicate that there are two fundamental ways in which human beings comprehend risk. The analytic system uses algorithms and normative rules, such as probability calculus, formal logic, and risk assessment. It is relatively slow, effortful, and requires conscious control. The experiential system is intuitive, fast, mostly automatic, and not very accessible to conscious awareness. The experiential system enabled human beings to survive during their long period of evolution and remains today the most natural and most common way to respond to risk. It relies on images and associations, linked by experience to emotion and affect (a feeling that something is good or bad). This system represents risk as a feeling that tells us whether it's safe to walk down this dark street or drink this strange-smelling water. Proponents of formal risk analysis tend to view affective responses to risk as irrational. Current wisdom disputes this view. The rational and the experiential systems operate in parallel and each seems to depend on the other for guidance. Studies have demonstrated that analytic reasoning cannot be effective unless it is guided by emotion and affect. Rational decision making requires proper integration of both modes of thought. Both systems have their advantages, biases, and limitations. Now that we are beginning to understand the complex interplay between emotion and reason that is essential to rational behavior, the challenge before us is to think creatively about what this means for managing risk. On the one hand, how do we apply reason to temper the strong emotions engendered by some risk events? On the other hand, how do we infuse needed "doses of feeling" into circumstances where lack of experience may otherwise leave us too "coldly rational"? This article addresses these important questions.

3,046 citations