Both authors contributed to the conceptualization of the study, data collection and preparation. DSC analyzed the data and wrote the initial report, SJW provided critical revisions. AcknowledgmentsResearch reported in this publication was supported by the NIAAA under award K01AA026647 (PI: Chester).

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Psychopathic traits predispose individuals toward antisocial behavior. Such antagonistic acts often result in “unsuccessful” outcomes such as incarceration. What mechanisms allow some people with relatively high levels of psychopathic traits to live “successful”, unincarcerated lives, in spite of their antisocial tendencies? Using neuroimaging, we investigated the possibility that “successful” psychopathic individuals exhibited greater development of neural structures that promote “successful” self-regulation, focusing on the ventrolateral prefrontal cortex (VLPFC). Across two structural magnetic resonance imaging studies of “successful” participants (Study 1: N = 80 individuals in long-term romantic relationships; Study 2: N = 64 undergraduates), we observed that gray matter density in the left and right VLPFC was positively associated with psychopathic traits. These preliminary results support a compensatory model of psychopathy, in which “successful” psychopathic individuals develop inhibitory mechanisms to compensate for their antisocial tendencies. Traditional models of psychopathy that emphasize deficits may be aided by such compensatory models that identify surfeits in neural and psychological processes.

The overall reliability or evidentiary value of any body of literature is established in part by ruling out publication bias for any observed effects. Questionable research practices have potentially undermined the evidentiary value of commonly-used research paradigms in psychological science. Subsequently, the evidentiary value of these common methodologies remains uncertain. To quantify the severity of these issues in the literature, we selected the Taylor Aggression Paradigm (TAP) as a case study and submitted 170 hypothesis-tests spanning over 50 years of research to a preregistered p-curve analysis. The TAP literature (N = 24,685) demonstrated significant evidentiary value but yielded a small average effect size (d = .29) and inadequate power (38%). Main effects demonstrated greater evidentiary value, power, and effect sizes than interactions. Studies that tested the effects of measured traits did not differ in evidentiary value or power to those that tested the effects of experimentally-manipulated states. Exploratory analyses revealed that evidentiary value, statistical power, and effect sizes have improved over time. We provide recommendations for researchers who seek to maximize the evidentiary value of their psychological measures.

Statement: Our preregistered hypotheses and study protocol(s) are publicly available (https://osf.io/46pg7/wiki/), along with all de-identified data and code needed to reproduce our findings (https://osf.io/46pg7/files/).

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Traumatic brain injury (TBI) is often experienced under stressful circumstances that can lead to symptoms of posttraumatic stress disorder (PTSD) and neurobehavioral symptoms of brain injury. There is considerable symptom overlap in the behavioral expression of these conditions. Psychometric network analysis is a useful approach to investigate the role of specific symptoms in connecting these two disorders and is well-suited to explore their interrelatedness. This study applied network analysis to examine the associations among PTSD and TBI symptoms in a sample of Service Members and Veterans (SM/Vs) with a history of TBI one year after injury.Responses to the Neurobehavioral Symptom Inventory (NSI) and PTSD Checklist-Civilian version (PCL-C) were obtained from participants who completed comprehensive inpatient rehabilitation services across five VA polytrauma rehabilitation centers. Participants (N = 612) were 93.1% male with an average age of 36.98 years at injury. The analysis produced a stable network. Within the NSI symptom groups, the frustration symptom was an important bridge between the affective and cognitive TBI symptoms. The PCL-C nodes formed their own small cluster with hyperarousal yielding connections with the affective, cognitive, and somatic symptom groups. Consistent with this observation, the hyperarousal node had the second strongest bridge centrality in the network. Hyperarousal appears to play a key role in holding together this network of distress and thus represents a prime target for intervention among individuals with elevated symptoms of PTSD and a history of TBI. Network analysis offers an empirical approach to visualizing and quantifying the associations among symptoms. The identification of symptoms that are central to connecting multiple conditions can inform diagnostic precision and treatment selection.

The analyses in this manuscript constitute secondary data analysis as the datasets used were collected for other projects. However, our analysis plan for each dataset was preregistered (Sample 1: https://osf.io/3j4ya, Sample 2: https://osf.io/vuze8, Sample 3: https://osf.io/h9jr5), and is available along with all the code, data needed to replicate our findings, and supplemental documents (https://osf.io/kqxd5/files/).This manuscript is not currently under review or consideration at other publication outlets. We have no conflicts of interest to disclose. Research reported in this publication was supported by the NIAAA under award K01AA026647 (PI: Chester). All data collection procedures were subjected to and approved via ethical review.