Protective mechanisms and prevention of violence and aggression in veterans.

Elbogen, Eric B.; Johnson, Sally C.; Newton, Virginia M.; Timko, Christine; Vasterling, Jennifer J.; Male, Lynn M. Van; Wagner, H. Ryan; Beckham, Jean C.

doi:10.1037/a0035088

Cited by 24 publications

(16 citation statements)

References 69 publications

(130 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…At the same time, empirical studies have determined that greater resilience is associated with reduced odds of both suicidality (Pietrzak, Russo, Ling, & Southwick, 2011; Youssef, Green, Beckham, & Elbogen, 2013) and violence (Elbogen et al, 2014b) in Iraq/Afghanistan-era veterans. Such findings are consistent with theoretical models of traumatic stress and “adaptive coping processes” which posit that there are psychological mechanisms of resilience by which individuals are able to recover from traumatic events and experiences (Agaibi & Wilson, 2005; Folkman, 1997; Yehuda et al, 2015).…”

mentioning

confidence: 99%

Risk factors for concurrent suicidal ideation and violent impulses in military veterans.

Elbogen¹,

Wagner²,

Kimbrel³

et al. 2018

Psychological Assessment

Self Cite

View full text Add to dashboard Cite

Suicide and violence are significant problems in a subset of Iraq/Afghanistan-era veterans. This study investigates how posttraumatic stress disorder (PTSD) and resilience in veterans are associated with suicidal ideation and violent impulses while controlling for known covariates of both adverse outcomes. Structured clinical interviews were conducted of N = 2,543 Iraq/Afghanistan-era U.S. veterans. Compared with veterans denying suicidal ideation or violent impulses (n = 1,927), veterans endorsing both (n = 171) were more likely to meet diagnostic criteria for PTSD, report childhood abuse, combat exposure, physical pain symptoms, and drug misuse, and less likely to endorse self-direction/life purpose. Veterans reporting concurrent suicidal ideation and violent impulses had higher odds of misusing drugs and reporting pain symptoms relative to veterans reporting suicidal ideation only (n = 186) and had lower odds of endorsing self-direction/life purpose compared with veterans reporting violent impulses only (n = 259). The findings underscore the importance of examining drug abuse, physical pain symptoms, and self-direction/life purpose, as well as PTSD and history of trauma, in the context of clinical assessment and empirical research aimed at optimizing risk management of suicide and violence in military veterans. (PsycINFO Database Record

show abstract

mentioning

confidence: 99%

Risk factors for concurrent suicidal ideation and violent impulses in military veterans.

Elbogen¹,

Wagner²,

Kimbrel³

et al. 2018

Psychological Assessment

Self Cite

View full text Add to dashboard Cite

show abstract

“…Scores could range from 0–100. The CD-RISC has demonstrated good psychometric properties (Connor & Davidson, 2003), and it has frequently been used in research with veterans (Elbogen et al, 2014a; Green, Beckham, Youssef, & Elbogen, 2013; Green et al, 2010; Green et al, 2014; Pietrzak, Goldstein, Malley, Rivers, & Southwick, 2010; Pietrzak & Southwick, 2011). In the current sample, Cronbach’s alpha was 0.96 for Wave 1 and 0.97 for Wave 2.…”

Section: Methodsmentioning

confidence: 99%

Effects of social support and resilient coping on violent behavior in military veterans.

Voorhees¹,

Wagner²,

Beckham³

et al. 2018

Psychological Services

Self Cite

View full text Add to dashboard Cite

Violence toward others has been identified as a serious postdeployment adjustment problem in a subset of Iraq- and Afghanistan-era veterans. In the current study, we examined the intricate links between posttraumatic stress disorder (PTSD), commonly cited psychosocial risk and protective factors, and violent behavior using a national randomly selected longitudinal sample of Iraq- and Afghanistan-era United States veterans. A total of 1,090 veterans from the 50 United States and all United States military branches completed 2 waves of self-report survey-data collection 1 year apart (retention rate = 79%). History of severe violent behavior at Wave 1 was the most substantial predictor of subsequent violence. In bivariate analyses, high correlations were observed among risk and protective factors, and between risk and protective factors and severe violence at both time points. In multivariate analyses, baseline violence (OR = 12.43, p < .001), baseline alcohol misuse (OR = 1.06, p < .05), increases in PTSD symptoms between Waves 1 and 2 (OR = 1.01, p < .05), and decreases in social support between Waves 1 and 2 (OR = .83, p < .05) were associated with increased risk for violence at Wave 2. Our findings suggest that rather than focusing specifically on PTSD symptoms, alcohol use, resilience, or social support in isolation, it may be more useful to consider how these risk and protective factors work in combination to convey how military personnel and veterans are managing the transition from wartime military service to civilian life, and at what point it might be most effective to intervene. (PsycINFO Database Record

show abstract

“…Such social impairments can result from compromised reward evaluations where the motivation for maintaining healthy relationships are persistently diminished 8 . As such, the treatment of maladaptive social behaviour presents an important strategy for improving mental health [9][10][11][12] . However, despite the established role of social behaviour in psychiatric disorders and treatments, it remains unclear how social context interact with biological functions to produce protracted and chronic sequalae 10 .…”

Section: Introductionmentioning

confidence: 99%

Simple Behavioral Analysis (SimBA) – an open source toolkit for computer classification of complex social behaviors in experimental animals

Nilsson

Goodwin

Choong

et al. 2020

Preprint

194

191

View full text Add to dashboard Cite

Aberrant social behavior is a core feature of many neuropsychiatric disorders, yet the study of complex social behavior in freely moving rodents is relatively infrequently incorporated into preclinical models. This likely contributes to limited translational impact. A major bottleneck for the adoption of socially complex, ethology-rich, preclinical procedures are the technical limitations for consistently annotating detailed behavioral repertoires of rodent social behavior. Manual annotation is subjective, prone to observer drift, and extremely time-intensive. Commercial approaches are expensive and inferior to manual annotation. Open-source alternatives often require significant investments in specialized hardware and significant computational and programming knowledge. By combining recent computational advances in convolutional neural networks and pose-estimation with further machine learning analysis, complex rodent social behavior is primed for inclusion under the umbrella of computational neuroethology.Here we present an open-source package with graphical interface and workflow (Simple Behavioral Analysis, SimBA) that uses pose-estimation to create supervised machine learning predictive classifiers of rodent social behavior, with millisecond resolution and accuracies that can out-perform human observers. SimBA does not require specialized video acquisition hardware nor extensive computational background. Standard descriptive statistical analysis, along with graphical region of interest annotation, are provided in addition to predictive classifier generation. To increase ease-of-use for behavioural neuroscientists, we designed SimBA with accessible menus for pre-processing videos, annotating behavioural training datasets, selecting advanced machine learning options, robust classifier validation functions and flexible visualizations tools. This allows for predictive classifier transparency, explainability and tunability prior to, and during, experimental use. We demonstrate that this approach is flexible and robust in both mice and rats by classifying social behaviors that are commonly central to the study of brain function and social motivation. Finally, we provide a library of poseestimation weights and behavioral predictive classifiers for resident-intruder behaviors in mice and rats. All code and data, together with detailed tutorials and documentation, are available on the SimBA GitHub repository.Graphical abstractSimBA graphical interface (GUI) for creating supervised machine learning classifiers of rodent social behavior.(a) Pre-process videos. SimBA supports common video pre-processing functions (e.g., cropping, clipping, sampling, format conversion, etc.) that can be performed either on single videos, or as a batch.(b) Managing poseestimation data and creating classification projects. Pose-estimation tracking projects in DeepLabCut and DeepPoseKit can be either imported or created and managed within the SimBA graphical user interface, and the tracking results are imported into SimBA classification projects.SimBA also supports userdrawn region-of-interests (ROIs) for descriptive statistics of animal movements, or as features in machine learning classification projects.(c) Create classifiers, perform classifications, and analyze classification data. SimBA has graphical tools for correcting poseestimation tracking inaccuracies when multiple subjects are within a single frame, annotating behavioral events from videos, and optimizing machine learning hyperparameters and discrimination thresholds. A number of validation checkpoints and logs are included for increased classifier explainability and tunability prior to, and during, experimental use. Both detailed and summary data are provided at the end of classifier analysis. SimBA accepts behavioral annotations generated elsewhere (such as through JWatcher) that can be imported into SimBA classification projects.(d) Visualize classification results. SimBA has several options for visualizing machine learning classifications, animal movements and ROI data, and analyzing the durations and frequencies of classified behaviors.See the SimBA GitHub repository for a comprehensive documentation and user tutorials.

show abstract

Protective mechanisms and prevention of violence and aggression in veterans.

Cited by 24 publications

References 69 publications

Risk factors for concurrent suicidal ideation and violent impulses in military veterans.

Risk factors for concurrent suicidal ideation and violent impulses in military veterans.

Effects of social support and resilient coping on violent behavior in military veterans.

Simple Behavioral Analysis (SimBA) – an open source toolkit for computer classification of complex social behaviors in experimental animals

Contact Info

Product

Resources

About