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A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial 下载免费PDF全文
John P. Pestian PhD Michael Sorter MD Brian Connolly PhD Kevin Bretonnel Cohen PhD Cheryl McCullumsmith MD PhD Jeffry T. Gee MD Louis‐Philippe Morency PhD Stefan Scherer PhD Lesley Rohlfs MS the STM Research Group 《Suicide & life-threatening behavior》2017,47(1):112-121
Death by suicide demonstrates profound personal suffering and societal failure. While basic sciences provide the opportunity to understand biological markers related to suicide, computer science provides opportunities to understand suicide thought markers. In this novel prospective, multimodal, multicenter, mixed demographic study, we used machine learning to measure and fuse two classes of suicidal thought markers: verbal and nonverbal. Machine learning algorithms were used with the subjects’ words and vocal characteristics to classify 379 subjects recruited from two academic medical centers and a rural community hospital into one of three groups: suicidal, mentally ill but not suicidal, or controls. By combining linguistic and acoustic characteristics, subjects could be classified into one of the three groups with up to 85% accuracy. The results provide insight into how advanced technology can be used for suicide assessment and prevention. 相似文献
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Collin L. Davidson MS LaRicka R. Wingate PhD Meredith L. Slish MS Kathy A. Rasmus MS 《Suicide & life-threatening behavior》2010,40(2):170-180
Positive psychology has garnered considerable scholarly interest recently and has been suggested to hold promise in the application to suicide research and prevention; however, empirical research has lagged behind these suggestions. This is the first study to examine the relationship between hope and a specific theory of suicide in African Americans. It was hypothesized that (1) hope would negatively predict the interpersonal suicide risk factors of burdensomeness and thwarted belongingness; and positively predict acquired capability to enact suicide; (2) hope would negatively predict suicidal ideation; and (3) the interpersonal suicide risk factors would predict suicidal ideation. Results were primarily as predicted. Implications for hope theory and Joiner's theory of suicidal behavior are discussed, as well as implications for clinical practice. 相似文献
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Risk Factors,Warning Signs,and Drivers of Suicide: What Are They,How Do They Differ,and Why Does It Matter? 下载免费PDF全文
Raymond P. Tucker MS Kevin J. Crowley MA Collin L. Davidson PhD Peter M. Gutierrez PhD 《Suicide & life-threatening behavior》2015,45(6):679-689
Research investigating suicide attempts and deaths by suicide has yielded many specific risk factors and warning signs for future suicidal behaviors. Yet, even though these variables are each valuable for suicide prevention efforts, they may be limited in their applicability to clinical practice. The differences among risk factors, warning signs, and “drivers,” which are person‐specific variables that lead individuals to desire death by suicide, are highlighted. The scarce evidence on drivers is described and specific recommendations for conducting future drivers‐focused research and targeting them in clinical practice are suggested. 相似文献
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Measuring Associations of the Department of Veterans Affairs' Suicide Prevention Campaign on the Use of Crisis Support Services 下载免费PDF全文
Elizabeth Karras PhD Naiji Lu PhD Guoxin Zuo PhD Xin M. Tu PhD Brady Stephens MS John Draper PhD Caitlin Thompson PhD Robert M. Bossarte PhD 《Suicide & life-threatening behavior》2016,46(4):447-456
Campaigns have become popular in public health approaches to suicide prevention; however, limited empirical investigation of their impact on behavior has been conducted. To address this gap, utilization patterns of crisis support services associated with the Department of Veterans Affairs' Veterans Crisis Line (VCL) suicide prevention campaign were examined. Daily call data for the National Suicide Prevention Lifeline, VCL, and 1‐800‐SUICIDE were modeled using a novel semi‐varying coefficient method. Analyses reveal significant increases in call volume to both targeted and broad resources during the campaign. Findings underscore the need for further research to refine measurement of the effects of these suicide prevention efforts. 相似文献
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Ewa K. Czyz MS Amy S. B. Bohnert PhD Cheryl A. King PhD Amanda M. Price MS Felicia Kleinberg MSW Mark A. Ilgen PhD 《Suicide & life-threatening behavior》2014,44(6):698-709
Individuals with substance use disorders (SUDs) are at high risk of suicidal behaviors, highlighting the need for an improved understanding of potentially influential factors. One such domain is self‐efficacy to manage suicidal thoughts and impulses. Psychometric data about the Self‐Efficacy to Avoid Suicidal Action (SEASA) Scale within a sample of adults seeking SUD treatment (N = 464) is provided. Exploratory factor analysis supported a single self‐efficacy construct. Lower SEASA scores, or lower self‐efficacy, were reported in those with more severe suicidal ideation and those with more suicide attempts, providing evidence for convergent validity. Implications of measuring self‐efficacy in the context of suicide risk assessment are discussed. 相似文献
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Sarah A. Arias PhD Zi Zhang MD MPH Carla Hillerns Ashley F. Sullivan MS MPH Edwin D. Boudreaux PhD Ivan Miller PhD Carlos A. Camargo MD DrPH 《Suicide & life-threatening behavior》2014,44(5):537-547
Adverse event (AE) detection and reporting practices were compared during the first phase of the Emergency Department Safety Assessment and Follow‐up Evaluation (ED‐SAFE), a suicide intervention study. Data were collected using a combination of chart reviews and structured telephone follow‐up assessments postenrollment. Beyond chart reviews, structured telephone follow‐up assessments identified 45% of the total AEs in our study. Notably, detection of suicide attempts significantly varied by approach with 53 (18%) detected by chart review, 173 (59%) by structured telephone follow‐up assessments, and 69 (23%) marked as duplicates. Findings provide support for utilizing multiple methods for more robust AE detection in suicide research. 相似文献