Researchers from the Veteran's Health Administration, Academia, and Adaptive Testing Technologies Validate the Computerized Adaptive Test Suicide Scale (CAT-SS) for U.S. Military Veterans

CHICAGO, Jan. 25, 2022 /PRNewswire/ -- A promising new research study published today in the Public Library of Science (PLOS) ONE demonstrates that a newly developed computerized adaptive assessment for suicide risk severity can be used among military veterans to accurately predict suicidal outcomes at baseline and at 6- and 12-month marks.

Based on research conducted at the Veterans Health Administration by study lead author, Lisa Brenner, Ph.D., Director, Veterans Affairs Rocky Mountain MIRECC, Rocky Mountain Regional Medical Center Aurora, CO, Vice Chair of Research, Physical Medicine and Rehabilitation (PM&R), Professor of PM&R, Psychiatry, & Neurology, University of Colorado and Robert Gibbons, Ph.D., Blum-Riese Professor at the University of Chicago, the Computerized Adaptive Testing (CAT-SS) assessment tool, developed by Adaptive Testing Technologies, demonstrated added value over current suicide risk prediction practices in predicting future suicidal ideation and behavior. Specifically:  

• Unlike current tools, it draws from a much larger set of symptomatology that includes depression and anxiety symptoms that are precursors to the development of suicidal ideation and behavior. 
• CAT-SS scores outperformed history of suicide attempt in the past year as a predictor of future suicide-related thoughts and behaviors.

Computerized Adaptive Test-Suicide Scale (CAT-SS)^1* is an adaptive measure, comprised of 111-items, which dimensionally measures suicide risk severity on a 100-point scale with 5 points of precision. The scores are also thresholded to yield categories of low, moderate, and high risk.

In the United States, suicide rates are rising among military personnel, Veterans, and civilians. In fact, according to the National Veteran Suicide Prevention Annual Report, the veteran suicide rate rose from 23.3 to 31.6 suicides per 100,000 and the non-Veteran rate rose from 12.6 to 16.8 between 2001 and 2019.² According to work by Ahmedani, nearly 30% of individuals who die by suicide had a healthcare visit within the previous week, and therefore could have been screened for suicide risk.

While additional work is required to evaluate where the CAT-SS could be implemented in clinical settings, study findings suggest that if implemented in the electronic medical record, the CAT-SS would be expected to rapidly facilitate precise and personalized screening and assessment of suicide risk severity. Specifically:  

• The baseline CAT-SS demonstrated predictive accuracy for all outcomes at 6-months, and similar results were found for baseline and all outcomes at and through 12-months.
• The CAT-SS measured suicide risk severity using an average of 10 items in under 2 minutes.
• Analysis showed that for every 10-point change in the CAT-SS there was a 50-77% increase in the likelihood of suicide-related outcomes (outcomes were active ideation with plan and intent; attempt; interrupted, aborted or self -interrupted attempt, or preparatory acts or beaviors; and all outcomes combined).
• The clinical gold standard for predicting future suicidal ideation and behavior is a prior suicide attempt in the past year. The CAT-SS outperformed this gold standard for all suicide outcome measures in terms of predictive accuracy. 

Adaptive Testing Technologies' Computerized Adaptive Diagnostic (CAD) and Computerized Adaptive Testing (CAT-MH™) assessment tools, including the CAT-SS tool, are based on algorithms and research validated over 20+ years by Robert Gibbons, Ph.D., Blum-Riese Professor at the University of Chicago. They are validated for use with a variety of mental health conditions, including PTSD, depression, anxiety, mania, psychosis, substance use disorder, suicidality, ADHD, and assess Social Determinants of Health. They use a unique algorithm based on multidimensional item response theory and machine learning to adaptively select an optimal set of questions for each person, tailored to that person's level of severity at that point in time, thereby increasing the precision of measurement and accuracy of diagnosis. The tests are cloud-based, HIPAA compliant, administered remotely or on-site, self-guided, and can easily be integrated into electronic health records for immediate review by health care providers. 

The same group of researchers published another study in July 2021 in The Journal of the American Medical Association (JAMA) Network Open, demonstrating that two newly developed computerized adaptive post-traumatic stress disorder (PTSD) assessment tools - CAD-PTSD and CAT-PTSD - were equal to or outperformed diagnostic accuracy of standard tests and significantly reduced patient and clinician burden among military Veterans.

"To address the pressing public health problem of suicide, efforts must be aimed at validating measures that can be used to evaluate suicide risk in both primary and specialty care medical settings; can be rapidly administered via an electronic platform; and be personalized to individual patients," said Professor Gibbons. "Among Veterans seeking care at a VAMC, the CAT-SS assessed suicide risk severity with a median of 11 items in under two minutes. We believe this is enormously important for our nation's public health and the health of our Veterans and active military. The future of mental health measurement will be based on adaptive screening and measurement to provide more accurate diagnoses and severity measurements that benefit patients, their providers, and the overall health care system."

About the Study 

The study included 305 military veterans who completed the CAT-SS, the Columbia-Suicide Severity Rating Scale (C-SRSS), a clinician-administered interview used to evaluate suicidal ideation (including intensity) and suicide-related behavior, the Structured Clinical Interview for DSM-5 Disorders (SCID-5) Research Version, a valid semi-structured interview used to diagnose Axis I psychiatric disorders in clinical and research settings, and the Rocky Mountain MIRECC Demographic Questionnaire, a survey used to gather demographic information. All measures were administered at baseline, and again at 6- and 12-month appointments.

About Adaptive Testing Technologies  

Adaptive Testing Technologies (ATT) is the leader in the design, testing, and implementation of large-scale, cloud-based mental health assessment tools based on Computerized Adaptive Testing (CAT) and Computerized Adaptive Diagnostic (CAD) technologies. These tools are utilized by health professionals to assess a variety of mental health conditions – including depression, anxiety, mania, psychosis, PTSD, substance use disorder, suicide risk, ADHD, and assess Social Determinants of Health. The CAT-MH™ and K-CAT® represent the first and only validated, comprehensive, multidimensional item-response-theory-based adaptive screening and measurement systems in the world.?They provide levels of precision and accuracy that is far beyond what can be achieved using traditional fixed-length mental health assessment scales and can be administered anywhere at any frequency, in or out of the clinic, to any sized population. ATT's tools are currently being utilized in emergency departments, psychiatric and primary care clinics, telemedicine, student health clinics, perinatal medicine clinics, child welfare settings, substance use disorder programs, federal and state mental health programs, employee assistance programs, and the judicial system. The tools are available worldwide and are currently being used in the United States, Canada, the United Kingdom, Sweden, India, and Chile. 

MEDIA CONTACT:           

Dawn Maniglia 
TogoRun 
[email protected]  
917.862.5444 

Hannah Wulczyn, MPA 
Adaptive Testing Technologies 
[email protected] 
312.878.6490, Ext. 505 

*Measures administered at baseline, and 6- and 12-month follow-up appointments

¹ Gibbons RD, Kupfer D, Frank E, Moore T, Beiser DG, Boudreaux ED. Development of a Computerized Adaptive Test Suicide Scale-The CAT-SS. J Clin Psychiatry. 2017;78(9):1376-82. Available from: https://doi.org/10.4088/JCP.16m10922

² 2021 National Veteran Suicide Prevention Annual Report. (n.d.). Retrieved December 20, 2021, from https://www.mentalhealth.va.gov/docs/data-sheets/2021/2021-National-Veteran-Suicide-Prevention-Annual-Report-FINAL-9-8-21.pdf 

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