Results tagged‘Method: Quantitative’

Accurate prediction of suicide risk is crucial for identifying patients with elevated risk burden, helping ensure these patients receive targeted care. The US Department of Veteran …

Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined …

Abstract: U.S. Air Force remotely piloted aircraft (USAF RPA) personnel face diverse stressors negatively affecting psychological health and military readiness. Prior research in …

Abstract: Due to the inherent nature of service in both military and medical careers, some veterans are drawn to medicine after completing military service. However, there are …

Abstract: Combat veterans suffer from elevated rates of posttraumatic stress disorder (PTSD), depression, and generalized anxiety relative to the general population and other …

Abstract: Context: In response to the opioid crisis, federal guidelines were implemented, including the Veterans Health Administration's (VA) Opioid Safety Initiative in 2013. The …

Abstract: Objective: The Charlson Comorbidity Index (CCI), the Elixhauser Comorbidity Index (ECI), and the Functional Comorbidity Index (FCI) are validated clinical measures of …

Abstract: Background: Annually, thousands of Veterans file Department of Veterans Affairs' (VA) disability claims (“service connection”) for posttraumatic stress disorder …

Abstract: Background: Females are the fastest-growing group in the veteran population, yet there is a paucity in the literature of sex-specific Results: from studies of chronic …

Abstract: Objectives: To observe whether Veterans with spinal cord injury (SCI) are receiving appropriate dental care, and if not, what the barriers are. Design: At a single …