Improving risk prediction accuracy for new soldiers in the U.S. Army by adding self-report survey data to administrative data

BMC Psychiatry

Volumn 18, Issue 1, 2018, Pages

  Bernecker, Samantha L ^a,b   Rosellini, Anthony J ^c   Nock, Matthew K ^a   Chiu, Wai Tat ^b   Gutierrez, Peter M ^d   Hwang, Irving ^b   Joiner, Thomas E ^e   Naifeh, James A ^f   Sampson, Nancy A ^b   Zaslavsky, Alan M ^b   Stein, Murray B ^g   Ursano, Robert J ^f   Kessler, Ronald C ^b  

^a HARVARD UNIVERSITY   (United States)

^b HARVARD MEDICAL SCHOOL   (United States)

^c BOSTON UNIVERSITY   (United States)

^d UNIVERSITY OF COLORADO SCHOOL OF MEDICINE   (United States)

^e FLORIDA STATE UNIVERSITY   (United States)

^f UNIFORMED SERVICES UNIVERSITY OF THE HEALTH SCIENCES   (United States)

^g UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Army; Military; Predictive modeling; Risk assessment; Sexual assault; Violence

Indexed keywords

ADULT; ARMY; ARTICLE; CLINICAL ASSESSMENT; FEMALE; HUMAN; HUMAN EXPERIMENT; MACHINE LEARNING; MALE; PHYSICAL VIOLENCE; PREDICTION; RISK ASSESSMENT; RISK FACTOR; SELF REPORT; SEXUAL ASSAULT; SURVIVAL ANALYSIS; CRIME VICTIM; MENTAL DISEASE; METHODOLOGY; PROCEDURES; PSYCHOLOGY; SEXUAL CRIME; SOLDIER; STATISTICS AND NUMERICAL DATA; SUICIDE; UNITED STATES; YOUNG ADULT;

ADULT; CRIME VICTIMS; FEMALE; HUMANS; MALE; MENTAL DISORDERS; MILITARY PERSONNEL; RESEARCH DESIGN; RISK ASSESSMENT; RISK FACTORS; SELF REPORT; SEX OFFENSES; SUICIDE; UNITED STATES; YOUNG ADULT;

EID: 85044843399     PISSN: None     EISSN: 1471244X     Source Type: Journal    
DOI: 10.1186/s12888-018-1656-4     Document Type: Article

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