Using self-report surveys at the beginning of service to develop multi-outcome risk models for new soldiers in the U.S. Army
The U.S. Army uses universal preventives interventions for several negative outcomes (e.g. suicide, violence, sexual assault) with especially high risks in the early years of service. More intensive interventions exist, but would be cost-effective only if targeted at high-risk soldiers. We report re...
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Veröffentlicht in: | Psychological medicine 2017-10, Vol.47 (13), p.2275-2287 |
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creator | Rosellini, A. J. Stein, M. B. Benedek, D. M. Bliese, P. D. Chiu, W. T. Hwang, I. Monahan, J. Nock, M. K. Petukhova, M. V. Sampson, N. A. Street, A. E. Zaslavsky, A. M. Ursano, R. J. Kessler, R.C. |
description | The U.S. Army uses universal preventives interventions for several negative outcomes (e.g. suicide, violence, sexual assault) with especially high risks in the early years of service. More intensive interventions exist, but would be cost-effective only if targeted at high-risk soldiers. We report results of efforts to develop models for such targeting from self-report surveys administered at the beginning of Army service.
21 832 new soldiers completed a self-administered questionnaire (SAQ) in 2011-2012 and consented to link administrative data to SAQ responses. Penalized regression models were developed for 12 administratively-recorded outcomes occurring by December 2013: suicide attempt, mental hospitalization, positive drug test, traumatic brain injury (TBI), other severe injury, several types of violence perpetration and victimization, demotion, and attrition.
The best-performing models were for TBI (AUC = 0.80), major physical violence perpetration (AUC = 0.78), sexual assault perpetration (AUC = 0.78), and suicide attempt (AUC = 0.74). Although predicted risk scores were significantly correlated across outcomes, prediction was not improved by including risk scores for other outcomes in models. Of particular note: 40.5% of suicide attempts occurred among the 10% of new soldiers with highest predicted risk, 57.2% of male sexual assault perpetrations among the 15% with highest predicted risk, and 35.5% of female sexual assault victimizations among the 10% with highest predicted risk.
Data collected at the beginning of service in self-report surveys could be used to develop risk models that define small proportions of new soldiers accounting for high proportions of negative outcomes over the first few years of service. |
doi_str_mv | 10.1017/S003329171700071X |
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21 832 new soldiers completed a self-administered questionnaire (SAQ) in 2011-2012 and consented to link administrative data to SAQ responses. Penalized regression models were developed for 12 administratively-recorded outcomes occurring by December 2013: suicide attempt, mental hospitalization, positive drug test, traumatic brain injury (TBI), other severe injury, several types of violence perpetration and victimization, demotion, and attrition.
The best-performing models were for TBI (AUC = 0.80), major physical violence perpetration (AUC = 0.78), sexual assault perpetration (AUC = 0.78), and suicide attempt (AUC = 0.74). Although predicted risk scores were significantly correlated across outcomes, prediction was not improved by including risk scores for other outcomes in models. Of particular note: 40.5% of suicide attempts occurred among the 10% of new soldiers with highest predicted risk, 57.2% of male sexual assault perpetrations among the 15% with highest predicted risk, and 35.5% of female sexual assault victimizations among the 10% with highest predicted risk.
Data collected at the beginning of service in self-report surveys could be used to develop risk models that define small proportions of new soldiers accounting for high proportions of negative outcomes over the first few years of service.</description><identifier>ISSN: 0033-2917</identifier><identifier>EISSN: 1469-8978</identifier><identifier>DOI: 10.1017/S003329171700071X</identifier><identifier>PMID: 28374665</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject><![CDATA[Adolescent ; Adult ; Aggression ; Archives & records ; Armed forces ; Army ; Attrition ; Classification ; Consent ; Cost analysis ; Crime Victims - statistics & numerical data ; Demotion ; Drug abuse ; Early intervention ; Female ; Follow-Up Studies ; Health care policy ; Health Surveys - statistics & numerical data ; High risk ; Hospitalization ; Humans ; Intensive care ; Intensive treatment ; Male ; Medicine ; Mental Disorders - epidemiology ; Military personnel ; Military Personnel - statistics & numerical data ; Models, Statistical ; Original Articles ; Physical Abuse - statistics & numerical data ; Polls & surveys ; Prevention ; Prognosis ; Psychiatry ; Regression analysis ; Risk Assessment - methods ; Risk factors ; Self Report ; Sex crimes ; Sex Offenses - statistics & numerical data ; Soldiers ; Suicide ; Suicide, Attempted - statistics & numerical data ; Suicides & suicide attempts ; Survival analysis ; Trauma ; Traumatic brain injury ; United States - epidemiology ; Victimization ; Victims of crime ; Violence ; Violent crime ; Young Adult]]></subject><ispartof>Psychological medicine, 2017-10, Vol.47 (13), p.2275-2287</ispartof><rights>Copyright © Cambridge University Press 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c504t-7f257fb9df32e5d0a52a5d016689a42346a085f8283b8538c8c9e0e30599408e3</citedby><cites>FETCH-LOGICAL-c504t-7f257fb9df32e5d0a52a5d016689a42346a085f8283b8538c8c9e0e30599408e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S003329171700071X/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,230,314,776,780,881,12825,27901,27902,30976,55603</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28374665$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rosellini, A. J.</creatorcontrib><creatorcontrib>Stein, M. B.</creatorcontrib><creatorcontrib>Benedek, D. M.</creatorcontrib><creatorcontrib>Bliese, P. D.</creatorcontrib><creatorcontrib>Chiu, W. T.</creatorcontrib><creatorcontrib>Hwang, I.</creatorcontrib><creatorcontrib>Monahan, J.</creatorcontrib><creatorcontrib>Nock, M. K.</creatorcontrib><creatorcontrib>Petukhova, M. V.</creatorcontrib><creatorcontrib>Sampson, N. A.</creatorcontrib><creatorcontrib>Street, A. E.</creatorcontrib><creatorcontrib>Zaslavsky, A. M.</creatorcontrib><creatorcontrib>Ursano, R. J.</creatorcontrib><creatorcontrib>Kessler, R.C.</creatorcontrib><title>Using self-report surveys at the beginning of service to develop multi-outcome risk models for new soldiers in the U.S. Army</title><title>Psychological medicine</title><addtitle>Psychol. Med</addtitle><description>The U.S. Army uses universal preventives interventions for several negative outcomes (e.g. suicide, violence, sexual assault) with especially high risks in the early years of service. More intensive interventions exist, but would be cost-effective only if targeted at high-risk soldiers. We report results of efforts to develop models for such targeting from self-report surveys administered at the beginning of Army service.
21 832 new soldiers completed a self-administered questionnaire (SAQ) in 2011-2012 and consented to link administrative data to SAQ responses. Penalized regression models were developed for 12 administratively-recorded outcomes occurring by December 2013: suicide attempt, mental hospitalization, positive drug test, traumatic brain injury (TBI), other severe injury, several types of violence perpetration and victimization, demotion, and attrition.
The best-performing models were for TBI (AUC = 0.80), major physical violence perpetration (AUC = 0.78), sexual assault perpetration (AUC = 0.78), and suicide attempt (AUC = 0.74). Although predicted risk scores were significantly correlated across outcomes, prediction was not improved by including risk scores for other outcomes in models. Of particular note: 40.5% of suicide attempts occurred among the 10% of new soldiers with highest predicted risk, 57.2% of male sexual assault perpetrations among the 15% with highest predicted risk, and 35.5% of female sexual assault victimizations among the 10% with highest predicted risk.
Data collected at the beginning of service in self-report surveys could be used to develop risk models that define small proportions of new soldiers accounting for high proportions of negative outcomes over the first few years of service.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Aggression</subject><subject>Archives & records</subject><subject>Armed forces</subject><subject>Army</subject><subject>Attrition</subject><subject>Classification</subject><subject>Consent</subject><subject>Cost analysis</subject><subject>Crime Victims - statistics & numerical data</subject><subject>Demotion</subject><subject>Drug abuse</subject><subject>Early intervention</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Health care policy</subject><subject>Health Surveys - statistics & numerical data</subject><subject>High risk</subject><subject>Hospitalization</subject><subject>Humans</subject><subject>Intensive care</subject><subject>Intensive treatment</subject><subject>Male</subject><subject>Medicine</subject><subject>Mental Disorders - epidemiology</subject><subject>Military personnel</subject><subject>Military Personnel - statistics & numerical data</subject><subject>Models, Statistical</subject><subject>Original Articles</subject><subject>Physical Abuse - statistics & numerical data</subject><subject>Polls & surveys</subject><subject>Prevention</subject><subject>Prognosis</subject><subject>Psychiatry</subject><subject>Regression analysis</subject><subject>Risk Assessment - methods</subject><subject>Risk factors</subject><subject>Self Report</subject><subject>Sex crimes</subject><subject>Sex Offenses - statistics & numerical data</subject><subject>Soldiers</subject><subject>Suicide</subject><subject>Suicide, Attempted - statistics & numerical data</subject><subject>Suicides & suicide attempts</subject><subject>Survival analysis</subject><subject>Trauma</subject><subject>Traumatic brain injury</subject><subject>United States - epidemiology</subject><subject>Victimization</subject><subject>Victims of crime</subject><subject>Violence</subject><subject>Violent crime</subject><subject>Young Adult</subject><issn>0033-2917</issn><issn>1469-8978</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>7QJ</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kU9rFDEYh4Modq1-AC8S8OJl1mQy-XcRSrEqFHqoC95CZuadbepMsiaZlQU_fLN2La2lp_fwe94n-fEi9JaSJSVUfrwkhLFaU0klIUTSH8_QgjZCV0pL9Rwt9nG1z4_Qq5SuCaGMNvVLdFQrJhsh-AL9WSXn1zjBOFQRNiFmnOa4hV3CNuN8BbiFtfN-D4WhcHHrOsA54B62MIYNnuYxuyrMuQsT4OjSTzyFHsaEhxCxh984hbF3EBN2_q9xtbxc4pM47V6jF4MdE7w5zGO0Ovv8_fRrdX7x5dvpyXnVcdLkSg41l0Or-4HVwHtieW3LoEIobZuaNcISxQdVWrWKM9WpTgMBRrjWDVHAjtGnW-9mbifoO_A52tFsopts3JlgnXmYeHdl1mFruJBakroIPhwEMfyaIWUzudTBOFoPYU6GKtVQoRjlBX3_H3od5uhLPUM1k4IISVWh6C3VxZBShOHuM5SY_W3No9uWnXf3W9xt_DtmAdhBaqc2un4N995-UnsDVpqvJg</recordid><startdate>20171001</startdate><enddate>20171001</enddate><creator>Rosellini, A. 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J. ; Stein, M. B. ; Benedek, D. M. ; Bliese, P. D. ; Chiu, W. T. ; Hwang, I. ; Monahan, J. ; Nock, M. K. ; Petukhova, M. V. ; Sampson, N. A. ; Street, A. E. ; Zaslavsky, A. M. ; Ursano, R. 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J.</creatorcontrib><creatorcontrib>Kessler, R.C.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection【Remote access available】</collection><collection>ProQuest Central (Corporate)</collection><collection>Applied Social Sciences Index & Abstracts (ASSIA)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest - Health & Medical Complete保健、医学与药学数据库</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Sociology Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>ProQuest Psychology</collection><collection>ProQuest research library</collection><collection>Sociology Database (ProQuest)</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Psychological medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rosellini, A. J.</au><au>Stein, M. B.</au><au>Benedek, D. M.</au><au>Bliese, P. D.</au><au>Chiu, W. T.</au><au>Hwang, I.</au><au>Monahan, J.</au><au>Nock, M. K.</au><au>Petukhova, M. V.</au><au>Sampson, N. A.</au><au>Street, A. E.</au><au>Zaslavsky, A. M.</au><au>Ursano, R. J.</au><au>Kessler, R.C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using self-report surveys at the beginning of service to develop multi-outcome risk models for new soldiers in the U.S. Army</atitle><jtitle>Psychological medicine</jtitle><addtitle>Psychol. Med</addtitle><date>2017-10-01</date><risdate>2017</risdate><volume>47</volume><issue>13</issue><spage>2275</spage><epage>2287</epage><pages>2275-2287</pages><issn>0033-2917</issn><eissn>1469-8978</eissn><abstract>The U.S. Army uses universal preventives interventions for several negative outcomes (e.g. suicide, violence, sexual assault) with especially high risks in the early years of service. More intensive interventions exist, but would be cost-effective only if targeted at high-risk soldiers. We report results of efforts to develop models for such targeting from self-report surveys administered at the beginning of Army service.
21 832 new soldiers completed a self-administered questionnaire (SAQ) in 2011-2012 and consented to link administrative data to SAQ responses. Penalized regression models were developed for 12 administratively-recorded outcomes occurring by December 2013: suicide attempt, mental hospitalization, positive drug test, traumatic brain injury (TBI), other severe injury, several types of violence perpetration and victimization, demotion, and attrition.
The best-performing models were for TBI (AUC = 0.80), major physical violence perpetration (AUC = 0.78), sexual assault perpetration (AUC = 0.78), and suicide attempt (AUC = 0.74). Although predicted risk scores were significantly correlated across outcomes, prediction was not improved by including risk scores for other outcomes in models. Of particular note: 40.5% of suicide attempts occurred among the 10% of new soldiers with highest predicted risk, 57.2% of male sexual assault perpetrations among the 15% with highest predicted risk, and 35.5% of female sexual assault victimizations among the 10% with highest predicted risk.
Data collected at the beginning of service in self-report surveys could be used to develop risk models that define small proportions of new soldiers accounting for high proportions of negative outcomes over the first few years of service.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><pmid>28374665</pmid><doi>10.1017/S003329171700071X</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adolescent Adult Aggression Archives & records Armed forces Army Attrition Classification Consent Cost analysis Crime Victims - statistics & numerical data Demotion Drug abuse Early intervention Female Follow-Up Studies Health care policy Health Surveys - statistics & numerical data High risk Hospitalization Humans Intensive care Intensive treatment Male Medicine Mental Disorders - epidemiology Military personnel Military Personnel - statistics & numerical data Models, Statistical Original Articles Physical Abuse - statistics & numerical data Polls & surveys Prevention Prognosis Psychiatry Regression analysis Risk Assessment - methods Risk factors Self Report Sex crimes Sex Offenses - statistics & numerical data Soldiers Suicide Suicide, Attempted - statistics & numerical data Suicides & suicide attempts Survival analysis Trauma Traumatic brain injury United States - epidemiology Victimization Victims of crime Violence Violent crime Young Adult |
title | Using self-report surveys at the beginning of service to develop multi-outcome risk models for new soldiers in the U.S. Army |
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