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Zaslavsky, Alan

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Zaslavsky

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Alan

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Zaslavsky, Alan

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  • Publication

    Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports

    (2015) Kessler, Ronald; van Loo, Hanna M.; Wardenaar, Klaas J.; Bossarte, Robert M.; Brenner, Lisa A.; Cai, Tianxi; Ebert, David Daniel; Hwang, Irving; Li, Junlong; de Jonge, Peter; Nierenberg, Andrew; Petukhova, Maria; Rosellini, Anthony; Sampson, Nancy; Schoevers, Robert A.; Wilcox, Marsha A.; Zaslavsky, Alan

    Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. While efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine learning (ML) models developed from self-reports about incident episode characteristics and comorbidities among respondents with lifetime MDD in the World Health Organization World Mental Health (WMH) Surveys predicted MDD persistence, chronicity, and severity with good accuracy. We report results of model validation in an independent prospective national household sample of 1,056 respondents with lifetime MDD at baseline. The WMH ML models were applied to these baseline data to generate predicted outcome scores that were compared to observed scores assessed 10–12 years after baseline. ML model prediction accuracy was also compared to that of conventional logistic regression models. Area under the receiver operating characteristic curve (AUC) based on ML (.63 for high chronicity and .71–.76 for the other prospective outcomes) was consistently higher than for the logistic models (.62–.70) despite the latter models including more predictors. 34.6–38.1% of respondents with subsequent high persistence-chronicity and 40.8–55.8% with the severity indicators were in the top 20% of the baseline ML predicted risk distribution, while only 0.9% of respondents with subsequent hospitalizations and 1.5% with suicide attempts were in the lowest 20% of the ML predicted risk distribution. These results confirm that clinically useful MDD risk stratification models can be generated from baseline patient self-reports and that ML methods improve on conventional methods in developing such models.

  • Publication

    Associations of Housing Mobility Interventions for Children in High-Poverty Neighborhoods With Subsequent Mental Disorders During Adolescence

    (American Medical Association (AMA), 2014) Kessler, Ronald; Duncan, Greg J.; Gennetian, Lisa A.; Katz, Lawrence; Kling, Jeffrey R.; Sampson, Nancy; Sanbonmatsu, Lisa; Zaslavsky, Alan; Ludwig, Jens

    Importance Youth in high-poverty neighborhoods have high rates of emotional problems. Understanding neighborhood influences on mental health is crucial for designing neighborhood-level interventions.

    Objective To perform an exploratory analysis of associations between housing mobility interventions for children in high-poverty neighborhoods and subsequent mental disorders during adolescence.

    Design, Setting, and Participants The Moving to Opportunity Demonstration from 1994 to 1998 randomized 4604 volunteer public housing families with 3689 children in high-poverty neighborhoods into 1 of 2 housing mobility intervention groups (a low-poverty voucher group vs a traditional voucher group) or a control group. The low-poverty voucher group (n=1430) received vouchers to move to low-poverty neighborhoods with enhanced mobility counseling. The traditional voucher group (n=1081) received geographically unrestricted vouchers. Controls (n=1178) received no intervention. Follow-up evaluation was performed 10 to 15 years later (June 2008-April 2010) with participants aged 13 to 19 years (0-8 years at randomization). Response rates were 86.9% to 92.9%.

    Main Outcomes and Measures Presence of mental disorders from the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) within the past 12 months, including major depressive disorder, panic disorder, posttraumatic stress disorder (PTSD), oppositional-defiant disorder, intermittent explosive disorder, and conduct disorder, as assessed post hoc with a validated diagnostic interview.

    Results Of the 3689 adolescents randomized, 2872 were interviewed (1407 boys and 1465 girls). Compared with the control group, boys in the low-poverty voucher group had significantly increased rates of major depression (7.1% vs 3.5%; odds ratio (OR), 2.2 [95% CI, 1.2-3.9]), PTSD (6.2% vs 1.9%; OR, 3.4 [95% CI, 1.6-7.4]), and conduct disorder (6.4% vs 2.1%; OR, 3.1 [95% CI, 1.7-5.8]). Boys in the traditional voucher group had increased rates of PTSD compared with the control group (4.9% vs 1.9%, OR, 2.7 [95% CI, 1.2-5.8]). However, compared with the control group, girls in the traditional voucher group had decreased rates of major depression (6.5% vs 10.9%; OR, 0.6 [95% CI, 0.3-0.9]) and conduct disorder (0.3% vs 2.9%; OR, 0.1 [95% CI, 0.0-0.4]).

    Conclusions and Relevance Interventions to encourage moving out of high-poverty neighborhoods were associated with increased rates of depression, PTSD, and conduct disorder among boys and reduced rates of depression and conduct disorder among girls. Better understanding of interactions among individual, family, and neighborhood risk factors is needed to guide future public housing policy changes.

    Observational studies have consistently found that youth in high-poverty neighborhoods have high rates of emotional problems even after controlling for individual-level risk factors.1 These findings raise the possibilities that neighborhood characteristics affect emotional functioning2 and neighborhood-level interventions may reduce emotional problems. Available data from observational studies are unclear and subject to selection bias and the possibility of reverse causality (ie, families with emotional problems end up in poorer neighborhoods). Despite this uncertainty, presumptive neighborhood effects have been characterized,3 causal pathways have been hypothesized,4 and interventions have been implemented.5

    It is important to evaluate these causal claims regarding neighborhood effects experimentally. The US Department of Housing and Urban Development (HUD) enacted a housing mobility experiment known as the Moving to Opportunity for Fair Housing Demonstration by randomizing volunteer low-income public housing families with children to receive vouchers to move to lower-poverty neighborhoods.6,7 An interim evaluation 4 to 7 years after randomization showed that the intervention caused families to move to better neighborhoods with lower poverty and crime rates and increased social ties with more affluent people.8 Significant reductions in psychological distress and depression were also found among adolescent girls in the intervention group vs the control group but increased behavior problems were found among adolescent boys in the intervention group vs the control group.9- 11 Given the importance of these sex differences, clinically significant mental disorders were included in a long-term (10-15 years after randomization) follow-up assessment. Prior long-term follow-up reports documented effects on improved neighborhood characteristics,12,13 reduced adult extreme obesity and diabetes,14 and improved adult subjective well-being.13 No detectable effects on economic self-sufficiency were found.13 Although long-term evaluation found significantly reduced psychological distress among adolescent girls,15 measures of mental disorders were not examined in previous reports.

    The primary objectives of the Moving to Opportunity study were to move families to lower-poverty neighborhoods and increase educational achievement and economic self-sufficiency. Mental disorders were measured as post hoc outcomes. The current report presents the first exploratory analyses evaluating long-term associations of housing mobility randomization with mental disorders among participants who were in early childhood at randomization and adolescence at follow-up.

  • Publication

    Predicting Suicides After Psychiatric Hospitalization in US Army Soldiers

    (American Medical Association (AMA), 2015) Kessler, Ronald; Warner, Christopher H.; Ivany, Christopher; Petukhova, Maria; Rose, Sherri; Bromet, Evelyn J.; Brown, Millard; Cai, Tianxi; Colpe, Lisa J.; Cox, Kenneth L.; Fullerton, Carol S.; Gilman, Stephen Edward; Gruber, M; Heeringa, Steven G.; Lewandowski-Romps, Lisa; Li, Junlong; Millikan-Bell, Amy M.; Naifeh, James A.; Nock, Matthew K.; Rosellini, Anthony; Sampson, Nancy; Schoenbaum, Michael; Stein, Murray B.; Wessely, Simon; Zaslavsky, Alan; Ursano, Robert J.

    IMPORTANCE: The US Army experienced a sharp increase in soldier suicides beginning in 2004. Administrative data reveal that among those at highest risk are soldiers in the 12 months after inpatient treatment of a psychiatric disorder. OBJECTIVE: To develop an actuarial risk algorithm predicting suicide in the 12 months after US Army soldier inpatient treatment of a psychiatric disorder to target expanded posthospitalization care. DESIGN, SETTING, AND PARTICIPANTS: There were 53,769 hospitalizations of active duty soldiers from January 1, 2004, through December 31, 2009, with International Classification of Diseases, Ninth Revision, Clinical Modification psychiatric admission diagnoses. Administrative data available before hospital discharge abstracted from a wide range of data systems (sociodemographic, US Army career, criminal justice, and medical or pharmacy) were used to predict suicides in the subsequent 12 months using machine learning methods (regression trees and penalized regressions) designed to evaluate cross-validated linear, nonlinear, and interactive predictive associations. MAIN OUTCOMES AND MEASURES: Suicides of soldiers hospitalized with psychiatric disorders in the 12 months after hospital discharge. RESULTS: Sixty-eight soldiers died by suicide within 12 months of hospital discharge (12.0% of all US Army suicides), equivalent to 263.9 suicides per 100,000 person-years compared with 18.5 suicides per 100,000 person-years in the total US Army. The strongest predictors included sociodemographics (male sex [odds ratio (OR), 7.9; 95% CI, 1.9-32.6] and late age of enlistment [OR, 1.9; 95% CI, 1.0-3.5]), criminal offenses (verbal violence [OR, 2.2; 95% CI, 1.2-4.0] and weapons possession [OR, 5.6; 95% CI, 1.7-18.3]), prior suicidality [OR, 2.9; 95% CI, 1.7-4.9], aspects of prior psychiatric inpatient and outpatient treatment (eg, number of antidepressant prescriptions filled in the past 12 months [OR, 1.3; 95% CI, 1.1-1.7]), and disorders diagnosed during the focal hospitalizations (eg, nonaffective psychosis [OR, 2.9; 95% CI, 1.2-7.0]). A total of 52.9% of posthospitalization suicides occurred after the 5% of hospitalizations with highest predicted suicide risk (3824.1 suicides per 100,000 person-years). These highest-risk hospitalizations also accounted for significantly elevated proportions of several other adverse posthospitalization outcomes (unintentional injury deaths, suicide attempts, and subsequent hospitalizations). CONCLUSIONS AND RELEVANCE: The high concentration of risk of suicide and other adverse outcomes might justify targeting expanded posthospitalization interventions to soldiers classified as having highest posthospitalization suicide risk, although final determination requires careful consideration of intervention costs, comparative effectiveness, and possible adverse effects.

  • Publication

    Mental Disorders, Comorbidity, and Pre-enlistment Suicidal Behavior Among New Soldiers in the U.S. Army: Results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

    (Wiley-Blackwell, 2015) Nock, Matthew; Ursano, Robert J.; Heeringa, Steven G.; Stein, Murray B.; Jain, Sonia; Raman, Rema; Sun, Xiaoying; Chiu, Wai; Colpe, Lisa J.; Fullerton, Carol S.; Gilman, Stephen Edward; Hwang, Irving; Naifeh, James A.; Rosellini, Anthony; Sampson, Nancy; Schoenbaum, Michael; Zaslavsky, Alan; Kessler, Ronald

    We examined the associations between mental disorders and suicidal behavior (ideation, plans, and attempts) among new soldiers using data from the New Soldier Study (NSS) component of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS; n=38,507). Most new soldiers with a pre-enlistment history of suicide attempt reported a prior mental disorder (59.0%). Each disorder examined was associated with increased odds of suicidal behavior (ORs=2.6–8.6). Only PTSD and disorders characterized by irritability and impulsive/aggressive behavior (i.e., bipolar disorder, conduct disorder, oppositional defiant disorder, and attention-deficit/hyperactivity disorder) predicted unplanned attempts among ideators. Mental disorders are important predictors of pre-enlistment suicidal behavior among new soldiers and should figure prominently in suicide screening and prevention efforts.

  • Publication

    Prevalence and correlates of suicidal behavior among new soldiers in the US Army: results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

    (Wiley-Blackwell, 2014) Ursano, Robert J.; Heeringa, Steven G.; Stein, Murray B.; Jain, Sonia; Raman, Rema; Sun, Xiaoying; Chiu, Wai; Colpe, Lisa J.; Fullerton, Carol S.; Gilman, Stephen Edward; Hwang, Irving; Naifeh, James A.; Nock, Matthew; Rosellini, Anthony; Sampson, Nancy; Schoenbaum, Michael; Zaslavsky, Alan; Kessler, Ronald

    Background

    The prevalence of suicide among U.S. Army soldiers has risen dramatically in recent years. Prior studies suggest that most soldiers with suicidal behaviors (i.e., ideation, plans, and attempts) had first onsets prior to enlistment. However, those data are based on retrospective self-reports of soldiers later in their Army careers. Unbiased examination of this issue requires investigation of suicidality among new soldiers.

    Method

    The New Soldier Study (NSS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) used fully structured self-administered measures to estimate preenlistment histories of suicide ideation, plans, and attempts among new soldiers reporting for Basic Combat Training in 2011–2012. Survival models examined sociodemographic correlates of each suicidal outcome.

    Results

    Lifetime prevalence estimates of preenlistment suicide ideation, plans, and attempts were 14.1, 2.3, and 1.9%, respectively. Most reported onsets of suicide plans and attempts (73.3–81.5%) occurred within the first year after onset of ideation. Odds of these lifetime suicidal behaviors among new soldiers were positively, but weakly associated with being female, unmarried, religion other than Protestant or Catholic, and a race/ethnicity other than non-Hispanic White, non-Hispanic Black, or Hispanic.

    Conclusions

    Lifetime prevalence estimates of suicidal behaviors among new soldiers are consistent with retrospective reports of preenlistment prevalence obtained from soldiers later in their Army careers. Given that prior suicidal behaviors are among the strongest predictors of later suicides, consideration should be given to developing methods of obtaining valid reports of preenlistment suicidality from new soldiers to facilitate targeting of preventive interventions.

  • Publication

    Thirty-Day Prevalence ofDSM-IVMental Disorders Among Nondeployed Soldiers in the US Army

    (American Medical Association (AMA), 2014) Kessler, Ronald; Heeringa, Steven G.; Stein, Murray B.; Colpe, Lisa J.; Fullerton, Carol S.; Hwang, Irving; Naifeh, James A.; Nock, Matthew; Petukhova, Maria; Sampson, Nancy; Schoenbaum, Michael; Zaslavsky, Alan; Ursano, Robert J.

    Importance Although high rates of current mental disorder are known to exist in the US Army, little is known about the proportions of these disorders that had onsets prior to enlistment.

    Objective To estimate the proportions of 30-day DSM-IV mental disorders among nondeployed US Army personnel with first onsets prior to enlistment and the extent which role impairments associated with 30-day disorders differ depending on whether the disorders had pre- vs post-enlistment onsets.

    Design, Setting, and Participants A representative sample of 5428 soldiers participating in the Army Study to Assess Risk and Resilience in Servicemembers completed self-administered questionnaires and consented to linkage of questionnaire responses with administrative records.

    Main Outcomes and Measures Thirty-day DSM-IV internalizing (major depressive, bipolar, generalized anxiety, panic, and posttraumatic stress) and externalizing (attention-deficit/hyperactivity, intermittent explosive, alcohol/drug) disorders were assessed with validated self-report scales. Age at onset was assessed retrospectively. Role impairment was assessed with a modified Sheehan Disability Scale.

    Results A total of 25.1% of respondents met criteria for any 30-day disorder (15.0% internalizing; 18.4% externalizing) and 11.1% for multiple disorders. A total of 76.6% of cases reported pre-enlistment age at onset of at least one 30-day disorder (49.6% internalizing; 81.7% externalizing). Also, 12.8% of respondents reported severe role impairment. Controlling for sociodemographic and Army career correlates, which were broadly consistent with other studies, 30-day disorders with pre-enlistment (χ28 = 131.8, P < .001) and post-enlistment (χ27 = 123.8, P < .001) ages at onset both significantly predicted severe role impairment, although pre-enlistment disorders were more consistent powerful predictors (7 of 8 disorders significant; odds ratios, 1.6-11.4) than post-enlistment disorders (5 of 7 disorders significant; odds ratios, 1.5-7.7). Population-attributable risk proportions of severe role impairment were 21.7% for pre-enlistment disorders, 24.3% for post-enlistment disorders, and 43.4% for all disorders.

    Conclusions and Relevance Interventions to limit accession or increase resilience of new soldiers with pre-enlistment mental disorders might reduce prevalence and impairments of mental disorders in the US Army.

  • Publication

    Prevalence and Correlates of Suicidal Behavior Among Soldiers

    (American Medical Association (AMA), 2014) Nock, Matthew; Stein, Murray B.; Heeringa, Steven G.; Ursano, Robert J.; Colpe, Lisa J.; Fullerton, Carol S.; Hwang, Irving; Naifeh, James A.; Sampson, Nancy; Schoenbaum, Michael; Zaslavsky, Alan; Kessler, Ronald

    Importance The suicide rate among US Army soldiers has increased substantially in recent years.

    Objectives To estimate the lifetime prevalence and sociodemographic, Army career, and psychiatric predictors of suicidal behaviors among nondeployed US Army soldiers.

    Design, Setting, and Participants A representative cross-sectional survey of 5428 nondeployed soldiers participating in a group self-administered survey.

    Main Outcomes and Measures Lifetime suicidal ideation, suicide plans, and suicide attempts.

    Results The lifetime prevalence estimates of suicidal ideation, suicide plans, and suicide attempts are 13.9%, 5.3%, and 2.4%. Most reported cases (47.0%-58.2%) had pre-enlistment onsets. Pre-enlistment onset rates were lower than in a prior national civilian survey (with imputed/simulated age at enlistment), whereas post-enlistment onsets of ideation and plans were higher, and post-enlistment first attempts were equivalent to civilian rates. Most reported onsets of plans and attempts among ideators (58.3%-63.3%) occur within the year of onset of ideation. Post-enlistment attempts are positively related to being a woman (with an odds ratio [OR] of 3.3 [95% CI, 1.5-7.5]), lower rank (OR = 5.8 [95% CI, 1.8-18.1]), and previously deployed (OR = 2.4-3.7) and are negatively related to being unmarried (OR = 0.1-0.8) and assigned to Special Operations Command (OR = 0.0 [95% CI, 0.0-0.0]). Five mental disorders predict post-enlistment first suicide attempts in multivariate analysis: pre-enlistment panic disorder (OR = 0.1 [95% CI, 0.0-0.8]), pre-enlistment posttraumatic stress disorder (OR = 0.1 [95% CI, 0.0-0.7]), post-enlistment depression (OR = 3.8 [95% CI, 1.2-11.6]), and both pre- and post-enlistment intermittent explosive disorder (OR = 3.7-3.8). Four of these 5 ORs (posttraumatic stress disorder is the exception) predict ideation, whereas only post-enlistment intermittent explosive disorder predicts attempts among ideators. The population-attributable risk proportions of lifetime mental disorders predicting post-enlistment suicide attempts are 31.3% for pre-enlistment onset disorders, 41.2% for post-enlistment onset disorders, and 59.9% for all disorders.

    Conclusions and Relevance The fact that approximately one-third of post-enlistment suicide attempts are associated with pre-enlistment mental disorders suggests that pre-enlistment mental disorders might be targets for early screening and intervention. The possibility of higher fatality rates among Army suicide attempts than among civilian suicide attempts highlights the potential importance of means control (ie, restricting access to lethal means [such as firearms]) as a suicide prevention strategy.

  • Publication

    Sociodemographic and career history predictors of suicide mortality in the United States Army 2004–2009

    (Cambridge University Press (CUP), 2014) Gilman, Stephen Edward; Bromet, E. J.; Cox, K. L.; Colpe, L. J.; Fullerton, C. S.; Gruber, M; Heeringa, S. G.; Lewandowski-Romps, L.; Millikan-Bell, A. M.; Naifeh, J. A.; Nock, Matthew; Petukhova, Maria; Sampson, Nancy; Schoenbaum, M.; Stein, M. B.; Ursano, R. J.; Wessely, S.; Zaslavsky, Alan; Kessler, Ronald

    The US Army suicide rate has increased sharply in recent years. Identifying significant predictors of Army suicides in Army and Department of Defense (DoD) administrative records might help focus prevention efforts and guide intervention content. Previous studies of administrative data, although documenting significant predictors, were based on limited samples and models. A career history perspective is used here to develop more textured models. The analysis was carried out as part of the Historical Administrative Data Study (HADS) of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). De-identified data were combined across numerous Army and DoD administrative data systems for all Regular Army soldiers on active duty in 2004–2009. Multivariate associations of sociodemographics and Army career variables with suicide were examined in subgroups defined by time in service, rank and deployment history. Several novel results were found that could have intervention implications. The most notable of these were significantly elevated suicide rates (69.6–80.0 suicides per 100 000 person-years compared with 18.5 suicides per 100 000 person-years in the total Army) among enlisted soldiers deployed either during their first year of service or with less than expected (based on time in service) junior enlisted rank; a substantially greater rise in suicide among women than men during deployment; and a protective effect of marriage against suicide only during deployment. A career history approach produces several actionable insights missed in less textured analyses of administrative data predictors. Expansion of analyses to a richer set of predictors might help refine understanding of intervention implications.

  • Publication

    Field procedures in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

    (Wiley-Blackwell, 2013) Heeringa, Steven G.; Gebler, Nancy; Colpe, Lisa J.; Fullerton, Carol S.; Hwang, Irving; Kessler, Ronald; Naifeh, James A.; Nock, Matthew; Sampson, Nancy; Schoenbaum, Michael; Zaslavsky, Alan; Stein, Murray B.; Ursano, Robert J.

    The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) is a multi-component epidemiological and neurobiological study of unprecedented size and complexity designed to generate actionable evidence-based recommendations to reduce U.S. Army suicides and increase basic knowledge about determinants of suicidality by carrying out coordinated component studies. A number of major logistical challenges were faced in implementing these studies. The current report presents an overview of the approaches taken to meet these challenges, with a special focus on the field procedures used to implement the component studies. As detailed in the paper, these challenges were addressed at the onset of the initiative by establishing an Executive Committee, a Data Coordination Center (the Survey Research Center [SRC] at the University of Michigan), and study-specific design and analysis teams that worked with staff on instrumentation and field procedures. SRC staff, in turn, worked with the Office of the Deputy Under Secretary of the Army (ODUSA) and local Army Points of Contact (POCs) to address logistical issues and facilitate data collection. These structures, coupled with careful fieldworker training, supervision, and piloting contributed to the major Army STARRS data collection efforts having higher response rates than previous large-scale studies of comparable military samples.

  • Publication

    Response bias, weighting adjustments, and design effects in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

    (Wiley-Blackwell, 2013) Kessler, Ronald; Heeringa, Steven G.; Colpe, Lisa J.; Fullerton, Carol S.; Gebler, Nancy; Hwang, Irving; Naifeh, James A.; Nock, Matthew; Sampson, Nancy; Schoenbaum, Michael; Zaslavsky, Alan; Stein, Murray B.; Ursano, Robert J.

    The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) is a multi-component epidemiological and neurobiological study designed to generate actionable recommendations to reduce U.S. Army suicides and increase knowledge about determinants of suicidality. Three Army STARRS component studies are large-scale surveys: one of new soldiers prior to beginning Basic Combat Training (BCT; n=50,765 completed self-administered questionnaires); another of other soldiers exclusive of those in BCT (n=35,372); and a third of three Brigade Combat Teams about to deploy to Afghanistan who are being followed multiple times after returning from deployment (n= 9,421). Although the response rates in these surveys are quite good (72.0-90.8%), questions can be raised about sample biases in estimating prevalence of mental disorders and suicidality, the main outcomes of the surveys based on evidence that people in the general population with mental disorders are under-represented in community surveys. This paper presents the results of analyses designed to determine whether such bias exists in the Army STARRS surveys and, if so, to develop weights to correct for these biases. Data are also presented on sample inefficiencies introduced by weighting and sample clustering and on analyses of the trade-off between bias and efficiency in weight trimming.