Sandro Galea

Boston University, Boston, Massachusetts, United States

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Publications (705)1966.26 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: High rates of mental health (MH) problems have been documented among disaster relief workers. However, few workers utilize MH services, and predictors of service use among this group remain unexplored. The purpose of this study was to explore associations between predisposing, illness-related, and enabling factors from Andersen's behavioral model of treatment-seeking and patterns of service use among participants who completed at least one full day of cleanup work after the Deepwater Horizon oil spill and participated in home visits for the NIEHS GuLF STUDY (N = 8931). Workers reported on MH symptoms and whether they had used counseling or medication for MH problems since the oil spill. Hierarchical logistic regression models explored associations between predictors and counseling and medication use in the full sample, and type of use (counseling only, medication only, both) among participants who used either service. Analyses were replicated for subsamples of participants with and without symptom inventory scores suggestive of probable post-disaster mental illness. Having a pre-spill MH diagnosis, pre-spill service use, more severe post-spill MH symptoms, and healthcare coverage were positively associated with counseling and medication use in the full sample. Among participants who used either service, non-Hispanic Black race, pre-spill counseling, lower depression, and not identifying a personal doctor or healthcare provider were predictive of counseling only, whereas older age, female gender and pre-spill medication were predictive of medication only. The results were generally consistent among participants with and without probable post-disaster mental illness. The results suggest variability in which factors within Andersen's behavioral model are predictive of different patterns of service use among disaster relief workers. Copyright © 2015 Elsevier Ltd. All rights reserved.
    Social Science & Medicine. 04/2015; 130.
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    ABSTRACT: Curricular change is essential for maintaining vibrant, timely, and relevant educational programming. However, major renewal of a long-standing curriculum at an established university presents many challenges for leaders, faculty, staff, and students. We present a case study of a dramatic curriculum renewal of one of the nation's largest Master of Public Health degree programs: Columbia University's Mailman School of Public Health. We discuss context, motivation for change, the administrative structure established to support the process, data sources to inform our steps, the project timeline, methods for engaging the school community, and the extensive planning that was devoted to evaluation and communication efforts. We highlight key features that we believe are essential for successful curricular change.
    American journal of public health. 03/2015; 105 Suppl 1:S17-21.
  • Karestan C Koenen, Sandro Galea
    Social Psychiatry and Psychiatric Epidemiology 02/2015; · 2.58 Impact Factor
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    ABSTRACT: Attempts at predicting individual risk of disease based on common germline genetic variation have largely been disappointing. The present paper formalises why genetic prediction at the individual level is and will continue to have limited utility given the aetiological architecture of most common complex diseases. Data were simulated on one million populations with 10 000 individuals in each populations with varying prevalences of a genetic risk factor, an interacting environmental factor and the background rate of disease. The determinant risk ratio and risk difference magnitude for the association between a gene variant and disease is a function of the prevalence of the interacting factors that activate the gene, and the background rate of disease. The risk ratio and total excess cases due to the genetic factor increase as the prevalence of interacting factors increase, and decrease as the background rate of disease increases. Germline genetic variations have high predictive capacity for individual disease only under conditions of high heritability of particular genetic sequences, plausible only under rare variant hypotheses. Under a model of common germline genetic variants that interact with other genes and/or environmental factors in order to cause disease, the predictive capacity of common genetic variants is determined by the prevalence of the factors that interact with the variant and the background rate. A focus on estimating genetic associations for the purpose of prediction without explicitly grounding such work in an understanding of modifiable (including environmentally influenced) factors will be limited in its ability to yield important insights about the risk of disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
    Journal of Epidemiology &amp Community Health 02/2015; · 3.29 Impact Factor
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    ABSTRACT: Objective: The individual and economic burden of psychiatric illnesses is substantial. Although treatment of psychiatric disorders mitigates the burden of illness, over half of military personnel with disorders do not receive mental health care. However, there is a paucity of research examining the relationship between psychiatric disorder categories and treatment-seeking behavior in representative military populations. This study aimed to document, by psychiatric disorder category, the annualized rate of Guard members who obtained psychiatric services and the factors associated with service utilization. Methods: Face-to-face clinical assessments were conducted between 2008 and 2012 to assess lifetime and current psychiatric disorders and recent psychiatric service use among 528 Ohio Army National Guard soldiers. Results: An annualized rate of 31% of persons per year accessed psychiatric services between 2010 and 2012. Persons with substance use disorders had the lowest annualized rate of service use, and these were the only disorders not predictive of accessing services. Current mood disorder, current anxiety disorder, and lifetime history of service use were the strongest predictors of recent service use. There were no socioeconomic or other group predictors of psychiatric service use. Conclusions: About half of the soldiers who could benefit from mental health services used them, yet soldiers with substance use disorders were predominantly going untreated. There were no differences in treatment utilization by group characteristics, suggesting no systematic barriers to care for particular groups. Efforts to encourage broader adoption of treatment seeking, particularly among persons with substance use disorders, are necessary to mitigate psychiatric health burden in this population.
    Psychiatric services (Washington, D.C.) 02/2015; · 2.81 Impact Factor
  • Katherine Keyes, Sandro Galea
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    ABSTRACT: Risk factor epidemiology has contributed to substantial public health success. In this essay we argue, however, that the focus on risk factor epidemiology has led epidemiology to ever increasing focus on the estimation of precise causal effects of exposures on an outcome, at the expense of engagement with the broader causal architecture that produces population health. In order to conduct an epidemiology of consequence, a systematic effort is needed to engage our science in a critical reflection both about how well and under what conditions or assumptions we can assess causal effects, and also on what will truly matter most for changing population health. Such an approach changes the priorities and values of the discipline, and requires reorientation of how we structure the questions we ask and the methods we use, as well as how we teach epidemiology to our emerging scholars.
    Annals of Epidemiology 02/2015; · 2.15 Impact Factor
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    ABSTRACT: Background: Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are frequently comorbid. One explanation for this comorbidity is that PTSD has a constellation of " dysphoria " symptoms resembling depression. Method: Using confirmatory factor analysis we tested the role of DSM-5 PTSD's dysphoria factor in relation to MDD symptom dimensions of somatic and non-somatic psychopathology. 672 Ohio National Guard soldiers completed DSM-5 measures of PTSD and MDD symptoms in an epidemiological study. Results: Results indicated that in contrast to other PTSD factors, PTSD's dysphoria factor was more related to MDD's somatic and non-somatic factors. Limitations: Limitations include generalizability to the epidemiological population of trauma-exposed military veterans rather than civilians, and reliance on self-report measures. Conclusions: Implications concerning clinical psychopathology and comorbidity of PTSD are discussed, including whether PTSD should be refined by removing its non-specific symptoms.
    Journal of Affective Disorders 01/2015; 175:373-378. · 3.76 Impact Factor
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  • Sasha Rudenstine, Sandro Galea
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    ABSTRACT: Prevention efforts have greatly reduced the prevalence of many communicable and non-communicable diseases worldwide. In contrast, prevention strategies for mental disorders remain in their infancy. This paper provides a summary of the key issues surrounding mental disorder prevention and proposes a framework for how to catalyze action in the area. Three core assumptions guide this work (1) the onset of mental disorders is often preventable, (2) among those individuals with a mental disorder, the trajectory of health and functioning can be shaped by external resources, and (3) many specific and generic risk and protective factors for mental disorders are associated with specific stages of the life course. We propose that the adoption of a life course approach to prevention can be clarifying and motivating for both research and practice.
    Social Psychiatry and Psychiatric Epidemiology 01/2015; · 2.58 Impact Factor
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    ABSTRACT: Since 2001, the US military has increasingly relied on National Guard and reserve component forces to meet operational demands. Differences in preparation and military engagement experiences between active component and reserve component forces have long suggested that the psychiatric consequences of military engagement differ by component. We conducted a systematic review of prevalence and new onset of psychiatric disorders among reserve component forces and a meta-analysis of prevalence estimates comparing reserve component and active component forces, and we documented stage-sequential drivers of psychiatric burden among reserve component forces. We identified 27 reports from 19 unique samples published between 1985 and 2012: 9 studies reporting on the reserve component alone and 10 reporting on both the reserve component and the active component. The pooled prevalence for alcohol use disorders of 14.5% (95% confidence interval: 12.7, 15.2) among the reserve component was higher than that of 11.7% (95% confidence interval: 10.9, 12.6) among the active component, while there were no component differences for depression or post-traumatic stress disorder. We observed substantial heterogeneity in prevalence estimates reported by the reserve component. Published studies suggest that stage-sequential risk factors throughout the deployment cycle predicted alcohol use disorders, post-traumatic stress disorder and, to a lesser degree, depression. Improved and more standardized documentation of the mental health burden, as well as study of explanatory factors within a life-course framework, is necessary to inform mitigating strategies and to reduce psychiatric burden among reserve component forces. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
    Epidemiologic Reviews 01/2015; · 7.33 Impact Factor
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    ABSTRACT: Posttraumatic stress disorder (PTSD) is a common, debilitating mental disorder that has been associated with type 2 diabetes mellitus (T2D) and its risk factors, including obesity, in cross-sectional studies. If PTSD increases risk of incident T2D, enhanced surveillance in high-risk populations may be warranted. To conduct one of the first longitudinal studies of PTSD and incidence of T2D in a civilian sample of women. The Nurses' Health Study II, a US longitudinal cohort of women (N = 49 739). We examined the association between PTSD symptoms and T2D incidence over a 22-year follow-up period. Type 2 diabetes, self-reported and confirmed with self-report of diagnostic test results, symptoms, and medications, a method previously validated by physician medical record review. Posttraumatic stress disorder was assessed by the Short Screening Scale for DSM-IV PTSD. We examined longitudinal assessments of body mass index, smoking, alcohol intake, diet quality, physical activity, and antidepressant use as mediators of possible increased risk of T2D for women with PTSD. The study hypothesis was formulated prior to PTSD ascertainment. Symptoms of PTSD were associated in a dose-response fashion with T2D incidence (1-3 symptoms: hazard ratio, 1.4 [95% CI, 1.2-1.6]; 4 or 5 symptoms; hazard ratio, 1.5 [95% CI, 1.3-1.7]; 6 or 7 symptoms: hazard ratio, 1.8 [95% CI, 1.5-2.1]). Antidepressant use and a higher body mass index associated with PTSD accounted for nearly half of the increased risk of T2D for women with PTSD. Smoking, diet quality, alcohol intake, and physical activity did not further account for increased risk of T2D for women with PTSD. Women with the highest number of PTSD symptoms had a nearly 2-fold increased risk of T2D over follow-up than women with no trauma exposure. Health professionals treating women with PTSD should be aware that these patients are at risk of increased body mass index and T2D. Comprehensive PTSD treatment should be expanded to address the health behaviors that contribute to obesity and chronic disease in affected populations.
    JAMA Psychiatry 01/2015; · 12.01 Impact Factor
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    ABSTRACT: The goal of this study is to determine the pre-existing lifetime and current prevalence of DSM-IV Axis I disorders within the Ohio Army National Guard (OHARNG.) Data was analyzed from the clinical subsample of the Ohio Army National Guard Mental Health Initiative (OHARNG MHI.) 500 participants were provided with an in-depth clinical assessment using the Clinician-Administered PTSD Scale (CAPS) and the Structured Clinical Interview for DSM-IV-TR (SCID.) Logistic regression examined the relationship between Axis I disorders and the number of deployments and gender. Prevalence of at least one DSM-IV lifetime disorder was 66.2%; substance use disorders were 52.2%, followed by mood disorders (30.0%) and anxiety disorders (22.0%). Prevalence of at least one current disorder was 24.8%; anxiety disorders (13.2%), mood disorders (7.6%), and substance use disorders (7.0%) were most frequent. Number of deployments was associated with PTSD (OR=8.27, 95% CI 2.10-32.59, p=0.003), alcohol use disorder (OR=1.77, 95% CI 1.07-2.92, p=0.025), and any substance use disorder (OR=1.85, 95% CI 1.12-3.05, p=0.016). Gender (OR=2.02, 95% CI 1.10-3.73, p=0.024) was associated with any mood disorder. The results provide baseline information on the most prevalent mental disorders within the OHARNG.
    Psychiatry Research. 01/2015;
  • Brandon D L Marshall, Sandro Galea
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    ABSTRACT: Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry. © The Author 2014. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
    American Journal of Epidemiology 01/2015; 181(2):92-99. · 4.98 Impact Factor
  • Brandon D L Marshall, Sandro Galea
    American Journal of Epidemiology 12/2014; 181(2). · 4.98 Impact Factor
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    ABSTRACT: Disasters have far-reaching and potentially long-lasting effects on youth and families. Research has consistently shown a clear increase in the prevalence of several mental health disorders after disasters, including depression and posttraumatic stress disorder. Widely accessible evidence-based interventions are needed to address this unmet need for youth and families, who are underrepresented in disaster research. Rapid growth in Internet and Smartphone access, as well as several web based evaluation studies with various adult populations has shown that web-based interventions are likely to be feasible in this context and can improve clinical outcomes. Such interventions also are generally cost-effective, can be targeted or personalized, and can easily be integrated in a stepped care approach to screening and intervention delivery. This is a protocol paper that describes an innovative study design in which we evaluate a self-help web-based resource, Bounce Back Now, with a population-based sample of disaster affected adolescents and families. The paper includes description and justification for sampling selection and procedures, selection of assessment measures and methods, design of the intervention, and statistical evaluation of critical outcomes. Unique features of this study design include the use of address-based sampling to recruit a population-based sample of disaster-affected adolescents and parents, telephone and web-based assessments, and development and evaluation of a highly individualized web intervention for adolescents. Challenges related to large-scale evaluation of technology-delivered interventions with high-risk samples in time-sensitive research are discussed, as well as implications for future research and practice. Copyright © 2014. Published by Elsevier Inc.
    Contemporary Clinical Trials 12/2014; · 1.99 Impact Factor
  • Biological Psychiatry 12/2014; · 9.47 Impact Factor
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    ABSTRACT: Estimate prevalence of lifetime, current year, and current month depression and post-traumatic stress disorder (PTSD) among US military reservists. Structured interviews were performed with a nationally representative military reserve sample (n = 2,003). Sociodemographic characteristics, military experiences, lifetime stressors, and psychiatric conditions were assessed. Depression was measured with the PHQ-9, and PTSD (deployment and non-deployment related) was assessed with the PCL-C. Depression (21.63 % lifetime, 14.31 % current year, and 5.99 % current month) was more common than either deployment-related PTSD (5.49 % lifetime, 4.98 % current year, and 3.62 % current month) or non-deployment-related PTSD (5.40 % lifetime, 3.91 % current year, and 2.32 % current month), and branch-related differences were found. Non-deployment-related trauma was associated with non-deployment-related PTSD and depression in a dose-response fashion; deployment-related trauma was associated with deployment-related PTSD and depression in a dose-response fashion. The study reveals notable differences in PTSD and depression prevalence by service branch that may be attributable to a combination of factors including greater lifetime trauma exposures and differing operational military experiences. Our findings suggest that service branch and organizational differences are related to key protective and/or risk factors, which may prove useful in guiding prevention and treatment efforts among reservists.
    Social Psychiatry and Psychiatric Epidemiology 11/2014; · 2.58 Impact Factor
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    ABSTRACT: The current study examined the relationship between childhood maltreatment—emotional, physical, and severe physical maltreatment—and the initiation and persistence of smoking. Data were drawn from the Midlife Developmentin the United States (MIDUS) Survey Waves 1 and 2. Frequency of childhood emotional, physical, and severe physical maltreatment (never, rare, intermittent, frequent) reported at Wave 1 was examined in relation to ever smoking, smoking daily, and persistent daily smoking at Waves 1 and 2. Logistic regression analyses were used to calculate odds ratios (with 95% confidence intervals), which were then adjusted for potential confounders. Childhood emotional, physical, and severe physical maltreatment were associated with increased odds of ever smoking, smoking daily, and persistent smoking at Waves 1 and 2. The majority of these associations remained significant after adjusting for confounding variables. These results suggest a history of trauma may play a prominent role in recalcitrant cigarette smoking and suggest that the success rates of treatments for smoking cessation may be improved by integrating trauma treatment where appropriate.
    Child Abuse & Neglect 11/2014; · 2.47 Impact Factor
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    ABSTRACT: Socioeconomic disadvantage is often evaluated at single points in the adult life course in health research. Social mobility models suggest that socioeconomic patterns may also influence disease risk. This study examines cumulative socioeconomic disadvantage (CSD) in relation to CVD mortality.Methods Data were from the Alameda County (CA) Study (n=2530). The CSD indices included father’s education, the respondent’s education, and either average or latent variable trajectory models of adulthood household income (1965-1994). Proportional hazards models were used to assess the associations between CSD and CVD mortality.ResultsThe CSD measures were not associated with CVD mortality in men. Among women, , the magnitude of the association between CSD and CVD mortality was greater for the income trajectory (HR3 vs 0 = 4.73, 95% CI = 2.20-10.18) compared to the average income (HR 3 vs 0 = 3.78, 95% CI =1.67-8.53) CSD measure.Conclusions Measures of CSD that incorporate patterning of resources over the life course were associated with CVD mortality for women but not men. Patterning of available socioeconomic resources may differentially influence chronic disease risk and mortality by gender, and future work should continue to investigate how greater patterns variability in available resources influences health outcomes.
    Annals of Epidemiology 11/2014; 25(2). · 2.15 Impact Factor
  • Sasha Rudenstine, Sandro Galea
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    ABSTRACT: We propose a model of population behavior in the aftermath of disasters. We conducted a qualitative analysis of an empirical dataset of 339 disasters throughout the world spanning from 1950 to 2005. We developed a model of population behavior that is based on 2 fundamental assumptions: (i) behavior is predictable and (ii) population behavior will progress sequentially through 5 stages from the moment the hazard begins until is complete. Understanding the progression of population behavior during a disaster can improve the efficiency and appropriateness of institutional efforts aimed at population preservation after large-scale traumatic events. Additionally, the opportunity for population-level intervention in the aftermath of such events will improve population health. (Disaster Med Public Health Preparedness. 2014;0:1-8).
    Disaster Medicine and Public Health Preparedness 11/2014; · 1.14 Impact Factor

Publication Stats

14k Citations
1,966.26 Total Impact Points

Institutions

  • 2015
    • Boston University
      Boston, Massachusetts, United States
  • 2001–2015
    • Columbia University
      • Department of Epidemiology
      New York, New York, United States
  • 2005–2014
    • CUNY Graduate Center
      New York City, New York, United States
  • 2013
    • Stony Brook University Hospital
      Stony Brook, New York, United States
  • 2012–2013
    • University of Toledo
      • • Department of Psychology
      • • Department of Psychiatry
      Toledo, Ohio, United States
    • Wayne State University
      • Center for Molecular Medicine and Genetics
      Detroit, MI, United States
    • McGill University
      • Department of Epidemiology, Biostatistics and Occupational Health
      Montréal, Quebec, Canada
    • Berkeley Adult School
      Berkeley, California, United States
  • 2009–2013
    • White River Junction VA Medical Center
      White River Junction, Vermont, United States
    • Robert Wood Johnson Foundation
      Princeton, New Jersey, United States
    • University of Illinois at Chicago
      • Department of Health Systems Science
      Chicago, IL, United States
    • Rush Medical College
      Chicago, Illinois, United States
    • University of South Florida
      • Department of Anthropology
      Tampa, FL, United States
    • University College London
      • Department of Clinical, Educational and Health Psychology
      London, ENG, United Kingdom
  • 2006–2013
    • Complutense University of Madrid
      Madrid, Madrid, Spain
    • San Francisco State University
      • Department of Health Education
      San Francisco, CA, United States
    • Idaho State University
      • Department of Psychology
      Idaho Falls, ID, United States
  • 2005–2013
    • Johns Hopkins Bloomberg School of Public Health
      • • Department of Health, Behavior and Society
      • • Department of Epidemiology
      • • Department of Mental Health
      Baltimore, MD, United States
  • 2004–2013
    • Gracie Square Hospital, New York, NY
      New York City, New York, United States
    • New York Presbyterian Hospital
      • Department of Emergency Medicine
      New York City, NY, United States
    • Johns Hopkins University
      Baltimore, Maryland, United States
  • 2002–2013
    • University of Michigan
      • • Department of Epidemiology
      • • Department of Health Behavior and Health Education
      Ann Arbor, Michigan, United States
  • 2011–2012
    • University of Oxford
      • Department of Public Health
      Oxford, ENG, United Kingdom
    • Harvard Medical School
      Boston, Massachusetts, United States
    • University of Vermont
      • Department of Psychology
      Burlington, VT, United States
    • Case Western Reserve University
      • Department of Psychiatry (University Hospitals Case Medical Center)
      Cleveland, OH, United States
    • City University of New York - John Jay College of Criminal Justice
      New York City, New York, United States
    • New York City Department of Health and Mental Hygiene
      New York, United States
    • Boston Children's Hospital
      • Division of General Pediatrics
      Boston, MA, United States
    • University of California, San Francisco
      • Division of Hospital Medicine
      San Francisco, CA, United States
    • University of Malaga
      • Facultad de Psicología
      Málaga, Andalusia, Spain
  • 2009–2012
    • Harvard University
      • • Department of Society, Human Development, and Health
      • • Department of Epidemiology
      Cambridge, MA, United States
  • 2008–2012
    • Yale University
      • Department of Psychiatry
      New Haven, Connecticut, United States
    • Honolulu University
      Honolulu, Hawaii, United States
    • City University of New York - Hunter College
      • CUNY School of Public Health at Hunter College
      Manhattan, NY, United States
  • 2005–2012
    • Concordia University–Ann Arbor
      Ann Arbor, Michigan, United States
  • 2009–2011
    • Rush University Medical Center
      • Department of Behavioral Sciences
      Chicago, IL, United States
  • 2006–2011
    • University of California, Berkeley
      • Division of Epidemiology
      Berkeley, CA, United States
  • 1990–2011
    • University of Toronto
      • • Department of Anthropology
      • • Department of Immunology
      Toronto, Ontario, Canada
  • 2010
    • University of Haifa
      • School of Political Sciences
      Haifa, Haifa District, Israel
  • 2001–2010
    • New York Academy of Medicine
      New York City, New York, United States
  • 2008–2009
    • University of Washington Seattle
      • School of Social Work
      Seattle, WA, United States
  • 2007–2009
    • Medical University of South Carolina
      • Department of Psychiatry and Behavioral Sciences
      Charleston, SC, United States
    • Hospital Universitario La Paz
      Madrid, Madrid, Spain
    • New York University
      • Medicine
      New York City, NY, United States
  • 2003–2009
    • Weill Cornell Medical College
      • Department of Psychiatry
      New York City, NY, United States
  • 2007–2008
    • NYU Langone Medical Center
      • Department of Emergency Medicine
      New York City, NY, United States
    • Kent State University
      • • Department of Psychology
      • • Applied Psychology Center
      Kent, OH, United States
  • 2006–2007
    • Cornell University
      • Department of Psychiatry
      Ithaca, NY, United States
  • 2004–2007
    • New York State Psychiatric Institute
      • Anxiety Disorders Clinic
      New York City, New York, United States
  • 2005–2006
    • Beth Israel Medical Center
      New York City, New York, United States
  • 2003–2005
    • Icahn School of Medicine at Mount Sinai
      • Department of Psychiatry
      Manhattan, New York, United States