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Anthony J. Rosellini

Anthony J. Rosellini

D-Index & Metrics

Psychology

D-Index
32
Citations
5341
World Ranking
10824
National Ranking
5659

Overview

Anthony J. Rosellini is affiliated with Boston University in the United States and has contributed extensively to the field of psychology, with a primary focus on clinical psychology. Their research spans multiple subfields, including experimental and cognitive psychology, social psychology, epidemiology, and public health, environmental and occupational health.

Their work addresses a range of mental health topics, prominently featuring suicide and self-harm studies, mental health treatment and access, anxiety, depression, psychometrics, treatment, cognitive processes, posttraumatic stress disorder research, child and adolescent psychosocial and emotional development, mental health research topics broadly, and resilience and mental health.

Among their recent publications are the following papers:

  • Developing and Validating Clinical Questionnaires (2021), published in Annual Review of Clinical Psychology
  • Supervised Machine Learning: A Brief Primer (2020), published in Behavior Therapy
  • Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries (2021), published in American Journal of Epidemiology
  • Suicide prediction among men and women with depression: A population-based study (2021), published in Journal of Psychiatric Research
  • Using machine learning to predict suicide in the 30 days after discharge from psychiatric hospital in Denmark (2021), published in The British Journal of Psychiatry

Rosellini frequently collaborates with a group of coauthors who have contributed to multiple publications together. These include:

  • Jaimie L. Gradus
  • Erzsébet Horváth-Puhó
  • Timothy L. Lash
  • Henrik Toft Sørensen
  • Tammy Jiang

Rosellini's publications have appeared in several recurring venues, reflecting their consistent engagement with specific scholarly communities. These venues include:

  • Behavior Therapy
  • American Journal of Epidemiology
  • Social Psychiatry and Psychiatric Epidemiology
  • Journal of Psychiatric Research
  • Cognitive and Behavioral Practice

The scope of Rosellini's work indicates a focus on the application of clinical and cognitive psychology methods to better understand and address mental health challenges, particularly those related to suicide prevention, treatment accessibility, and the psychometrics of clinical tools. Their integration of machine learning techniques into psychiatric epidemiology demonstrates a methodological approach that combines advanced analytics with traditional psychological research.

Best Publications

  • Supervised Machine Learning: A Brief Primer.

    Tammy Jiang;Jaimie L. Gradus;Anthony J. Rosellini

  • Predicting Suicides After Psychiatric Hospitalization in US Army Soldiers: The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

    Ronald Kessler;Christopher H. Warner;Christopher Ivany;Maria Petukhova

  • How well can post‐traumatic stress disorder be predicted from pre‐trauma risk factors? An exploratory study in the WHO World Mental Health Surveys

    Ronald C. Kessler;Sherri Rose;Karestan C. Koenen;Elie G. Karam

  • The NEO Five-Factor Inventory: latent structure and relationships with dimensions of anxiety and depressive disorders in a large clinical sample.

    Anthony J. Rosellini;Timothy A. Brown

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

    R C Kessler;H. M. van Loo;Klaas Wardenaar;R M Bossarte

  • Developing a practical suicide risk prediction model for targeting high‐risk patients in the Veterans health Administration

    Ronald C. Kessler;Irving Hwang;Claire A. Hoffmire;John F. McCarthy

  • Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder.

    R C Kessler;H. M. van Loo;Klaas Wardenaar;R M Bossarte

  • Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

    R C Kessler;M B Stein;M B Stein;M V Petukhova;P Bliese

  • The Direct and Interactive Effects of Neuroticism and Life Stress on the Severity and Longitudinal Course of Depressive Symptoms

    Timothy A. Brown;Anthony J. Rosellini

  • Mental disorder comorbidity and suicidal thoughts and behaviors in the World Health Organization World Mental Health Surveys International College Student initiative.

    Randy P. Auerbach;Philippe Mortier;Ronny Bruffaerts;Jordi Alonso

  • Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

    Jaimie L. Gradus;Jaimie L. Gradus;Anthony J. Rosellini;Erzsébet Horváth-Puhó;Amy E. Street;Amy E. Street

  • PREVALENCE AND CORRELATES OF SUICIDAL BEHAVIOR AMONG NEW SOLDIERS IN THE U.S. ARMY: RESULTS FROM THE ARMY STUDY TO ASSESS RISK AND RESILIENCE IN SERVICEMEMBERS (ARMY STARRS)

    Robert J. Ursano;Steven G. Heeringa;Murray B. Stein;Murray B. Stein;Sonia Jain

  • Childhood adversity, adult stress, and the risk of major depression or generalized anxiety disorder in US soldiers: a test of the stress sensitization hypothesis.

    Gretchen Bandoli;Laura Campbell-Sills;Ronald C. Kessler;Steven G. Heeringa

  • LIFETIME PREVALENCE OF DSM‐IV MENTAL DISORDERS AMONG NEW SOLDIERS IN THE U.S. ARMY: RESULTS FROM THE ARMY STUDY TO ASSESS RISK AND RESILIENCE IN SERVICEMEMBERS (ARMY STARRS)

    Anthony Rosellini;Steven G. Heeringa;Murray B. Stein;Murray B. Stein;Robert J. Ursano

  • APPROXIMATING A DSM-5 DIAGNOSIS OF PTSD USING DSM-IV CRITERIA.

    Anthony J. Rosellini;M.P.H. Murray B. Stein M.D.;M.P.H. Lisa J. Colpe Ph.D.;Steven G. Heeringa

  • Sexual Assault Victimization and Mental Health Treatment, Suicide Attempts, and Career Outcomes Among Women in the US Army.

    Anthony J. Rosellini;Amy E. Street;Robert J. Ursano;Wai Tat Chiu

  • 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).

    Matthew K. Nock;Robert J. Ursano;Steven G. Heeringa;Murray B. Stein

  • Developing and Validating Clinical Questionnaires.

    Anthony J Rosellini;Timothy A Brown

  • Predicting posttraumatic stress disorder following a natural disaster

    Anthony J. Rosellini;Anthony J. Rosellini;Francisca Dussaillant;José R. Zubizarreta;Ronald C. Kessler

  • Understanding the elevated suicide risk of female soldiers during deployments

    A. E. Street;Stephen Edward Gilman;A Rosellini;M. B. Stein

  • Experiential Avoidance as a Mechanism of Change Across Cognitive-Behavioral Therapy in a Sample of Participants with Heterogeneous Anxiety Disorders

    Elizabeth H. Eustis;Nicole Cardona;Maya Nauphal;Shannon Sauer-Zavala

Frequent Co-Authors

Robert J. Ursano
Robert J. Ursano Uniformed Services University of the Health Sciences
Timothy A. Brown
Timothy A. Brown Boston University
Matthew K. Nock
Matthew K. Nock Harvard University
Paul D. Bliese
Paul D. Bliese University of South Carolina
Murray B. Stein
Murray B. Stein University of California, San Diego
John Monahan
John Monahan University of Virginia
Wai Tat Chiu
Wai Tat Chiu Harvard Medical School
Evelyn J. Bromet
Evelyn J. Bromet Stony Brook University
David H. Barlow
David H. Barlow Boston University
David Daniel Ebert
David Daniel Ebert Technical University of Munich

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