Selected Publications

Rubenstein, E., Tewolde, S., Michals, A., Fortea, J., Pescador Jimenez, M., Skotko, B., Tripodis, Y., Weuve, J., & Rosellini, A. J. (2025). Novel predictors of Alzehimer’s Disease in Down Syndrome identified using machine learning. Journal of Alzheimer’s Disease, 108, 1166-1176. PubMed

Rosellini, A. J., Andrea, A. M., Galiano, C. S., Hwang, I., Brown, T. A., Luedtke, A., & Kessler, R. C. (2023). Developing transdiagnostic internalizing disorder prognostic indices for outpatient cognitive behavioral therapy. Behavior Therapy, 54, 461-475. PubMed

Borowski, S., Rosellini, A. J., Street, A. E., Gradus, J. L., & Vogt, D. (2022). The first year after military service: Predictors of U.S. Veterans’ suicidal ideation. American Journal of Preventive Medicine, 63, 233-241. +VHA Suicide Prevention Program “Top 20 Picks” of 2022 (out of ~800 suicide-related papers) PubMed

Rosellini, A. J., Liu, S., Anderson, G. N., Sbi, S., Tung, E., Knyazhanskaya, E. (2020). Developing algorithms to predict adult onset internalizing disorders: An ensemble learning approach. Journal of Psychiatric Research, 121, 189-196. PubMed

Jiang, T., Gradus, J. L., & Rosellini, A. J. (2020). Supervised machine learning: A brief primer. Behavior Therapy, 51, 675-687. PubMed

Gradus, J. L., Rosellini, A. J., Horváth-Puhó, E., Street, A. E., Galatzer-Levy, I., Jiang, T., Lash, T. L., & Sørensen, H. T. (2019). Prediction of sex-specific suicide risk using machine learning and single-payer health care registry data from Denmark. JAMA Psychiatry, 77, 25-34. PubMed

Rosellini, A. J., Dussaillant, F., Zubizarreta, J. R., Kessler, R. C., & Rose, S. (2018). Predicting posttraumatic stress disorder following a natural disaster. Journal of Psychiatric Research, 96, 15-22. PubMed; Media Coverage

Rosellini, A. J. (2018). Using machine learning methods to predict internalizing psychopathology risk and prognosis. The Clinical Psychologist, 71, 5-13.

Galiano, C. S., Andrea A. M., Tung, E. S., Brown, T. A., & Rosellini, A. J. (2024). Psychometric properties of the Distress Tolerance Scale in a clinical sample. Psychological Assessment, 36, 192-199. PubMed

Andrea A. M., Galiano, C. S., Brown, T. A., & Rosellini, A. J. (2024). Psychometric evaluation of the Emotion Regulation Questionnaire in a clinical sample. Journal of Psychopathology and Behavioral Assessment, 46, 1-9. PubMed

Osma, J., Martinez-Loredo, V., Quilez-Orden, A., Peris-Baquero, O., Ferreres-Galan, V., Prado-Abril, J., Torres-Alfosea, M. A., & Rosellini, A. J. (2023). Multidimensional Emotional Disorders Inventory: Reliability and validity in a Spanish clinical sample. Journal of Affective Disorders, 320, 65-73. PubMed

Hilton, B. T., Yusufov, M., Rosellini, A. J., Taghian, N. R., Weiss, R. D., Griffin, M. L., & McHugh, R. K. (2022). Psychometric properties of the Anxiety Sensitivity Index-3 in adults with substance use disorders. Journal of Substance Abuse Treatment, 132, 108507 (Epub). PubMed

Rosellini, A. J., & Brown, T. A. (2021). Developing and validating clinical questionnaires. Annual Review of Clinical Psychology, 17, 55-81. PubMed

Rosellini, A. J., & Brown, T. A. (2019). The Multidimensional Emotional Disorder Inventory (MEDI): Assessing transdiagnostic dimensions to validate a profile approach to emotional disorder classification. Psychological Assessment, 31, 59-72.  PubMed

Rosellini, A. J., & Brown, T. A. (2014). Initial interpretation and evaluation of a profile-based classification system for the anxiety and mood disorders: Incremental validity compared to DSM-IV categories. Psychological Assessment, 26, 1212-1224. PubMed

Rosellini, A. J., & Brown, T. A. (2011). The NEO-Five Factor Inventory: Latent structure and relationships with dimensions of anxiety and depressive disorders in a large clinical sample. Assessment, 18, 27-38. PubMed