The objective of this application is to differentiate trauma survivors who recover from posttraumatic stress disorder (PTSD) from those who develop enduring symptoms. While recent PTSD studies have made advances, there have been limitations. To develop effective interventions that can become part of routine medical care, there is a need for effective decision tools to guide both clinicians and patients. Most agree these tools need to be based on sound longitudinal data. To meet this objective, we propose using a dataset originally developed by the study PI. The PI is completely familiar with this dataset. These data were collected during his NIMH-funded study, """"""""Impact of Mental Health Treatment in NY after WTC Disaster"""""""" (MH-66403), a study that assessed the health effects of the World Trade Center disaster (WTCD) in New York City (NYC). This study collected extensive information, including detailed medical, mental status, trauma, demographic, psychosocial, treatment, and exposure data spanning both the pre-WTCD and post-WTCD periods. The complete dataset includes 1,352 women and 1,016 men (N = 2,368) randomly selected from the five boroughs of NYC. This urban sample of community-dwelling adults is also ethnically diverse (African American = 606;Hispanics = 559;Asian/other = 188). Based on the full DSM-IV criteria (criteria A through E) used in this study, 174 persons were PTSD-positive one-year post-WTCD and 134 were PTSD-positive two- years post-WTCD. Thus, these data are viable for longitudinal modeling of PTSD outcomes, including remitted, delayed and persistent PTSD cases. Using an applied and experienced interdisciplinary team at Geisinger Clinic with expertise in psychology, epidemiology, neurology, clinical medicine, and biostatistical modeling, we plan to develop robust risk-factor models that will predict PTSD outcomes, including resilient, remitted, delayed, and persistent PTSD cases. These models will be extremely useful in applied clinical medicine. The Geisinger team has extensive experience in developing these advanced clinical models and in using them in clinical practice. The objective of this application is to differentiate trauma survivors who recover from posttraumatic stress disorder (PTSD) from those who develop enduring symptoms. To meet this objective, we propose using a dataset originally developed by the study PI. These data were collected during a NIMH-funded study, """"""""Impact of Mental Health Treatment in NY after WTC Disaster"""""""" (MH-66403), a study that assessed the health effects of the World Trade Center disaster (WTCD) in New York City (NYC). The complete dataset includes 1,352 women and 1,016 men (N = 2,368) randomly selected from the five boroughs of NYC. Based on the full DSM-IV criteria used in this study, 174 persons were PTSD-positive one-year post-WTCD and 134 were PTSD-positive two- years post-WTCD. Using an interdisciplinary team at Geisinger Clinic with expertise in psychology, epidemiology, neurology, clinical medicine, and biostatistical modeling, we plan to develop risk-factor models that will predict PTSD outcomes in different populations. The Geisinger team has experience in developing these clinical models and in using them in clinical practice.
The objective of this application is to differentiate trauma survivors who recover from posttraumatic stress disorder (PTSD) from those who develop enduring symptoms. To meet this objective, we propose using a dataset originally developed by the study PI. These data were collected during a NIMH-funded study, Impact of Mental Health Treatment in NY after WTC Disaster (MH-66403), a study that assessed the health effects of the World Trade Center disaster (WTCD) in New York City (NYC). The complete dataset includes 1,352 women and 1,016 men (N = 2,368) randomly selected from the five boroughs of NYC. Based on the full DSM-IV criteria used in this study, 174 persons were PTSD-positive one-year post-WTCD and 134 were PTSD-positive two-years post-WTCD. Using an interdisciplinary team at Geisinger Clinic with expertise in psychology, epidemiology, neurology, clinical medicine, and biostatistical modeling, we plan to develop risk-factor models that will predict PTSD outcomes in different populations. The Geisinger team has experience in developing these clinical models and in using them in clinical practice.
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