There are no generally accepted methods for prospectively identifying individuals at risk for post-traumatic stress disorder (PTSD) after a traumatic event. However, several individual difference variables show promise as pre-trauma risk factors. Recent findings from the PI's differential conditioning study indicate that a conditioned skin conductance response is acquired more strongly and extinguishes more slowly in PTSD than in non-PTSD, trauma-exposed control subjects, i.e., that PTSD subjects are more "conditionable." Given that many PTSD symptoms may be conceptualized as conditioned responses (CRs), it is plausible that individuals who are more prone to acquire CRs in the first place would be more likely to develop this disorder. The proposed project will examine a promising set of pre-trauma psychophysiologic, endocrinologic, and psychometric measures for their ability to predict the occurrence and severity of PTSD following exposure to traumatic events in firefighter/EMT and police recruits. It is hypothesized that the selected pre-trauma measures will predict PTSD following an index traumatic event. Prior to receiving their recruitment training, subjects will undergo a battery of psychometric questionnaires. A Pavlovian differential conditioning procedure which pairs colored circles with a mildly aversive UCS will be administered. Other psychophysiologic tests found useful in measuring PTSD, e.g., startle response, and suppression of salivary cortisol by a low (0.5 mg) dose of dexamethasone, will also be measured. After the pre-trauma assessment, subjects will be closely followed for the occurrence of a traumatic event that meets the DSM-IV PTSD A.1 criterion. Three months after such an event, the trauma-exposed subject will return for psychodiagnostic, psychometric, and psychophysiologic assessment of PTSD. Logistic and multiple regression techniques will be used to examine the relationship between psychophysiologic, endocrinologic, and psychometric predictor measures and categorical and continuous PTSD outcome measures.