Suicide is the ninth leading cause of death in the United States. Therefore, it is important to discover adaptive life-maintaining characteristics in high risk populations. Many patients with life-threatning illnesses have frequent suicidal thoughts. The difference in reasons for living between men and women with and without chronic illness was investigated. The suicide ideation was determined by ratings on a 48 item Reasons for Living questionnaire. Degree of chronocity of illness and illnes related issues were determined by a demographic questionnaire. Results showed that men commit suicide at a higher rate than women. Results of ANOVA'S indicated that individuals with chronic illness do not have fewer coping skills than individuals without chronic illness. Even though the present study did not indicate that chronic illness is one of the factors that precipitates suicide, research shows that in chronically ill patients depresion is a major risk factor for suicide. Thus it is necessary for researchers to discover additional reasons for living for these individuals to keep them from committing suicide.

abstract: Critical care environments are complex in nature. Fluctuating team dynamics and the plethora of technology and equipment create unforeseen demands on clinicians. Such environments become chaotic very quickly due to the chronic exposure to unpredictable clusters of events. In order to cope with this complexity, clinicians tend to develop ad-hoc adaptations to function in an effective manner. It is these adaptations or "deviations" from expected behaviors that provide insight into the processes that shape the overall behavior of the complex system. The research described in this manuscript examines the cognitive basis of clinicians' adaptive mechanisms and presents a methodology for studying the same. Examining interactions in complex systems is difficult due to the disassociation between the nature of the environment and the tools available to analyze underlying processes. In this work, the use of a mixed methodology framework to study trauma critical care, a complex environment, is presented. The hybrid framework supplements existing methods of data collection (qualitative observations) with quantitative methods (use of electronic tags) to capture activities in the complex system. Quantitative models of activities (using Hidden Markov Modeling) and theoretical models of deviations were developed to support this mixed methodology framework. The quantitative activity models developed were tested with a set of fifteen simulated activities that represent workflow in trauma care. A mean recognition rate of 87.5% was obtained in automatically recognizing activities. Theoretical models, on the other hand, were developed using field observations of 30 trauma cases. The analysis of the classification schema (with substantial inter-rater reliability) and 161 deviations identified shows that expertise and role played by the clinician in the trauma team influences the nature of deviations made (p<0.01). The results shows that while expert clinicians deviate to innovate, deviations of novices often result in errors. Experts' flexibility and adaptiveness allow their deviations to generate innovative ideas, in particular when dynamic adjustments are required in complex situations. The findings suggest that while adherence to protocols and standards is important for novice practitioners to reduce medical errors and ensure patient safety, there is strong need for training novices in coping with complex situations as well. / Dissertation/Thesis / Ph.D. Biomedical Informatics 2012