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Full-Text Articles in Social and Behavioral Sciences
From "Hooah" To "Om": Mindfulness Practices For A Military Population, Kimberlee B. Bonura, Dawn M. Fountain
From "Hooah" To "Om": Mindfulness Practices For A Military Population, Kimberlee B. Bonura, Dawn M. Fountain
Journal of Social, Behavioral, and Health Sciences
Mindfulness practices, in general, have a growing body of evidence of effectiveness for improving both physical health and mental health. Further, these practices are showing promise when implemented with military populations for mental health issues such as PTSD. Challenges arise for practitioners in understanding the military's cultural differences and the functional aspects of mindfulness that may be specifically useful to military members. We outline strategies for referring military members to quality services and instruction, as well as best practices for connecting with military clients. Recommendations are made for further research with female service members and using single case design.
Quantitative Forecasting Of Risk For Ptsd Using Ecological Factors: A Deep Learning Application, Nuriel S. Mor, Kathryn L. Dardeck
Quantitative Forecasting Of Risk For Ptsd Using Ecological Factors: A Deep Learning Application, Nuriel S. Mor, Kathryn L. Dardeck
Journal of Social, Behavioral, and Health Sciences
Forecasting the risk for mental disorders from early ecological information holds benefits for the individual and society. Computational models used in psychological research, however, are barriers to making such predictions at the individual level. Preexposure identification of future soldiers at risk for posttraumatic stress disorder (PTSD) and other individuals, such as humanitarian aid workers and journalists intending to be potentially exposed to traumatic events, is important for guiding decisions about exposure. The purpose of the present study was to evaluate a machine learning approach to identify individuals at risk for PTSD using readily collected ecological risk factors, which makes scanning …