Filtering by
- All Subjects: Stress
- All Subjects: Social Conflict
- Creators: Roberts, Nicole
- Status: Published
South Asian students are known for having immense pressure on them due to parental expectation and oftentimes that stress can present in psychosomatic symptoms. This investigation aimed to better understand the physical presentations of stress and how South Asians compare to their white peers. An online study was conducted with both South Asian (n = 15) and White (n = 58) individuals that use the Perceived Stress Scale and the New York State United Teachers physical stress assessment to understand the differences in stress. It was found that South Asians have a higher average perceived stress core of 25 versus 20 for whites and experience headaches, sore neck, an overall feeling of worry and anxiety, and diarrhea more frequently than their white counterparts. This suggests that South Asians may in fact have more psychosomatic manifestations of stress. It is posited that this is due to South Asian students not having an adequate outlet in which they can express negative emotions.
After controlling for demographic variables, mediational analysis revealed that perceived social support explained the relation between perceived child disability and depression and anxiety. Additionally, it partially explained the relation between perceived family burden and depression, anxiety, and stress. Further, parent perception of their child's disability and perceived family burden did not predict emotion-focused or social support coping. However, both emotion-focused and social support coping behaviors were related to reductions in depression in this sample.
This paper’s field of study falls into the cross section of geology and fire science, history, social conflict, public service ethics, and collaborative failures. I explore how a series of small choices snowballed into a full, government funded relocation effort after attempts at controlling the anthracite coal seam fire failed. Geology and fire science worked in tandem during the mine fire, influencing each other and complicating the firefighting efforts. The fire itself was a unique challenge. The history of Centralia played a large role in the government and community response efforts. I use the borough and regional history to contextualize the social conflict that divided Centralia. Social conflict impaired the community’s ability to unify and form a therapeutic community, and in turn, it damaged community-government relationships. The government agencies involved in the mine fire response did their own damage to community relationships by pursuing their own interests. Agencies worried about their brand image, and politicians worried about re-election. I study how these ethical failures impacted the situation. Finally, I look at a few examples of collaborative failures on behalf of the government and the community. Over the course of my research, it became apparent the people killed Centralia, not the fire.
As threats emerge, change, and grow, the life of a police officer continues to intensify. To help support police training curriculums and police cadets through this critical career juncture, this study proposes a state of the art approach to stress prediction and intervention through wearable devices and machine learning models. As an integral first step of a larger study, the goal of this research is to provide relevant information to machine learning models to formulate a correlation between stress and police officers’ physiological responses on and off on the job. Fitbit devices were leveraged for data collection and were complemented with a custom built Fitbit application, called StressManager, and study dashboard, termed StressWatch. This analysis uses data collected from 15 training cadets at the Phoenix Police Regional Training Academy over a 13 week span. Close collaboration with these participants was essential; the quality of data collection relied on consistent “syncing” and troubleshooting of the Fitbit devices. After the data were collected and cleaned, features related to steps, calories, movement, location, and heart rate were extracted from the Fitbit API and other supplemental resources and passed through to empirically chosen machine learning models. From the results of these models, we formulate that events of increased intensity combined with physiological spikes contribute to the overall stress perception of a police training cadet