Filtering by
- All Subjects: Mental illness
- Creators: Jimenez Arista, Laura
- Member of: Theses and Dissertations
- Resource Type: Text
- Status: Published
We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.
The purpose of this thesis was two-fold: 1) to perform a systematic review and collect information from articles that used music interventions or music programs to address the mental health needs of families and adolescents, and 2) to develop a family music therapy program for teenagers with mental health concerns based on the research literature used for the systematic review. Fourteen articles were included in the study. The main interventions and programs were improvisation (n = 6), songwriting (n = 3), lyric analysis or song discussions on client-selected music for introspective and expressive purposes (n = 3), therapeutic singing (n =1) and structured group music making (n = 1). Common outcomes included improvement in the adolescents' self-expression and communication, restoration of family relationships, increased awareness of covert family issues, and improved family communication and interactions. The proposed six-week music therapy program is improvisation-based, considering the amount of improvisational interventions that were found in research. Session plans include interventions such as musical “icebreakers” and warm-ups, improvisation, lyric analysis, and a culminating songwriting experience.
Keywords: family therapy, music therapy, adolescents, mental illness
The field of veterinary medicine can be rewarding, but also very demanding. Research has shown that many practicing veterinarians struggle with mental illness, and the profession has one of the highest suicide rates in the United States. Research has also shown that many veterinary students struggle with mental illness. It is important to further research the mental health of veterinary students and how that can correlate with one's mental health as a practicing veterinarian. The purpose of this project is to summarize findings of the literature concerning the mental health of veterinary students and to present a new resource, the Wisdom Vet app, that can potentially support the well-being of veterinary students.