Medicine and Health Sciences Commons^™

Improving Mental Health Documentation Through Education: An Intervention For Level Of Care Utilization System (Locus) Use In Psychiatric Crisis Placement, Lauren Ozimek

College of Nursing and Health Sciences Doctor of Nursing Practice (DNP) Project Publications

Purpose: The Community Mental Health Act (1963) created crisis stabilization units to lessen burdens of emergency departments addressing psychiatric crises. Crisis stabilization units – including the project site – evaluate treatment efficacy via assessments including the Level of Care Utilization System (LOCUS). The LOCUS is totaled into a composite score, expected to decrease at treatment completion. The project site has not consistently seen LOCUS scores decrease at completion. The project’s purpose was to improve use of a clinical assessment tool to reflect treatment and progress for patients utilizing crisis stabilization programs. A secondary aim was to increase incidence (75%) of …

Adolescent Suicide Prevention Via Parental Education, Junelle Shepard, Mary Val Palumbo

College of Nursing and Health Sciences Doctor of Nursing Practice (DNP) Project Publications

Purpose. Up to 24% of children from the ages of 12 to 17 have reported suicidal ideation, with 7-11% reporting at least one suicide attempt in the past 12 months (Hetrick, 2017). In a study by Jones et al (2019) over 50% of parents were unaware their child was exhibiting suicidal ideation. This project aims to increase community awareness of suicidal ideation and teach community members how to talk with adolescents about this sensitive topic.

Methods. Five online training sessions were offered in Fall 2021, with each session lasting 90 minutes. Using Smith et al.’s Suicide Knowledge and Skills Questionnaire, …

Using Word Embeddings To Explore The Language Of Depression On Twitter, Sandhya Gopchandani

Graduate College Dissertations and Theses

How do people discuss mental health on social media? Can we train a computer program to recognize differences between discussions of depression and other topics? Can an algorithm predict that someone is depressed from their tweets alone? In this project, we collect tweets referencing “depression” and “depressed” over a seven year period, and train word embeddings to characterize linguistic structures within the corpus. We find that neural word embeddings capture the contextual differences between “depressed” and “healthy” language. We also looked at how context around words may have changed over time to get deeper understanding of contextual shifts in the …