Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Associations between Classical Music, Physical Activity and Symptoms of Depression in Older Adults during the COVID-19 Pandemic(2023) Arnold-Nedimala, Naomi A; Smith, J Carson; Kinesiology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Background: The initial lockdown in March 2020 due to COVID-19 rattled the residents of North America as normalcy came to a standstill, freedom was stripped away, and people were forced to adapt to new restrictions and regulations, simply to survive. The elderly population was greatly affected by the lockdown as it prohibited those living in assisted living facilities to physically interact with family and friends highlighting the need to identify protective behaviors against mental health and depression. The neurological benefits of listening to classical music is an emerging area of research. A few studies suggest the positive outcomes of listening to classical music in reducing symptoms of depression. Additionally, while the cardiovascular benefits of exercise are well known, the impact of exercise on affect continues to be an emerging area of research. Purpose: The purpose of this study is to understand the efficacy of listening to classical music in attenuating symptoms of depression in older adults (50 – 90+) utilizing data collected from 3 separate time points during the COVID-19 pandemic, and to determine if physical activity is associated with providing additional benefit to lowering symptoms of depression Methods: A survey including the Geriatric Depression Scale (GDS), the Physical Activity Scale for the Elderly (PASE), and questions about listening to music (classical, Broadway, Christian music), and the frequency of listening to music was generated and distributed to people living in the United States and Canada immediately following the initial COVID-19 lockdown in April 2020. Informed consent was obtained prior to completing the survey, and participants who were interested in receiving a follow-up survey were asked to provide their email addresses. The follow-up surveys were generated 4-months (August 2020) and one year (April 2021) after the initial survey. Results: At the initial onset of the COVID-19 lockdown in April 2020, significant associations were observed between classical music listening (CML) and lower symptoms of depression, physical activity (PA) and lower symptoms of depression, music listening frequency, and lower symptoms of depression. In August 2020 and April 2021, significant associations were found between physical activity and lower symptoms of depression. However, no associations were observed between classical music listening and lower symptoms of depression, and music listening frequency and lower symptoms Additionally, significant associations were observed between age and lower symptoms of depression, sex, and lower symptoms of depression at all three time points. Conclusion: The results from our study suggest that there is an association between classical music listening and symptoms of depression, physical activity and symptoms of depression, music listening frequency and symptoms of depression in older adults (50+) during the early stages of the COVID-19 pandemic (April 2020). Additionally, the association between physical activity and symptoms of depression was maintained throughout the first year of the pandemic as supported by the data collected in August 2020 (4 months) and April 2021 (12-months).Item Generalizable Depression Detection and Severity Prediction Using Articulatory Representations of Speech(2022) Seneviratne, Nadee; Espy-Wilson, Carol; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Major Depressive Disorder (MDD) is a mental health disorder that has taken a massive toll on society both socially and financially. Timely diagnosis of MDD is extremely crucial to minimize serious consequences such as suicide. Hence automated solutions that can reliably detect and predict the severity of MDD can play a pivotal role in assisting healthcare professionals in providing timely treatments. MDD is known to affect speech. Leveraging on the changes in speech characteristics that occur due to depression, a lot of vocal biomarkers are being developed to detect depression. However, the study into changes in articulatory coordination associated with depression is under-explored. Speech articulation is a complex activity that requires finely timed coordination across articulators. In a depressed state involving psychomotor slowing, this coordination changes and in turn modifies the perceived speech signal. In this work, we use a direct representation of articulation known as vocal tract variables (TVs) to capture the coordination between articulatory gestures. TVs define the constriction degree and location of articulators (tongue, jaw, lips, velum and glottis). Previously, correlation structure of formants or mel-frequency cepstral coefficients (MFCCs) were used as a proxy for underlying articulatory coordination. We compute the articulatory coordination features (ACFs) which provide details about the correlation among time-series data at different time delays and are therefore rich with information about the underlying coordination level of speech production. Using the rank-ordered eigenspectra obtained from TV based ACFs, we show that depressed speech depicts simpler coordination relative to the speech of the same subjects when in remission which is inline with previous findings. By conducting a preliminary study using a small subset of speech from subjects who transitioned from being severely depressed to being in remission, we show that TV based ACFs outperform formant based ACFs in binary depression classification. We show that depressed speech has reduced variability in terms of reduced coarticulation and undershoot. To validate this, we present a comprehensive acoustic analysis and results of a speech-in-noise perception study to compare the intelligibility of depressed speech relative to not-depressed speech. Our results indicate that depressed speech is at least as intelligible as not-depressed speech. The next stage of our work focuses on developing deep learning based models using TV based ACFs to detect depression and attempts to overcome the limitations in existing work. We combine two speech depression databases with different characteristics which helps to increase the generalizability which is a key objective of this research. Moreover, we segment audio recordings prior to feature extraction to obtain data volumes required to train deep neural networks. We reduce the dimensionality of conventional stacked ACFs of multiple delay scales by using refined ACFs which are carefully curated to remove redundancies and using the strengths of dilated Convolutional Neural Networks. We show that models trained on TV based ACFs are more generalizable compared to its proxy counterparts. Then we develop a multi-stage convolutional recurrent neural network that performs classification at the session-level. We derive the constraints under which this segment-to-session level approach could be used to boost the classification performance. We extend our models to perform depression severity level classification. The TV based ACFs outperform other feature sets in this task as well. The language pattern and semantics can reveal vital information regarding a person's mental state. We develop a multimodal depression classifier which incorporates TV based ACFs and hierarchical attention based text embeddings. The fusion strategy of the proposed architecture enables segmenting data from different modalities independently (overlapping segments for audio and sentences for text), in the most optimal way for each modality, when performing segment-to-session level classification. The multimodal classifier clearly performs better than the unimodal classifiers. Finally, we develop a multimodal system to predict the depression severity score, which is a more challenging regression problem due to the quasi-numerical nature of the scores. Multimodal regressor achieves the lowest root mean squared error showing the synergies of combining multiple modalities such as audio and text. We perform an exhaustive error analysis that reveals potential improvements to be made in the future. The work in this dissertation takes a step forward towards the betterment of humanity by exploring the development of technologies to improve the performance of speech based depression assessment, utilizing the strengths of the ACFs derived from direct articulatory representations.Item THE STATE OF GRADUATE STUDENT MENTAL HEALTH IN THE UNITED STATES: ELEVEN YEARS AND 200,000 STUDENTS(2020) DeYoung, Kathryn Alyce; Leslie, Leigh A; Shackman, Alexander J; Family Studies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Graduate students are an essential part of the academic enterprise. Converging lines of evidence suggests that many graduate students experience high levels of emotional distress. Yet the true depth and breadth of this public health “crisis” has remained unclear. The present study used survey data collected from 187,427 American graduate students between 2008 and 2019 as part of the ACHA-NCHA II to demonstrate that moderate-to-severe emotional distress, psychiatric illness, and suicidality are common among graduate students. Remarkably nearly 1 in 3 students were diagnosed with or treated for one or more psychiatric disorders. Notably, every indicator of emotional distress and illness increased over the past decade, in some cases substantially, above and beyond contemporaneous shifts in demographic and institutional characteristics. This study represents the most comprehensive assessment to date, provides crucial information for refining research and policy, and sets the stage for efforts aimed at developing effective intervention strategies.Item Depression and Perception of Family Cohesion Levels and Social Support from Friends in Emerging Adulthood at a University Mental Health Clinic(2020) Roc, Sabrina; Barros, Patricia; Family Studies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Emerging adulthood is identified as a period of transition and uncertainty that occurs between the stages of adolescence and adulthood, often from ages 18-25. During this period, mental health issues are quite prominent, especially symptoms of depression. Previous research has explored what can ease the stress of depressive symptoms, and social support has had resounding effects. The present study used secondary analysis of data from 372 therapy-seeking individuals at a university-based family clinic to evaluate how perceived levels of familial cohesion and social support from friends are associated with depressive symptoms during emerging adulthood and whether or not age moderated the association. The results of this study show significant associations between familial cohesion as predicted, and social support from friends but in an unexpected direction. Age did not appear to have any significant associations. Potential future research as well as clinical implications are discussed.Item Restoration Space: Designing for Improved Workplace Culture and Health(2020) Knoebel, Adam Thomas; Simon, Madlen; Architecture; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Depression, as the leading cause of disability in the United States among people ages 15 - 44 and the top workplace issue. The goal of this thesis is to explore and identify strategies for designing for depression in the workplace. It aims to develop further the relationship between the built environment and the process of managing the vast symptoms and causes of workplace depression, stress, and anxiety. The goal will be to create spaces that encourage connection to nature, sensory comfort, physical wellness, and building social relations as a part of the solution. By understanding the difficulty of depression in the workplace and how those with depression react to their surroundings this thesis aims to design for health, engagement, and happiness.Item SURVIVING THE STORM: AN INTERSECTIONAL ANALYSIS OF HURRICANE KATRINA’S EFFECT ON LINGERING PHYSICAL AND MENTAL HEALTH DISPARITIES(2020) DeLoatch, Nicole T.; Rendall, Michael S; Sociology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This three-paper dissertation used an intersectional analytical framework to examine disparities in physical health and mental health (respectively) for Hurricane Katrina survivors by race and gender. To do so, health outcomes for New Orleans residents who survived Hurricane Katrina were analyzed. Displaced New Orleans Resident Survey (DNORS) data was used to investigate if natural disasters exacerbate health disparities. In Chapter 2, eight waves of self-reported data from the nationally-representative Panel Study of Income Dynamics (PSID) were used to conduct a sensitivity analysis of self-reported diagnoses. This was done to determine if there are differences by race and sex in the accuracy of self-reports. Chapter 2's analysis indicates that the intersections of race and sex were not associated with reporting variability after accounting for proxy status and class related characteristics. In Chapters 3 and 4, we determine if significant increases to physical and mental health diagnosis vary by race and sex, following Hurricane Katrina. The main finding of Chapter 3 was that Black women were more likely to report negative physical health outcomes than their White or male counterparts, both before and after Hurricane Katrina. Chapter 4's main finding was that Black women were not more likely to report a diagnosis of negative emotional problem and depression post-Katrina when compared to their White or male counterparts. There were increased adverse mental health outcomes across all four race-sex groups.Item VICTIM DEPRESSION, POSITIVE PARTNER BEHAVIOR, AND TYPE OF PARTNER AGGRESSION AS DETERMINANTS OF WOMEN’S STEPS TOWARD LEAVING AN ABUSIVE RELATIONSHIP(2019) Thomas, Jannel; Epstein, Norman B; Family Studies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This study investigated factors associated with the degree to which victims of partner violence take steps toward leaving the relationship. It was a secondary analysis of clinic data from pre-therapy couple assessments of demographic characteristics; physical, psychological, and sexual partner aggression; victim depression; perpetrator positive partner behavior; and steps the victim took toward leaving. Females’ income and education were not associated with steps toward leaving. Physical, psychological, and sexual aggression were all associated with steps toward leaving. Greater depression was associated with more steps toward leaving and more positive partner behavior was associated with fewer steps toward leaving. Neither depression nor positive partner behavior moderated the association between physical or psychological aggression and steps toward leaving. The association between sexual aggression and steps toward leaving was positive when positive partner behavior was higher, but non-significant when positive partner behavior was lower. Clinical implications and suggestions for future research are discussed.Item Understanding Secondary Educators’ Knowledge of Mental Health and Their Perceptions of Their Role in Addressing Student Mental Health(2019) Ross, Ana-Sophia; Wang, Cixin; Psychology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Adolescents have significant unmet mental health needs and schools represent the most common place for youth to receive mental health services. Teachers are primarily responsible for recognizing and working with students with mental health needs. Scholarship has investigated teachers’ knowledge pertaining to signs and symptoms for mental illness and found that teachers report little confidence in their knowledge, and have difficulty accurately identifying students struggling with mental illness. Research has provided some insight into how teachers can promote positive mental health amongst their students but little is known about classroom educators’ perceptions about how they can address student mental health concerns. Thus, this qualitative study utilized thematic analysis to investigate 27 teacher/classroom educators’ perceptions about how they can help students who struggle with mental health problems. Five main themes emerged from the analysis: 1) school collaboration, 2) student support, 3) family involvement/family-school partnership, 4) school reform/systematic change, and 5) teacher professional development training. Additionally, the study also investigated educator’s knowledge of signs and symptoms of depression, anxiety, and eating disorders. Eighty-five percent of teachers were able to correctly identify depression from a vignette while all participants were able to identify an eating disorder from a vignette. This study provides insights about how to improve school-based mental health efforts, with specific attention to classroom-based educators’ role in the provision of services.Item Medial Frontal Theta Negativities (MFTN) as Predictors of Anxiety Sensitivity Treatment Response(2019) Ellis, Jessica Steward; Bernat, Edward M; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Anxiety is one of the most prevalent mental health problems around the world. Despite a number of widely available interventions, it can take weeks or months to see effects, and nearly half of individuals may not respond. In an effort to better understand response rates, a large body of evidence indicates the most consistent predictor of treatment outcomes is activity in the anterior cingulate cortex (ACC). Although activity in ACC can be measured by medial frontal theta event related potentials (ERPs) at a finer temporal resolution, these neurophysiological components have not been evaluated as predictors of treatment response. There is also a lack of research on the functional networks associated with ACC treatment prediction, despite implications for prefrontal engagement of cognitive control processes. The present study aimed to examine these gaps in the literature by using task-based electroencephalography (EEG) and medial frontal theta negativities (MFTN) as predictors of anxiety sensitivity treatment response. Using amplitude as well as functional connectivity measures (i.e., inter-channel phase synchrony), baseline MFTN (i.e., Theta-FN, Theta-N2) were assessed as predictors of treatment response at mid-treatment, 1-week post treatment, and 6 months post treatment. Subjects underwent a baseline EEG before completing three sessions of a computerized cognitive behavioral intervention. Contrary to the hypothesis, findings revealed MFTN amplitude did not predict treatment response. However, medial to lateral prefrontal theta phase synchrony demonstrated significant prediction effects, such that lower phase synchrony was associated with greater symptom improvement at mid-treatment, 1-week post treatment, and 6 months post treatment. This effect was specific to certain task conditions (i.e., gain feedback and go stimuli), as well as to the combined anxiety and depression treatment group. Results demonstrated accuracy and consistency of treatment prediction, as well as incremental validity after controlling for self-report measures. Finally, results provide additional support for a convergent medial frontal theta process, and suggest that low engagement of regulatory and proactive control mechanisms may be predictive of better response to cognitive behavioral interventions. This work represents a novel finding that may contribute to the improvement in treatment efficacy by serving as a target for future interventions and individualized treatment selection.Item Perceived Ethnic-Racial Socialization and Parenting Styles on Asian American College Students' Depressive Symptoms(2018) Ahn, Lydia HaRim; Miller, Matthew J; Counseling and Personnel Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The present study examines how perceived mothers’ culturally relevant parenting styles and ethnic-racial socialization (ERS) are associated with depressive symptoms among 280 Asian American college students (M =19.53, SD = 1.57). We hypothesized that perceived ERS will predict depressive symptoms, and perceived authoritarian, authoritative, and training parenting styles will moderate this association. We used a cross-sectional, quantitative design to measure this model through an online questionnaire. Depressive symptoms were dependent on the parenting style and the type of ERS message. Results indicated that 1) training parenting style (high in guidance and care for children) was negatively associated with depressive symptoms, 2) the combination of promotion of equality messages and training parenting style was negatively linked with depressive symptoms, and 3) authoritarian parenting was positively correlated with depressive symptoms. Findings highlight the importance of culturally sensitive parenting on mental health.
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