Filtering by
- All Subjects: Depression
- Creators: Department of Psychology
- Creators: School of International Letters and Cultures
The Beck Depression Inventory II (BDI-II) and the Patient Health Questionnaire 9 (PHQ-9) are highly valid depressive testing tools used to measure the symptom profile of depression globally and in South Asia, respectively (Steer et al., 1998; Kroenke et al, 2001). Even though the South Asian population comprises only 23% of the world’s population, it represents one-fifth of the world’s mental health disorders (Ogbo et al., 2018). Although this population is highly affected by mental disorders, there is a lack of culturally relevant research on specific subsections of the South Asian population.<br/><br/>As such, the goal of this study is to investigate the differences in the symptom profile of depression in native and immigrant South Asian populations. We investigated the role of collective self-esteem and perceived discrimination on mental health. <br/><br/>For the purpose of this study, participants were asked a series of questions about their depressive symptoms, self-esteem and perceived discrimination using various depressive screening measures, a self-esteem scale, and a perceived discrimination scale.<br/><br/>We found that immigrants demonstrated higher depressive symptoms than Native South Asians as immigration was viewed as a stressor. First-generation and second-generation South Asian immigrants identified equally with somatic and psychological symptoms. These symptoms were positively correlated with perceived discrimination, and collective self-esteem was shown to increase the likelihood of these symptoms.<br/><br/>This being said, the results from this study may be generalized only to South Asian immigrants who come from highly educated and high-income households. Since seeking professional help and being aware of one’s mental health is vital for wellbeing, the results from this study may spark the interest in an open communication about mental health within the South Asian immigrant community as well as aid in the restructuring of a highly reliable and valid measurement to be specific to a culture.
The relevance of depression in the clinical realm is well known, as it is one of the most common mental disorders in the United States. Clinical depression is the leading cause of disease for women worldwide. The sex difference in depression and anxiety has guided the research of not just recent studies but older studies as well, supporting the theory that gonadal hormones are associated with the mechanisms of emotional cognition. The scientific literature points towards a clear correlative relationship between gonadal hormones, especially estrogens, and emotion regulation. This thesis investigates the neural pathways that have been indicated to regulate mood and anxiety. Currently, the research points to the hypothalamic-pituitary-adrenal axis, which regulates the stress response through its ultimate secretion of cortisol through the adrenal cortex, and its modulated response when exposed to higher levels of estrogen. Another mechanism that has been investigated is the interaction of estrogen and the serotonergic system, which is noteworthy because the serotonergic system is known for its importance in mood regulation. However, it is important to note that the research seeking to determine the neurobiological underpinnings of estrogen and the serotonergic system is not expansive. Future research should focus on determining the direct relationship between cortisol hypersecretion and estrogens, the specific neurobiological effects of serotonergic receptor subtypes on the antidepressant actions of estrogens, and the simultaneous effects of the stress and serotonergic systems on depressive symptoms.
Graduating from college is an important time of life transitions and career development for undergraduates and their future. Future self-identification, the connection between an individual’s current and future self, can negatively predict depression and utilize self-control as a mechanism to achieve later academic goals. Investigating an individual’s future self- identification, depression scores, and behavioral outcomes in the face of the COVID-19 pandemic can help optimize college graduate success in an uncertain world. The present study aimed to (1) determine if earlier future self-identification moderated the changes between later outcomes (e.g., depression, perceived alcohol consumption, and academic and career goals) from pre-COVID-19 to during COVID-19, (2) investigate if psychological resources (e.g., self-control and emotion regulation) had any intermediary effects between earlier future self-identification and later depression and behavioral outcomes during the pandemic, and (3) test for any moderation effects of future self-identification on the relationship between available psychological resources before COVID-19 and during COVID-19. The present research demonstrated that students with greater earlier future self-identification were less likely to change their academic and career goals and were less likely to experience symptoms of depression during the pandemic. Additionally, self-control was demonstrated as an intermediary factor between earlier future self-identification and later academic and career goal changes. These findings may help college graduates develop resilience in other stressful situations.
The recent popularity of ChatGPT has brought into question the future of many lines of work, among them, psychotherapy. This thesis aims to determine whether or not AI chatbots should be used by undergraduates with depression as a form of mental healthcare. Because of barriers to care such as understaffed campus counseling centers, stigma, and issues of accessibility, AI chatbots could perhaps bridge the gap between this demographic and receiving help. This research includes findings from studies, meta-analyses, reports, and Reddit posts from threads documenting people’s experiences using ChatGPT as a therapist. Based on these findings, only mental health AI chatbots specifically can be considered appropriate for psychotherapeutic purposes. Certain chatbots that are designed purposefully to discuss mental health with users can provide support to undergraduates with mild to moderate symptoms of depression. AI chatbots that promise companionship should never be used as a form of mental healthcare. ChatGPT should generally be avoided as a form of mental healthcare, except to perhaps ask for referrals to resources. Non mental health-focused chatbots should be trained to respond with referrals to mental health resources and emergency services when they detect inputs related to mental health, and suicidality especially. In the future, AI chatbots could be used to notify mental health professionals of reported symptom changes in their patients, as well as pattern detectors to help individuals with depression understand fluctuations in their symptoms. AI more broadly could also be used to enhance therapist training.