An Evaluation of Impostor Phenomenon in Data Science Students.

Impostor Phenomenon (IP), also called impostor syndrome, involves feelings of perceived fraudulence, self-doubt, and personal incompetence that persist despite one's education, experience, and accomplishments. This study is the first to evaluate the presence of IP among data science students and to evaluate several variables linked to IP simultaneously in a single study evaluating data science. In addition, it is the first study to evaluate the extent to which gender identification is linked to IP. We examined: (1) the degree to which IP exists in our sample; (2) how gender identification is linked to IP; (3) whether there are differences in goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value for different levels of IP; and (4) the extent to which goal orientation, domain identification, perfectionism, self-efficacy, anxiety, personal relevance, expectancy, and value predict IP. We found that most students in the sample showed moderate and frequent levels of IP. Moreover, gender identification was positively related to IP for both males and females. Finally, results indicated significant differences in perfectionism, value, self-efficacy, anxiety, and avoidance goals by IP level and that perfectionism, self-efficacy, and anxiety were particularly noteworthy in predicting IP. Implications of our findings for improving IP among data science students are discussed.

College Students' Reduced Cognitive Empathy and Increased Anxiety and Depression before and during the COVID-19 Pandemic.

This study explored college students' individual mental health (i.e., anxious and depressive symptoms, intrapersonal identity, and ethnic identity), as well as interpersonal mental health, as assessed by their affective connection to and care for others (i.e., cognitive empathy), exploring the role of culture and identity during the twin COVID-19 and racial justice pandemics of 2020. Comparing a longitudinal cohort of 147 undergraduate students' experiences prior to the pandemic (Spring 2019) and after the onset of the pandemic (Spring 2021), the study examines students' mental health changes amidst the multi-layered challenges of this time. A repeated measures Multivariate Analysis of Variance (MANOVA) revealed heightened anxiety and depression scores from pre-pandemic to during the pandemic and a reduction in cognitive empathy as expressed through perspective taking and empathic concern. The study begins to examine the implications of these findings in the COVID-19 era with a focus on young adult mental health, higher education, empathy, and community-mindedness.

Predicting Suicide in Counties: Creating a Quantitative Measure of Suicide Risk.

Rising rates of suicide over the past two decades have increased the need for wide-ranging suicide prevention efforts. One approach is to target high-risk groups, which requires the identification of the characteristics of these population sub-groups. This suicidology study was conducted using large-scale, secondary data to answer the question: using the research on suicide, are there variables studied at the community level that are linked to suicide and are measurable using quantitative, demographic data that are already collected and updated? Data on deaths from suicide in U.S. counties for the years 2000, 2005, 2010 and 2015 were analyzed using multiple regression, longitudinal regression, and cluster analysis. Results indicated that the suicide rate in a county can be predicted by measuring the financial stability of the residents, the quality of mental health in the county, and the economic opportunity in the county. The results are further analyzed using two sociological theories, Social Strain Theory and the Theory of Anomie, and two psychological theories, the Shame Model and the Interpersonal Theory of Suicide.

Pilot Testing a Brief Partner-Inclusive Hybrid Intervention for Perinatal Mood and Anxiety Disorders.

The necessity of hybrid and more accessible options for perinatal mood and anxiety disorders (PMADs) has taken on increased urgency in the wake of the COVID-19 pandemic and its lasting impacts. In the New Family Wellness Project (NFWP), participants engage in a hybrid in-person and teletherapy six-session intervention for new parents early in their postpartum period. This small, phase 1 clinical research examined early outcomes of the NFWP's cognitive behavioral intervention on adverse mental health outcomes (i.e., perinatal depression and anxiety, overall mental illness symptoms) and adaptive outcomes and protective factors (i.e., relational health, social support, flourishing, self-efficacy). Despite a small sample size (N = 12), paired t-tests yielded significant effects for improvements in mental health symptoms at posttest, as well as marginally significant improvements in postpartum anxiety and self-efficacy. Findings suggest the brief, partner-inclusive, hybrid intervention shows promise for further study. Lessons learned from this small phase 1 clinical study and recommendations for revising the intervention prior to future trials are discussed.