Correlates of verbal and physical violence experienced and perpetrated among cisgender college women: serial cross-sections during one year of the COVID-19 pandemic.

Introduction: Violence against women is a prevalent, preventable public health crisis. COVID-19 stressors and pandemic countermeasures may have exacerbated violence against women. Cisgender college women are particularly vulnerable to violence. Thus, we examined the prevalence and correlates of verbal/physical violence experienced and perpetrated among cisgender women enrolled at a New York City college over one year during the COVID-19 pandemic. Methods: From a prospective cohort study, we analyzed data self-reported quarterly (T1, T2, T3, T4) between December 2020 and December 2021. Using generalized estimated equations (GEE) and logistic regression, we identified correlates of experienced and perpetrated violence among respondents who were partnered or cohabitating longitudinally and at each quarter, respectively. Multivariable models included all variables with unadjusted parameters X 2 p-value ≤0.05. Results: The prevalence of experienced violence was 52% (T1: N = 513), 30% (T2: N = 305), 33% (T3: N = 238), and 17% (T4: N = 180); prevalence of perpetrated violence was 38%, 17%, 21%, and 9%. Baseline correlates of experienced violence averaged over time (GEE) included race, living situation, loneliness, and condom use; correlates of perpetrated violence were school year, living situation, and perceived social support. Quarter-specific associations corroborated population averages: living with family members and low social support were associated with experienced violence at all timepoints except T4. Low social support was associated with higher odds of perpetrated violence at T1/T3. Other/Multiracial identity was associated with higher odds of violence experience at T3. Conclusions: Living situation was associated with experienced and perpetrated violence in all analyses, necessitating further exploration of household conditions, family dynamics, and interpersonal factors. The protective association of social support with experienced and perpetrated violence also warrants investigation into forms of social engagement and cohesion. Racial differences in violence also require examination. Our findings can inform university policy development on violence and future violence research. Within or beyond epidemic conditions, universities should assess and strengthen violence prevention and support systems for young women by developing programming to promote social cohesion.

Correlates of psychological distress among undergraduate women engaged in remote learning through a New York City college during the COVID-19 pandemic.

OBJECTIVE: The study's objective is to explore psychological distress (PD) among remote learners during COVID-19. PARTICIPANTS: Female undergraduates matriculated at an NYC college in Winter 2020. METHODS: Using the Kessler-6 scale, we defined PD as no/low (LPD), mild/moderate (MPD), and severe (SPD) and assessed if residing in/near NYC modified associations. RESULTS: PD was common (MPD: 34.1%, SPD: 38.9%). Students identifying as Other/Multiracial had lower MPD odds (aOR = 0.39 [0.17-0.88]). SPD was associated with identifying as White (aOR = 2.02 [1.02-3.99]), unbalanced meals (aOR = 2.59 [1.06-6.30]), violence experience (aOR = 1.77 [1.06-2.94]), no social support (aOR = 3.24 [1.37-7.64]), and loneliness (aOR = 2.52 [1.29-4.95]). Among students in/near NYC, moderate/high drug use (aOR = 2.76 [1.15-6.61]), no social support (aOR = 3.62 [1.10-1.19]), and loneliness (aOR = 2.92 [1.11-7.63]) were SPD correlates. CONCLUSIONS: PD was high and associated with food insecurity, violence experience, no social support, and loneliness. Living in/near NYC modified drug use, loneliness, and social support associations. Mental health initiatives should address modifiable risk factors to ameliorate pandemic-associated PD.

Supervised Machine Learning Approach to Identify Early Predictors of Poor Outcome in Patients with COVID-19 Presenting to a Large Quaternary Care Hospital in New York City.

BACKGROUND: The progression of clinical manifestations in patients with coronavirus disease 2019 (COVID-19) highlights the need to account for symptom duration at the time of hospital presentation in decision-making algorithms. METHODS: We performed a nested case-control analysis of 4103 adult patients with COVID-19 and at least 28 days of follow-up who presented to a New York City medical center. Multivariable logistic regression and classification and regression tree (CART) analysis were used to identify predictors of poor outcome. RESULTS: Patients presenting to the hospital earlier in their disease course were older, had more comorbidities, and a greater proportion decompensated (<4 days, 41%; 4-8 days, 31%; >8 days, 26%). The first recorded oxygen delivery method was the most important predictor of decompensation overall in CART analysis. In patients with symptoms for <4, 4-8, and >8 days, requiring at least non-rebreather, age ≥ 63 years, and neutrophil/lymphocyte ratio ≥ 5.1; requiring at least non-rebreather, IL-6 ≥ 24.7 pg/mL, and D-dimer ≥ 2.4 µg/mL; and IL-6 ≥ 64.3 pg/mL, requiring non-rebreather, and CRP ≥ 152.5 mg/mL in predictive models were independently associated with poor outcome, respectively. CONCLUSION: Symptom duration in tandem with initial clinical and laboratory markers can be used to identify patients with COVID-19 at increased risk for poor outcomes.