Supporting routine cognitive reactivity assessment during the perinatal period: psychometric testing of the Chinese version of the Leiden Index of Depression Sensitivity.

BACKGROUND: It is critical to find optimal forms to identify perinatal depression (PND) and its vulnerable factors and make them more applicable to depression screening. This study aims to evaluate the reliability and validity of the Chinese version of the Leiden Index of Depression Sensitivity (LEIDS-RR-CV) among perinatal women in China and determine the cut-off values for screening for high-risk depression. METHODS: Women in their third trimester of pregnancy and six weeks postpartum completed the LEIDS-RR-CV and a diagnostic reference standard online. We assessed the LEIDS-RR-CV using classical test theory (CTT) and item response theory (IRT). We also assessed the test performance for cut-off scores using receiver operator characteristic analysis to further screen for high-risk depression at each time point. RESULTS: In total, 396 (third trimester) and 321 (six weeks postpartum) women participated. Cronbach's alpha, two-week test-retest reliability, and marginal reliability for the scale were all greater than 0.8. It showed a five-factor model; the cut-off values were 58 (third trimester) and 60 (six weeks postpartum). The areas under the curve were acceptable (≥ 0.7), and the LEIDS-RR-CV was positively correlated with the total Edinburgh Postnatal Depression Scale (EPDS) score (r = 0.52 and 0.56, p = 0.00), indicating its predictive validity. An IRT analysis further confirmed its discriminative validity. CONCLUSIONS: The LEIDS-RR-CV was found to be reliable, valid, and can be used to quantify cognitive reactivity among perinatal Chinese women and for screening for high-risk depression during this period.

Unsanitized and Unfair: How COVID-19 Bailout Funds Refuel Inequity in the US Health Care System.

CONTEXT: The CARES Act of 2020 allocated provider relief funds to hospitals and other providers. We investigate whether these funds were distributed in a way that responded fairly to COVID-19-related medical and financial need. The US health care system is bifurcated into the "haves" and "have nots." The health care safety net hospitals, which were already financially weak, cared for the bulk of COVID-19 cases. In contrast, the "have" hospitals suffered financially because their most profitable procedures are elective and were postponed during the COVID-19 outbreak. METHODS: To obtain relief fund data for each hospital in the United States, we started with data from the HHS website. We use the RAND Hospital Data tool to analyze how fund distributions are associated with hospital characteristics. FINDINGS: Our analysis reveals that the "have" hospitals with the most days of cash on hand received more funding per bed than hospitals with fewer than 50 days of cash on hand (the "have nots"). CONCLUSIONS: Despite extreme racial inequities, which COVID-19 exposed early in the pandemic, the federal government rewards those hospitals that cater to the most privileged in the United States, leaving hospitals that predominantly serve low-income people of color with less.