States across the country have been experiencing a steady decline in public health nursing workforce, including North Carolina (NC). Objectives: To better understand retention in the NC Public Health Nurses (PHNs) workforce through an assessment of perceptions of the working environment, stress, intent to stay, and job satisfaction. Design: A cross‐sectional online survey using closed and open‐ended questions. Sample: The study population comprised of non‐supervisory PHNs (n = 672) working at NC local health departments (LHD). Measurements: Retention problem, working environment, and job satisfaction measures were adapted from the revised Casey‐Fink Registered Nurse Retention Survey© (2009) to fit public health settings. Results: Despite high levels of job satisfaction (79.76%, n = 473), 53% of respondents (n = 323) acknowledged a retention problem within their LHD; 35.32% (n = 203) planned to/considered leaving their position in the next 3 years for reasons other than retirement. ANOVAs and Kruskal Wallis Test results showed that those planning to leave had statistically lower scores on perceived working environment and job satisfaction and demonstrated higher negative stress levels. Conclusion: Like other states, NC is experiencing a PHN shortages predicted to worsen in coming years. To retain the current workforce, LHDs need to work to improve PHNs working environment, increase PHNs’ pay, and alleviate stressors.

The novel coronavirus (COVID-19) pandemic presents a severe threat to human health worldwide. The United States (US) has the highest number of reported COVID-19 cases, and over 16 million people were infected up to the 12 December 2020. To better understand and mitigate the spread of the disease, it is necessary to recognize the pattern of the outbreak. In this study, we explored the patterns of COVID-19 cases in the US from 1 March to 12 December 2020. The county-level cases and rates of the disease were mapped using a geographic information system (GIS). The overall trend of the disease in the US, as well as in each of its 50 individual states, were analyzed by the seasonal-trend decomposition. The disease curve in each state was further examined using K-means clustering and principal component analysis (PCA). The results showed that three clusters were observed in the early phase (1 March–31 May). New York has a unique pattern of the disease curve and was assigned one cluster alone. Two clusters were observed in the middle phase (1 June–30 September). California, Texas and Florida were assigned in the same cluster, which has the pattern different from the remaining states. In the late phase (1 October–12 December), California has a unique pattern of the disease curve and was assigned a cluster alone. In the whole period, three clusters were observed. California, Texas and Florida still have similar patterns and were assigned in the same cluster. The trend analysis consolidated the patterns identified from the cluster analysis. The results from this study provide insight in making disease control and mitigation strategies.

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Primary care providers’ (PCPs) implicit and explicit bias can adversely affect health outcomes of lesbian women including their mental health. Practice guidelines recommend universal screening for depression in primary care settings, yet the guidelines often are not followed. The intersection of PCPs’ implicit and explicit bias toward lesbian women may lead to even lower screening and diagnosis of depression in the lesbian population than in the general population. The purpose of this secondary analysis was to examine the relationship between PCPs’ implicit and explicit bias toward lesbian women and their recommendations for depression screening in this population. PCPs ( n = 195) in Kentucky completed a survey that included bias measures and screening recommendations for a simulated lesbian patient. Bivariate inferential statistical tests were conducted to compare the implicit and explicit bias scores of PCPs who recommended depression screening and those who did not. PCPs who recommended depression screening demonstrated more positive explicit attitudes toward lesbian women ( p < .05) and their implicit bias scores were marginally lower than the providers who did not recommend depression screening (p = .068). Implications for practice: Depression screening rates may be even lower for lesbian women due to implicit and explicit bias toward this population. Training to increase providers’ awareness of bias and its harm is the first step to improve primary care for lesbian women. Policies must protect against discrimination based on sexual orientation or gender identity.

Purpose Women who receive an abnormal Pap result may experience negative psychological factors. The purpose of this study is to assess the baseline occurrence of negative psychological factors and evaluate the relationships between psychological factors and demographic characteristics among Appalachian women who received abnormal Pap results. Methods We conducted a secondary analysis of data collected from Appalachia Kentucky women (N = 521) ages ≥18 enrolled in an intervention. Data included sociodemographics, Beck depression and anxiety inventories, fatalism, and personal control measures. Multiple variable logistic regression was used to investigate the association between demographics and psychological factors. Findings Participants were predominantly White (96.2%), with mean age 28.93 ± 11.03 years, and the majority (77%) had yearly income below $20,000. Depression was reported by 34.6% (n = 173); 10% (n = 50) experienced moderate or severe anxiety; 20.6% (n = 107) had fatalistic beliefs; and 55.1% (n = 289) believed they lacked personal control over cancer. Women with lower income had higher occurrence of depression (P = .003). Women with moderate to severe anxiety were significantly older than those with low to moderate depression (34.44 vs 28.34, P < .001). Controlling for other variables, as age increased, the odds of fatalistic beliefs increased, OR (95%) = 1.042 (1.022, 1.062). When education level increased, the odds of fatalistic beliefs decreased, OR (95%) = 0.873 (0.800, 0.952). Conclusions Given the high occurrence of depression, anxiety, and fatalistic beliefs among this population, health care providers should assess for underlying mental health diagnoses and psychological distress during each patient encounter and provide recommendations to address them.