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The coronavirus disease (COVID-19) pandemic has exposed nurses to conditions that threaten their health, well-being, and ability to work. It is therefore critical to study nurses’ experiences and well-being during the current crisis in order to identify risk groups for ill health and potential sources of organizational intervention. The aim of this study was to explore perceptions of the most salient sources of stress in the early stages of the coronavirus pandemic in a sample of U.S. nurses. A cross-sectional online survey was conducted among a sample of 695 U.S. nurses in May 2020. Content analysis was conducted on nurses’ responses (n = 455) to an open-ended question on the most stressful situations they had experienced during the pandemic. Six distinct themes emerged from the analysis: exposure/infection-self; illness/death-others; workplace; personal protective equipment/supplies; unknowns; opinions/politics. Two sub-themes concerned restrictions associated with the pandemic and feelings of inadequacy/helplessness regarding patients and their treatment. More than half of all comments concerned stress related to problems in workplace response to the pandemic. Healthcare institutions should provide opportunities for nurses to discuss the stress they are experiencing, support one another, and make suggestions for workplace adaptations during this pandemic.

There has been a substantial decline in in-person care in inpatient and outpatient settings during the ongoing COVID-19 pandemic. Avoidance of needed in-person care may contribute to an avoidable decline in patient health and an increase in mortality. While several systems and behavioral theories have been put forward to explain the decline, there is a lack of studies informed by patients' own experiences. The current study applied a socio-ecological model encompassing patient, environmental, and institutional-related variables to examine patient-reported factors associated with avoidance of in-person care. Between October and December 2020, a total of 3840 persons responded to a nationwide online questionnaire that was administered using ResearchMatch and Facebook. Self-reported avoidance of in-person care among those who needed it was the main outcome. Multivariable logistic regression analysis was used to identify factors associated with avoidance of needed care. Out of a total of 3372 respondents who reported that they needed in-person care during the early phase of the pandemic, 257 (7.6%) avoided it. Patient-related variables associated with avoiding needed care included younger age (odds ratio (OR), 1.46, 95% CI 1.11 to 1.94, p<0.01; <45 y/o vs 45+), inability to afford care (OR = 1.65, 95% CI 1.17 to 2.34, p<0.01), and greater COVID-related stress (OR = 1.36, CI 1.01 to 1.83, p<0.05). More frequent discussions about COVID with family and friends was the only significant environment-related avoidance of care variable (OR = 1.39, 95% CI 1.01-1.91, p < .05). Institution-related care avoidance variables included a negative patient healthcare experience rating (OR 1.83, 95% CI 1.38 to 2.42, p<0.001), poor awareness of the institution's safety protocol (OR = 1.79, 95% CI 1.28 to 2.51, p<0.01), and low ratings of the institution's effectiveness in communicating their safety protocol (OR = 3.45, 95% CI 1.94 to 6.12, p<0.001). The final model predicted 11.9% of the variance in care avoidance. These results suggest that care avoidance of in-person care during the initial phase of the pandemic was influenced by a patient's demographics as well as environmental and healthcare institutional factors. Patients' previous experiences and their awareness of healthcare systems' safety protocols are important factors in care avoidance.

Substantial numbers of individuals who contract COVID-19 experience long-lasting cognitive symptoms such as brain fog. Yet research to date has not compared these patients with healthy controls with a history of laboratory-confirmed COVID-19 infection, making it difficult to understand why certain COVID patients develop post-COVID cognitive symptoms while others do not. The objective of this pilot study was to compare two groups of laboratory-confirmed post-COVID patients, with and without cognitive symptoms, on measures of cognitive and psychological functioning, self-reported perceptions of functional status and quality of life, and biomarkers of stress, inflammation, and neuroplasticity. Using a case-control design, 17 participants were recruited from a healthcare system in western Michigan, USA in 2022–2024. All participants were aged 25–65 and had a positive polymerase chain reaction (PCR) test confirming previous COVID-19 infection. Ten participants reported cognitive symptoms (long COVID group) while seven were fully recovered with no residual symptoms (controls). All participants underwent an interview on their self-rated health and quality of life, a battery of neurocognitive tests, and blood draw for biomarker analysis. No group differences were detected for neuropsychological test measures except for letter fluency where the long COVID group scored significantly lower (p < .05). The long COVID group had significantly lower ratings than controls on quality of life, physical health, emotional functioning, and psychological well-being. Serum levels of nerve growth factor (NGF), a biomarker of brain plasticity, were significantly lower in the long COVID group, which was significantly more likely than controls to have serum levels of inflammatory marker (interleukin (IL)-10) values greater than or equal to the median (p = 0.015). Biomarker analyses suggest possible prolonged inflammatory processes in long COVID patients compared to fully recovered patients. Results of decreased neuroplastic functioning give credence to patients’ reports of post-COVID changes in brain function.

Physician stress is associated with near misses and adverse medical events. However, little is known about physiological mechanisms linking stress to such events. We explored the utility of machine learning to determine whether the catabolic stress hormone cortisol and the anabolic, anti-stress hormone dehydroepiandrosterone sulfate (DHEA-S), as well as the cortisol to DHEA-S ratio relate to near misses in emergency medicine residents during active duty in a trauma 1 emergency department. Compared to statistical models better suited for inference, machine learning models allow for prediction in situations that have not yet occurred, and thus better suited for clinical applications. This exploratory study used multiple machine learning models to determine possible relationships between biomarkers and near misses. Of the various models tested, support vector machine with radial bias function kernels and support vector machine with linear kernels performed the best, with training accuracies of 85% and 79% respectively. When evaluated on a test dataset, both models had prediction accuracies of around 80%. The pre-shift cortisol to DHEA-S ratio was shown to be the most important predictor in interpretable models tested. Results suggest that interventions that help emergency room physicians relax before they begin their shift could reduce risk of errors and improve patient and physician outcomes. This pilot demonstrates promising results regarding using machine learning to better understand the stress biology of near misses. Future studies should use larger groups and relate these variables to information in electronic medical records, such as objective and patient-reported quality measures.

Objective Healthcare is battling a conflict between the Quadruple Aims—reducing costs; improving population health, patient experience, and team well-being—and productivity. This quasi-experimental pilot study tested a 2 week intervention aimed to address the Quadruple Aims while improving productivity. Participants were 25 employees and their patients in a primary care clinic. One provider and their team implemented an efficiency-focused intervention that modified work roles and processes focused on utilizing all team members’ skills as allowable by applicable licensure restrictions. The five remaining providers and their teams comprised the reference group, who continued patient care as usual. Study outcomes were measured via provider/staff and patient surveys and administrative data. Results In total, 46 team surveys and 156 patient surveys were collected. Clinic output data were retrieved for 467 visits. Compared to the reference team, the intervention team performed better in all Quadruple Aims and productivity measures. The intervention group offered 48% more patient slots than the average reference team. These preliminary results support the feasibility of introducing substantial process changes that show promising improvement in both the Quadruple Aims and productivity. A larger-scale study over a longer time period is needed to confirm findings and examine feasibility and cost-effectiveness.

Artificial and virtual technologies in healthcare have advanced rapidly, and healthcare systems have been adapting care accordingly. An intriguing new development is the virtual physician, which can diagnose and treat patients independently. This qualitative study of advanced degree students aimed to assess their perceptions of using a virtual primary care physician as a patient. Four focus groups were held: first year medical students, fourth year medical students, first year engineering/data science graduate students, and fourth year engineering/data science graduate students. The focus groups were audiotaped, transcribed verbatim, and content analyses of the transcripts was performed using a data-driven inductive approach. Themes identified concerned advantages, disadvantages, and the future of virtual primary care physicians. Within those main categories, 13 themes emerged and 31 sub-themes. While participants appreciated that a virtual primary care physician would be convenient, efficient, and cost-effective, they also expressed concern about data privacy and the potential for misdiagnosis. To garner trust from its potential users, future virtual primary physicians should be programmed with a sufficient amount of trustworthy data and have a high level of transparency and accountability for patients.

Background The federal government offers Earned Income Tax Credit (EITC) to working low and middle-income families. Lack of knowledge and distrust in government results in a large proportion of qualified families not claiming EITC. This is especially true for minority groups, including immigrants. The study objectives were: (1) to examine whether a community derived EITC outreach campaign targeting EITC eligible residents of Arab-American descent in Southeast Detroit, Michigan, U.S.A., resulted in increased knowledge of EITC; (2) to study the prospective relationship between EITC knowledge and financial hardship; and (3) to study the relationship between risks (financial hardship) and protective (exercise) factors and self-rated health. Methods In 2021, a total of 215 women attending Women, Infants, and Children (WIC) centers in Southeast Detroit, Michigan, were recruited. Participants filled out a survey at baseline, and after 6 and 12 months, respectively. The survey contained questions on sociodemographics, financial stressors, exercise, health, and knowledge of EITC. The 1-year retention rate was 48% ( n  = 104). Results At baseline, knowledge about EITC was low (mean 1.1 [SE 0.3] on a 0–10 visual analogue scale) but increased significantly during the first six months (2.9 [0.3]; p  < .01). Knowledge of EITC was not related to financial hardship ratings. Approximately 38% of respondents worried about not having sufficient funds to pay for rent/mortgage at baseline, and 28% worried about not being able to buy nutritious meals for their families. Worry about paying for meals at the 6-month study mid-point was significantly related to self-rated health at 12 months ( p  = .013). Self-rated health at 12 months was significantly lower (-0.74; 95% confidence interval − 1.40, − 0.16) among those worrying about paying for meals. The model explained 5.6% (r 2  = 0.056) of the variance in self-rated health at 12-months. Conclusions The study shows that knowledge about EITC is limited among qualified Arab-American households. A community engaged EITC outreach campaign increased knowledge substantially. Financial strain is related to worsening self-rated health. EITC is an underused bipartisan, pro-employment supported federal program to address near-poverty and poverty among underserved families. Future studies should determine whether EITC outreach campaigns increase the actual uptake of EITC, and whether increased uptake results in improved health.

Psychological war trauma among displaced refugees is an established risk factor for mental health disorders, especially post-traumatic stress disorder (PTSD). Persons with trauma-induced disorders have heightened neuroplastic restructuring of limbic brain circuits (e.g., amygdala and hippocampus), which are critical factors in the pathophysiology of PTSD. Civilians in war are exposed to both psychological trauma and environmental hazards, such as metals. Little is known about the possible mental health impact from such environmental exposures, alone or in combination with trauma. It is of special interest to determine whether war exposures contribute to dysfunctional neuroplasticity; that is, an adverse outcome from sustained stress contributing to mental health disorders. The current study examined Middle Eastern refugees in the United States to determine the relationships among pre-displacement trauma and environmental exposures, brain derived neurotrophic growth factor (BDNF) and nerve growth factor (NGF)-two neurotrophins reported to mediate neuroplasticity responses to stress-related exposures-and mental health. Middle Eastern refugees (n = 64; 33 men, 31 women) from Syria (n = 40) or Iraq (n = 24) were assessed 1 month after arrival to Michigan, US. Participants were interviewed in Arabic using a semi-structured survey to assess pre-displacement trauma and environmental exposure, PTSD, depression, anxiety, and self-rated mental health. Whole blood was collected, and concentrations of six heavy metals as well as BDNF and NGF levels were determined. Because these two neurotrophins have similar functions in neuroplasticity, we combined them to create a neuroplasticity index. Linear regression tested whether psychosocial trauma, environmental exposures and biomarkers were associated with mental health symptoms. The neuroplasticity index was associated with PTSD (standardized beta, β = 0.25, p < 0.05), depression (0.26, < 0.05) and anxiety (0.32, < 0.01) after controlling for pre-displacement trauma exposures. In addition, pre-displacement environmental exposure was associated with PTSD (0.28, < 0.05) and anxiety (0.32, < 0.05). Syrian refugees and female gender were associated with higher scores on depression (0.25, < 0.05; 0.30, < 0.05) and anxiety scales (0.35, < 0.01; 0.27, < 0.05), and worse on self-rated mental health (0.32, < 0.05; 0.34, < 0.05). In bivariate analysis, the neuroplasticity index was related to blood lead levels (r = 0.40; p < 0.01). The current study confirms the adverse effects of war trauma on mental health. Higher levels of biomarkers of neuroplasticity correlated with worse mental health and higher blood lead levels. Higher neurotrophin levels in refugees might indicate dysfunctional neuroplasticity with increased consolidation of adverse war memories in the limbic system. Such a process may contribute to psychiatric symptoms. Further research is needed to clarify the pathobiological mechanisms linking war trauma and environmental exposures to adverse mental health.

Screening for mental health problems has been shown to be effective to detect depression and initiate treatment in primary care. Current guidelines recommend periodic screening for depression and anxiety. This study examines the association of patient sociodemographic factors and clinic characteristics on mental health screening in primary care. In this retrospective cohort study, electronic medical record (EMR) data from a 14-month period from 10/15/2021 to 12/14/2022 were analyzed. Data were retrieved from 18 primary care clinics from the Corewell Health healthcare system in West Michigan. The main outcome was documentation of any Patient Health Questionnaire (PHQ-4/PHQ-9/GAD-7) screening in the EMR within the 14-month period at patient level. General linear regression models with logit link function were used to assess adjusted odds ratio (aOR) of having a documented screening. In total, 126,306 unique patients aged 16 years or older with a total of 291,789 encounters were included. The prevalence of 14-month screening was 79.8% (95% CI, 79.6-80.0). Regression analyses revealed higher screening odds for patients of smaller clinics (<5,000 patients, aOR 1.88; 95% CI 1.80-1.98 vs. clinics >10.000 patients), clinics in areas with mental health provider shortages (aOR 1.69; 95% CI 1.62-1.77), frequent visits (aOR 1.80; 95% CI, 1.78-1.83), and having an annual physical / well child visit encounter (aOR 1.52; 95% CI, 1.47-1.57). Smaller positive effect sizes were also found for male sex, Black or African American race, Asian race, Latinx ethnicity (ref. White/Caucasians), and having insurance through Medicaid (ref. other private insurance). The 14-month mental health screening rates have been shown to be significantly lower among patients with infrequent visits seeking care in larger clinics and available mental health resources in the community. Introducing and incentivizing mandatory mental health screening protocols in annual well visits, are viable options to increase screening rates.

Objective With the growing immigrant communities in the western world, there is an urgent need to address language barriers to care, and health disparities as a whole. Studies on limited English proficiency patients (LEP) have focused on patient perspectives of office visits, however little is known about health care provider perspectives of medical visits using interpretive services. We aimed to develop a pragmatic brief questionnaire for assessing providers’ views of the quality of communication in outpatient visits with patients with LEP. The questionnaire was validated in a cross-sectional study (n = 99) using principal component analyses (PCA) with oblimin rotation. Internal consistency was analyzed using Cronbach’s alpha. Results Based on theory and literature, a seven-item scale was developed that captures two relevant concepts: (1) Provider - patient interaction during the consultation and (2) perceived quality of translation. The questionnaire was used to assess 99 LEP consultations and demonstrated good feasibility in a clinical setting. PCA revealed the two theory-based components with good factor loadings and internal consistency of α = 0.77. These preliminary results indicate that the questionnaire provides medical professionals with a validated tool to evaluate LEP patient encounters. Further confirmatory validation of the Provider-assessed Quality of Consultations with Language Interpretation (PQC-LI) in larger samples is warranted.