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The updated AORN “Guideline for transmission‐based precautions” provides perioperative nurses with evidence‐based guidance on preparing for emerging and persistent infectious threats and outlines strategies to reduce the risk of transmission in the surgical setting. This article provides an overview of the guideline and discusses recommendations for personal protective equipment; implementing standard, contact, droplet, and airborne precautions; infective airborne particle risk assessment; transporting patients with confirmed or suspected infectious disease; and preparing for emerging infectious diseases. A scenario illustrates the application of these practices during the transport of a patient on airborne precautions. Perioperative nurses should review the guideline in its entirety and apply the recommendations to support infection prevention; protect patients and personnel; and ensure safe, evidence‐based care across all surgical settings.

The updated AORN “Guideline for transmission‐based precautions” provides perioperative nurses with evidence‐based guidance on preparing for emerging and persistent infectious threats and outlines strategies to reduce the risk of transmission in the surgical setting. This article provides an overview of the guideline and discusses recommendations for personal protective equipment; implementing standard, contact, droplet, and airborne precautions; infective airborne particle risk assessment; transporting patients with confirmed or suspected infectious disease; and preparing for emerging infectious diseases. A scenario illustrates the application of these practices during the transport of a patient on airborne precautions. Perioperative nurses should review the guideline in its entirety and apply the recommendations to support infection prevention; protect patients and personnel; and ensure safe, evidence‐based care across all surgical settings.

Among school districts in the greater Boston area, the lifting of masking requirements was associated with an additional 44.9 Covid-19 cases per 1000 students and staff during the 15 weeks after a statewide masking policy was rescinded.

Investigations about the interrelationships of nurses' safety climate, quality of care, and standard precautions (SP) adherence and compliance remain particularly scarce in the literature. Thus, we tested a model of the associations between nurses' safety climate, quality of care, and the factors influencing adherence and compliance with SPs utilizing the structural equation modeling (SEM) approach. Cross-sectional design complying with STROBE guidelines. Using convenience sampling, nurses (n = 730) from the Philippines were recruited. Data were collected between April and September 2022 using four validated self-report measures. Spearman Rho, mediation and path analyses, and SEM were employed for data analysis. Acceptable model fit indices were shown by the emerging model. The safety climate is positively associated with quality of care and factors influencing adherence to and compliance with SPs. Quality of care directly affected factors influencing adherence to SPs. The factors influencing adherence to SPs directly affected SP compliance. Quality of care mediated between safety climate and the factors influencing adherence to SPs. Factors influencing adherence to SPs mediated between safety climate, quality of care, and SP compliance. The study's variables are not distinct but overlapping nursing concepts that must be examined collectively. Nurse administrators can utilize the emerging model to formulate strategies and regulations for evaluating and enhancing nurses' safety climate, quality of care, and SP adherence and compliance. Our findings may impact policymaking, organizational, and individual levels to improve nurses' clinical practice. This study had no patient contribution or public funding.

Data collection using Internet-based samples has become increasingly popular in many social science disciplines, including advertising. This research examines whether one popular Internet data source, Amazon's Mechanical Turk (MTurk), is an appropriate substitute for other popular samples utilized in advertising research. Specifically, a five-sample between-subjects experiment was conducted to help researchers who utilize MTurk in advertising experiments understand the strengths and weaknesses of MTurk relative to student samples and professional panels. In comparisons across five samples, results show that the MTurk data outperformed panel data procured from two separate professional marketing research companies across various measures of data quality. The MTurk data were also compared to two different student samples, and results show the data were at least comparable in quality. While researchers may consider MTurk samples as a viable alternative to student samples when testing theory-driven outcomes, precautions should be taken to ensure the quality of data regardless of the source. Best practices for ensuring data quality are offered for advertising researchers who utilize MTurk for data collection.

Researchers focusing on how artificial intelligence (AI) methods explain their decisions often discuss controversies and limitations. Some even assert that most publications offer little to no valuable contributions. In this article, we substantiate the claim that explainable AI (XAI) is in trouble by describing and illustrating four problems: the disagreements on the scope of XAI, the lack of definitional cohesion, precision, and adoption, the issues with motivations for XAI research, and limited and inconsistent evaluations. As we delve into their potential underlying sources, our analysis finds these problems seem to originate from AI researchers succumbing to the pitfalls of interdisciplinarity or from insufficient scientific rigor. Analyzing these potential factors, we discuss the literature at times coming across unexplored research questions. Hoping to alleviate existing problems, we make recommendations on precautions against the challenges of interdisciplinarity and propose directions in support of scientific rigor.

Emphasize robustness, monitoring, and flexibility A great deal of research to inform environmental conservation and management takes a predict-and-prescribe strategy in which improving forecasts about future states of ecosystems is the primary goal. But sufficiently thorough understanding of ecosystems needed to reduce deep uncertainties is probably not achievable, seriously limiting the potential effectiveness of the predict-and-prescribe approach. Instead, research should integrate more closely with policy development to identify the range of alternative plausible futures and develop strategies that are robust across these scenarios and responsive to unpredictable ecosystem dynamics.

Effective management of the global pandemic caused by Severe Acute Respiratory Syndrome Coronavirus 2 (also known as COVID-19), resulted in the implementation of severe restrictions in movement and enforcement of social distancing measures. This study aimed to understand and characterize the psychosocial effects of the COVID-19 pandemic in the general population and to identify risks and protective factors that predict changes in mental health status. In addition, the study investigated compliance with precautionary measures (PM) to halt the spread of the virus. The online anonymous survey collected information on sociodemographic data, compliance with PM, quality of life (QOL), and mental health via the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9). A total of 1642 adult participants (71.6% women, 28.4% men) completed the survey in the European island country, Cyprus. A large percentage (48%) reported significant financial concerns and 66.7% significant changes in their QOL. About 41% reported symptoms associated with mild anxiety; 23.1% reported moderate-severe anxiety symptoms. Concerning depression, 48% reported mild and 9.2% moderate-severe depression symptoms. Women, younger age (18–29), student status, unemployment status, prior psychiatric history, and those reporting greater negative impact on their QOL, were at higher risk for increased anxiety and depression symptoms (p < 0.05). The youngest age group and males also reported lower levels of compliance with PM. Higher compliance with PM predicted lower depression scores (p < 0.001) but higher anxiety for measures related to personal hygiene. The results of this study provide important data on the effects of the COVID-19 outbreak on mental health and QOL and identify a variety of personal and social determinants that serve as risks and protective factors. Furthermore, it has implications for policy makers demonstrating the need for effective mental health programs and guidance for the implementation of PM as a public health strategy.

Unrecognized transmission of pathogens in healthcare settings can lead to colonization and infection of both patients and healthcare personnel. The use of personal protective equipment (PPE) is an important strategy to protect healthcare personnel from contamination and to prevent the spread of pathogens to subsequent patients. However, optimal PPE use is difficult, and healthcare personnel may alter delivery of care because of the PPE. Here, we summarize recent research from the Prevention Epicenters Program on healthcare personnel contamination and improvement of the routine use of PPE as well as Ebola-specific PPE. Future efforts to optimize the use of PPE should include increasing adherence to protocols for PPE use, improving PPE design, and further research into the risks, benefits, and best practices of PPE use.

Switzerland began a national lockdown on March 16, 2020, in response to the rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We assessed the prevalence of SARS-CoV-2 infection among patients admitted to 4 hospitals in the canton of Zurich, Switzerland, in April 2020. These 4 acute care hospitals screened 2,807 patients, including 2,278 (81.2%) who did not have symptoms of coronavirus disease (COVID-19). Overall, 529 (18.8%) persons had >1 symptom of COVID-19, of whom 60 (11.3%) tested positive for SARS-CoV-2. Eight asymptomatic persons (0.4%) also tested positive for SARS-CoV-2. Our findings indicate that screening on the basis of COVID-19 symptoms, regardless of clinical suspicion, can identify most SARS-CoV-2-positive persons in a low-prevalence setting.