The impact of tutoring on nursing students' clinical judgment: A quasi-experimental study.

BACKGROUND: Nurses' lack of clinical judgment often leads to adverse patient outcomes due to failure to recognize clinical deterioration, intervene, and manage complications. Teaching clinical judgment through a nursing process can help nursing students provide safe and competent patient care with improved health outcomes and to pass the National Council Licensure Examination for Registered Nurses (NCLEX-RN). AIMS: The aim of this study was to examine the effect of tutoring on clinical judgment of undergraduate nursing students utilizing Lasater's Clinical Judgment Rubric (LCJR). This study also compared the clinical judgment of male and female nursing students and students from different semester levels. METHODS: This quasi-experimental study utilized a single group pretest, posttest design. A convenience sample of n = 40 undergraduate nursing students from the Los Angeles County College of Nursing and Allied Health participated in the study. The participants underwent a pretest simulation, four sessions of the Clinical Judgment Model (CJM)-based tutoring, and a posttest simulation. RESULTS: The posttest clinical judgment scores (35.70 ± 3.6) were significantly different from the pretest scores (25.78 ± 5.20). The tutoring had a significant effect on the clinical judgment of nursing students t(39) = -11.64, n = 40, p < .001, at 95% CI of the mean difference. LINKING EVIDENCE TO ACTION: Enhancing nursing students' clinical judgment is crucial to provide high-quality, safe patient care with improved health outcomes. The CJM-based tutoring is an effective strategy for developing clinical judgment in nursing students. This new teaching approach can train students to critically think, develop clinical judgment, and prepare for the complex healthcare environment. Therefore, nurse educators should focus on integrating clinical judgment into the prelicensure nursing program curriculum as a priority.

Characterization of COVID-19 Vaccine Hesitancy Among Essential Workforce Members of a Large Safety Net Urban Medical Center.

OBJECTIVES: Vaccine hesitancy among essential workers remains a significant public health challenge. We examined psychological constructs of perceived susceptibility, threat, and self-efficacy and their associations with COVID-19 vaccine hesitancy among a racially and ethnically diverse essential workforce population. METHODS: We performed a cross-sectional survey of essential workers from September-December 2020 at a large Los Angeles safety-net medical center as part of a program offering free COVID-19 serology testing. Program participants completed a standardized survey at the time of phlebotomy. Hierarchical logistic regression was utilized to determine factors independently associated with vaccine hesitancy. RESULTS: Among 1327 persons who had serology testing, 1235 (93%) completed the survey. Of these, 958 (78%) were healthcare workers. Based on expressed intent, 22% were vaccine-hesitant 78% were vaccine acceptors. In our multivariate model, vaccine hesitancy was associated with female gender [aOR = 2.09; 95% CI (1.44-3.05)], African American race [aOR = 4.32; (2.16-8.62)], LatinX ethnicity [aOR = 2.47; 95% CI (1.51-4.05)] and history of not/sometimes receiving influenza vaccination [aOR = 4.39; 95% CI (2.98-6.48)]. Compared to nurses, vaccine hesitancy was lower among physicians [aOR = 0.09; 95% CI (0.04-0.23)], non-nursing/non-physician healthcare workers [aOR = 0.55; 95% CI (0.33-0.92)], and non-healthcare care workers [aOR = 0.53; 95% CI (0.36-0.78)]. CONCLUSIONS: Among a racially/ethnically diverse group of safety net medical center essential workers, COVID-19 vaccine hesitancy was associated with racial/ethnic minority groups, employment type, and prior influenza vaccination hesitancy. Interestingly, we found no association with the Health Belief Model construct measures of perceived susceptibility, threat, and self-efficacy. Psychological constructs not assessed may be drivers of vaccine hesitancy in our population.

Gene-environment interactions and predictors of breast cancer in family-based multi-ethnic groups.

Breast cancer (BC) is the most common cancer in women worldwide and second leading cause of cancer-related death. Understanding gene-environment interactions could play a critical role for next stage of BC prevention efforts. Hence, the purpose of this study was to examine the key gene-environmental factors affecting the risks of BC in a diverse sample. Five genes in one-carbon metabolism pathway including MTHFR 677, MTHFR 1298, MTR 2756, MTRR 66, and DHFR 19bp together with demographics, lifestyle, and dietary intake factors were examined in association with BC risks. A total of 80 participants (40 BC cases and 40 family/friend controls) in southern California were interviewed and provided salivary samples for genotyping. We presented the first study utilizing both conventional and new analytics including ensemble method and predictive modeling based on smallest errors to predict BC risks. Predictive modeling of Generalized Regression Elastic Net Leave-One-Out demonstrated alcohol use (p = 0.0126) and age (p < 0.0001) as significant predictors; and significant interactions were noted between body mass index (BMI) and alcohol use (p = 0.0027), and between BMI and MTR 2756 polymorphisms (p = 0.0090). Our findings identified the modifiable lifestyle factors in gene-environment interactions that are valuable for BC prevention.

MTHFR Gene Polymorphism-Mutations and Air Pollution as Risk Factors for Breast Cancer: A Metaprediction Study.

BACKGROUND: The methylenetetrahydrofolate reductase gene (MTHFR) is one of the most investigated genes associated with breast cancer for its role in epigenetic pathways. OBJECTIVES: The objectives of this metaprediction study were to examine the polymorphism-mutation risk subtypes of MTHFR and air pollution as contributing factors for breast cancer. METHODS: For triangulation purposes in metapredictive analyses, we used a recursive partition tree, nonlinear association curve fit, and heat maps for data visualization, in addition to the conventional comparison procedure and pooled analyses. RESULTS: We included 36,683 breast cancer cases and 40,689 controls across 82 studies for MTHFR 677 and 23,252 cases and 27,094 controls across 50 studies for MTHFR 1298. MTHFR 677 TT was a risk genotype for breast cancer (p = .0004) and in the East Asian subgroup (p = .005). On global maps, the most polymorphism-mutations on MTHFR 677 TT were found in the Middle East, Europe, Asia, and the Americas, whereas the most mutations on MTHFR 1298 CC were located in Europe and the Middle East for the control group. The geographic information system maps further revealed that MTHFR 677 TT mutations yielded a higher risk of breast cancer for Australia, East Asia, the Middle East, South Europe, Morocco, and the Americas and that MTHFR 1298 CC mutations yielded a higher risk in Asia, the Middle East, South Europe, and South America. Metapredictive analysis revealed that air pollution level was significantly associated with MTHFR 677 TT polymorphism-mutation genotype. DISCUSSION: We present the most comprehensive analyses to date of MTHFR polymorphism-mutations and breast cancer risk. Future nursing studies are needed to investigate the health impact on breast cancer of epigenetics and air pollution across populations.