Methods: A cross-sectional study was conducted with 500 nurses, selected through multistage cluster sampling, from the hospitals in Shiraz in 2017. The data collection tools were the Siberia Schering's Emotional Intelligence Standard Questionnaire and the Hospital Job Stress Standard Questionnaire, completed through the self-report method. The data were analysed using SPSS 22 software.
Results: The mean scores of emotional intelligence and job stress were 113.59 ± 14.70 (total score = 165) and 97.10 ± 14.27 (total score = 175), respectively. The correlation test showed that there was an inverse relationship between emotional intelligence and job stress (r = -0.474, P < 0.001). Also, the multiple linear regression analysis showed that self-awareness, social consciousness, and income predicted 25% of the job stress in the subjects under study (r2 = 0.25).
Conclusion: Regarding the relatively strong and inverse relationship between the nurses' emotional intelligence and job stress, it is suggested that emotional intelligence workshops be included in the in-service training programs of the nurses.
METHODS: 160 eyes of 160 healthy children (74 boys, 86 girls) aged 6-18 years (mean: 11.60 ± 3.28 years) were evaluated in this cross-sectional study. The peripapillary retinal nerve fibre layer (pRNFL) and macular thickness were determined for the 1st, 5th, 95th, and 99th percentile points. Cohen's κ value and specific agreement between pediatric data and adult reference database were estimated. The correlation between retinal thickness with age and SE was also determined.
RESULTS: The mean thickness for the total RNFL, average macular, and central macula were 112.05±8.65 μm, 280.24±12.46 μm, and 220.55±17.53 μm, respectively. The overall agreement between the classification of the adult database and pediatric data for pRNFL was ≥90%, with discrepancies in 46 out of 150 eyes (30.67%); for macula, it was above 72%, with discrepancies in 93 out of 153 eyes (60.78%); and for ganglion cell complex and ganglion cell + inner plexiform layer (GCIPL) the agreement was above 84% and 85%, respectively. A significant level of agreement between pediatric data and adult reference data was achieved for temporal RNFL (κ = 0.65), macular perifoveal superior (κ = 0.67), and inferior (κ = 0.63) and inferior GCIPL (κ = 0.67). The correlations between age and retinal thickness were not significant (all p>0.05). Most retinal thickness parameters were positively associated with SE (Pearson's coefficient, r = 0.26 to 0.49, all p<0.05).
CONCLUSIONS: The overall agreement for pRNFL and macular thickness measurements in children with the adult reference database was between 72% and 90%. Children's retinal thickness was not significantly correlated with age but was positively associated with spherical equivalent.
MATERIALS AND METHODS: This was a single-centre cross-sectional study of 115 women with American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BIRADS) breast density C and D on DBT with breast lesions who underwent AB-MR from June 2018 to December 2021. AB-MR was performed on a 3 T MRI system with an imaging protocol consisting of three sequences: axial T1 fat-saturated unenhanced; axial first contrast-enhanced; and subtracted first contrast-enhanced with maximum intensity projection (MIP). DBT and AB-MR images were evaluated by two radiologists blinded to the histopathology and patient outcomes. Diagnostic accuracy (sensitivity, specificity, positive predictive value [PPV] and negative predictive value [NPV]) was assessed.
RESULT: Of the 115 women, the mean age was 50.6 years. There were 48 (41.7%) Malay, 54 (47%) Chinese, and 12 (10.4%) Indian women. The majority (n=87, 75.7%) were from the diagnostic population. Sixty-one (53.1%) were premenopausal and 54 (46.9%) postmenopausal. Seventy-eight (72.4%) had an increased risk of developing breast cancer. Ninety-one (79.1%) women had density C and 24 (20.9%) had density D. There were 164 histopathology-proven lesions; 69 (42.1%) were malignant and 95 (57.9%) were benign. There were 62.8% (n=103/164) lesions detected at DBT. All the malignant lesions 100% (n=69) and 35.7% (n=34) of benign lesions were detected. Of the 61 lesions that were not detected, 46 (75.4%) were in density C, and 15 (24.6%) were in density D. The sensitivity, specificity, PPV, and NPV for DBT were 98.5%, 34.6%, 66.3%, and 94.7%, respectively. There were 65.2% (n=107/164) lesions detected on AB-MR, with 98.6% (n=68) malignant and 41.1% (39) benign lesions detected. The sensitivity, specificity, PPV, and NPV for AB-MR were 98.5%, 43.9%, 67.2%, and 96.2%, respectively. One malignant lesion (0.6%), which was a low-grade ductal carcinoma in-situ (DCIS), was missed on AB-MR.
CONCLUSION: The present findings suggest that both DBT and AB-MR have comparable effectiveness as an imaging method for detecting breast cancer and have high NPV for low-risk lesions in women with dense breasts.
METHODS: Between December 2020 to February 2023, parents of ARM and HD patients with and without DS aged 3-17 years who had undergone surgery > 12 months prior at four tertiary referral centers were recruited. We used the Pediatric Quality of Life Inventory™ (PedsQL™) Generic Core Scales, General Well-Being (GWB) Scale and Family Impact (FI) Module questionnaires, and the Rintala bowel function score (BFS).
RESULTS: There were 101 ARM, 9 (8.9%) of whom had DS; and 87 HD, of whom 6 (6.9%) had DS. Parent-reported Core scores in ARM and HD with DS were comparable to those without DS. However, ARM and HD with DS had worse scores in the FI Module and bowel function than those without DS.
CONCLUSION: Although parent-reported QOL in ARM and HD with DS is similar to those without DS, family impact and BFS are worse. Our findings are limited by small sample size in proportion of DS patients.
METHODOLOGY: This was a cross-sectional study on 258 patients with T2DM duration of at least 10 years. Transient elastography (FibroScan®) was performed on all subjects. Advanced liver fibrosis was diagnosed based on LSM results. The FIB-4 index formula was used.
RESULTS: The prevalence of advanced liver fibrosis was 22.1%. Associated factors were body mass index (BMI), alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT), triglyceride (TG) and high-density lipoprotein (HDL) cholesterol. Independent factors were BMI and GGT (p=0.003 and p<0.001). FIB-4 index has 30.0% sensitivity, 85.0% specificity, 38.7% positive predictive value, and 79.4% negative predictive value in detecting advanced liver fibrosis by LSM criteria.
CONCLUSION: Our study confirmed the high prevalence of advanced liver fibrosis among patients with long-standing T2DM. This study suggests the benefit of advanced liver fibrosis screening in patients with a minimum of 10 years of T2DM, especially those with high BMI and GGT.
MATERIALS AND METHODS: All the cross-sectional studies were retrieved from the PubMed databases, the Web of Science ISI, Scopus, and the Cochrane Library. Papers published in English between 2 November 2019 and 23 May 2023 were subjected to further assessment based on their title, abstract, and main text, with a view to ensuring their relevance to the present study.
RESULTS: Following an exhaustive investigation, 59 studies were selected for screening in this systematic review. The most frequently employed method of data collection was the online survey. The study sample comprised 59.12% women and 40.88% men, with ages ranging from 16 to 78 years. The proportion of individuals accepting the vaccine ranged from 13% to 96%, while the proportion of those exhibiting hesitancy ranged from 0% to 57.5%. The primary reasons for accepting the COIVD-19 vaccine were a heightened perception of risk associated with the virus and a general trust in the healthcare system. The most frequently cited reasons for vaccine hesitancy in the context of the ongoing pandemic include concerns about the potential dangers of the vaccines, the rapid pace of their development, the possibility of adverse effects (such as infertility or death), and the assumption that they have been designed to inject microchips.
DISCUSSION: A variety of socio-demographic factors are implicated in determining the rate of vaccine acceptance. A number of socio-demographic factors have been identified as influencing vaccine acceptance. These include high income, male gender, older age, marriage, the presence of older children who have been vaccinated and do not have chronic diseases, high education, and health insurance coverage.
CONCLUSION: Eliminating vaccine hesitancy or increasing vaccine acceptance is a crucial factor that should be addressed through various means and in collaboration with regulatory and healthcare organizations.