METHODS: University students from Jiangsu Province participated in this study. Participants completed self-report surveys assessing emotion regulation strategies. It was conducted from May 2022 to July 2022. The study employed confirmatory factor analysis (CFA) to assess the two-factor model of ERQ-8 and measurement invariance across male and female samples.
RESULTS: The mean age of 1534 participants was 19.83 years (SD = 1.54), and the majority were female (70.4%). The initial ERQ-10 model with ten items demonstrated good fit for all indicators, CFI (Comparative Fit index) = 0.967, TLI (Tucker-Lewis Index) = 0.957, RMSEA (Root Mean Square Error of Approximation) = 0.043, SRMR (Standardised Root Mean Square Residual) = 0.029. However, to assess the fit of the previously proposed ERQ-8 model, two items (Q1 and Q3) were excluded. The fit of the ERQ-8 model was further improved (CFI = 0.989, TLI = 0.984, RMSEA = 0.029, SRMR = 0.021). All item loadings exceeded or were equal to 0.573. Internal consistency analysis based on the ERQ-8 model revealed Cronbach's alpha values of 0.840 for reappraisal and 0.745 for suppression, and corresponding composite reliability (CR) values of 0.846 and 0.747, respectively. Test-retest reliability, assessed using the intraclass correlation coefficient (ICC) (95% CI) within a one-week interval, ranged from 0.537 to 0.679. The correlation coefficient between the two factors was 0.084, significantly below 0.85, which suggested a low correlation between the two factors. The results of the invariance analysis across gender demonstrated that the values of ΔCFI and ΔTLI were both below 0.01. It was supported the gender invariance of the ERQ-8 among university students.
CONCLUSION: The eight-item ERQ demonstrated validity and reliability in evaluating emotion regulation strategies, and measurement invariance was observed across gender among university students. The ERQ-8 may prove to be a practical and cost-effective tool, particularly in time-constrained situations.
METHODS: We conducted a comprehensive literature review, searching databases such as PubMed, Embase, and Web of Science until June 2023. Our objective was to identify studies that compared the efficacy of 68Ga-PSMA-11 PET/CT and mpMRI in detecting primary prostate cancer. To determine heterogeneity, the I2 statistic was used. Meta-regression analysis and leave-one-out sensitivity analysis were conducted to identify potential sources of heterogeneity.
RESULTS: Initially, 1286 publications were found, but after careful evaluation, only 16 studies involving 1227 patients were analyzed thoroughly. The results showed that the 68Ga-PSMA-11 PET/CT method had a pooled sensitivity and specificity of 0.87 (95 % CI: 0.80-0.92) and 0.80 (95 % CI: 0.69-0.89), respectively, for diagnosing prostatic cancer. Similarly, the values for mpMRI were determined as 0.84 (95 % CI: 0.75-0.92) and 0.74 (95 % CI: 0.61-0.86), respectively. There were no significant differences in diagnostic effectiveness observed when comparing two primary prostate cancer methodologies (pooled sensitivity P = 0.62, pooled specificity P = 0.50). Despite this, the funnel plots showed symmetry and the Egger test results (P values > 0.05) suggested there was no publication bias.
CONCLUSIONS: After an extensive meta-analysis, it was found that both 68Ga-PSMA-11 PET/CT and mpMRI demonstrate similar diagnostic effectiveness in detecting primary prostate cancer. Future larger prospective studies are warranted to investigate this issue further.
METHODS: Urine samples were collected from pesticide applicators in Malaysia, Uganda, and the UK during mixing/application days (and also during non-application days in Uganda). Samples were collected pre- and post-activity on the same day and analysed for biomarkers of active ingredients (AIs), including synthetic pyrethroids (via the metabolite 3-phenoxybenzoic acid [3-PBA]) and glyphosate, as well as creatinine. We performed multilevel Tobit regression models for each study to assess the relationship between exposure modifying factors (e.g., mixing/application of AI, duration of activity, personal protective equipment [PPE]) and urinary biomarkers of exposure.
RESULTS: From the Malaysia, Uganda, and UK studies, 81, 84, and 106 study participants provided 162, 384 and 212 urine samples, respectively. Pyrethroid use on the sampling day was most common in Malaysia (n = 38; 47%), and glyphosate use was most prevalent in the UK (n = 93; 88%). Median pre- and post-activity 3-PBA concentrations were similar, with higher median concentrations post-compared to pre-activity for glyphosate samples in the UK (1.7 to 0.5 μg/L) and Uganda (7.6 to 0.8 μg/L) (glyphosate was not used in the Malaysia study). There was evidence from individual studies that higher urinary biomarker concentrations were associated with mixing/application of the AI on the day of urine sampling, longer duration of mixing/application, lower PPE protection, and less education/literacy, but no factor was consistently associated with exposure across biomarkers in the three studies.
CONCLUSIONS: Our results suggest a need for AI-specific interpretation of exposure modifying factors as the relevance of exposure routes, levels of detection, and farming systems/practices may be very context and AI-specific.
METHODS: A systematic search was carried out over the last 5 years from 2017 to 2022 on basis the following electronic databases: Science Direct, Scopus, Web of Science, Springer and PubMed. The keywords that used in the searching were: ultrasound, sonography, ultrasonography, plantar fasciitis, imaging of plantar fascia, physiotherapy of plantar fasciitis, interventional treatment of plantar fasciitis, randomized controlled trial of plantar fasciitis and interventional ultrasound. The review focused on the assessment of PF in patients with PFS underwent different interventions using B-mode, shear wave elastography (SWE) and color Doppler ultrasound.
RESULTS: During the search process, 1661 were recorded using the proper keywords from 2017 to 2022 in which 666 original articles were found after removing the review and duplicated articles. Of these, thirty articles met the inclusion criteria and included in this review. The articles have assessed the PF in patients with PFS under different conditions using different ultrasound modes. Twenty-six articles evaluated the effectiveness of different treatment on PF in patients with PFS using different ultrasound modes. In 8 of 26 articles, the ultrasound was used as both an assessment tool of PF and guide therapeutic technique in patients with PFS. In 18 articles, the ultrasound was used as only assessment tool to identify the PF thickness and its observation changes in patients with PFS. Four articles compared the PF thickness and its intrafascial changes between patients with PFS and healthy subjects.
CONCLUSION: The ultrasound can be a reliable tool in assessment the effect of different interventions on PF by evaluating its thickness, echogenicity and stiffness changes in patients with PFS. There were different methods and treatments were used among the studies.
METHODS: We conducted an international, retrospective cohort study using 2019 and 2020 data from 11 national clinical quality registries covering 15 countries. Non-COVID-19 admissions in 2020 were compared with all admissions in 2019, prepandemic. The primary outcome was intensive care unit (ICU) mortality. Secondary outcomes included in-hospital mortality and standardised mortality ratio (SMR). Analyses were stratified by the country income level(s) of each registry.
FINDINGS: Among 1 642 632 non-COVID-19 admissions, there was an increase in ICU mortality between 2019 (9.3%) and 2020 (10.4%), OR=1.15 (95% CI 1.14 to 1.17, p<0.001). Increased mortality was observed in middle-income countries (OR 1.25 95% CI 1.23 to 1.26), while mortality decreased in high-income countries (OR=0.96 95% CI 0.94 to 0.98). Hospital mortality and SMR trends for each registry were consistent with the observed ICU mortality findings. The burden of COVID-19 was highly variable, with COVID-19 ICU patient-days per bed ranging from 0.4 to 81.6 between registries. This alone did not explain the observed non-COVID-19 mortality changes.
INTERPRETATION: Increased ICU mortality occurred among non-COVID-19 patients during the pandemic, driven by increased mortality in middle-income countries, while mortality decreased in high-income countries. The causes for this inequity are likely multi-factorial, but healthcare spending, policy pandemic responses, and ICU strain may play significant roles.