Mental State of Central Sterile Supply Department Staff During COVID-19 Epidemic and CART Analysis

Chi Square ◽

Factors Affecting ◽

Abstract Background: During the COVID-19 epidemic, the central sterile supply department (CSSD) staff handled many devices, implements and non-disposable protective articles used by suspected or confirmed COVID-19 patients. As a result, the CSSD staff may have experienced psychological stress, however, the mental state of the CSSD staff during the COVID-19 epidemic has been rarely studied. We aim to investigate the mental state of the CSSD staff and relevant influencing factors experienced during the COVID-19 epidemic.Methods: The survey utilising a general information questionnaire, Chinese perceived stress scale (CPSS), self-rating anxiety scale (SAS), and Connor-Davidson resilience scale (CD-RISC) was conducted with 423 CSSD staff members from 35 hospitals in Sichuan Province, China. Data was analysed in SPSS24.0. Classification and regression tree (CART) was utilised to analyse variables and find variation between groups. A chi-square test was performed on enumeration data, and t-test and analysis of variance were performed on measurement data.Results: The CSSD staff’s SAS score was 37.39 ± 8.458, their CPSS score was 19.21 ± 7.265, and their CD-RISC score was 64.26 ± 15.129 (Tenacity factor score: 31.70 ± 8.066, Strength factor score: 21.60 ± 5.066, Optimism factor scores: 10.96 ± 3.189). The CPSS score was positively correlated with the SAS score (r = 0.66; P < 0.01), the CPSS score was negatively correlated with the CD-RISC score (r = -0.617, P < 0.01), and the SAS score was negatively correlated with the CD-RISC score (r = -0.477, P < 0.01). The job position, age, and political status of the CSSD staff were the main factors affecting their mental state; for example, the CPSS score and SAS score of the CSSD nurses were significantly different from those of the CSSD logistic staff (P < 0.01). Conclusion: During the epidemic, the CSSD staff’s psychological resilience was at a low level; the anxiety level of the CSSD nurses was higher than that of the CSSD logistic staff. Therefore, more attention should be given to the mental health of the CSSD staff, including taking protective measures regarding the risk factors to ensure they can maintain a healthy mental state.

Mental state of central sterile supply department staff during COVID-19 epidemic and CART analysis

BMC Health Services Research ◽

10.1186/s12913-020-05864-5 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Wei Pan ◽

Juan Hu ◽

Liangying Yi

Keyword(s):

Mental State ◽

Factor Score ◽

Measurement Data ◽

Regression Tree ◽

General Information ◽

Chi Square ◽

Factors Affecting ◽

Abstract Background During the COVID-19 epidemic, the central sterile supply department (CSSD) staff handled many devices, implements and non-disposable protective articles used by suspected or confirmed COVID-19 patients. As a result, the CSSD staff may have experienced psychological stress, however, the mental state of the CSSD staff during the COVID-19 epidemic has been rarely studied. We aim to investigate the mental state of the CSSD staff and relevant influencing factors experienced during the COVID-19 epidemic. Methods The survey utilising a general information questionnaire, Chinese perceived stress scale (CPSS), self-rating anxiety scale (SAS), and Connor-Davidson resilience scale (CD-RISC) was conducted with 423 CSSD staff members from 35 hospitals in Sichuan Province, China. Data was analysed in SPSS24.0. Classification and regression tree (CART) was utilised to analyse variables and find variation between groups. A chi-square test was performed on enumeration data, and t-test and analysis of variance were performed on measurement data. Results The CSSD staff’s SAS score was 37.39 ± 8.458, their CPSS score was 19.21 ± 7.265, and their CD-RISC score was 64.26 ± 15.129 (Tenacity factor score: 31.70 ± 8.066, Strength factor score: 21.60 ± 5.066, Optimism factor scores: 10.96 ± 3.189). The CPSS score was positively correlated with the SAS score (r = 0.66; P < 0.01), the CPSS score was negatively correlated with the CD-RISC score (r = − 0.617, P < 0.01), and the SAS score was negatively correlated with the CD-RISC score (r = − 0.477, P < 0.01). The job position, age, and political status of the CSSD staff were the main factors affecting their mental state; for example, the CPSS score and SAS score of the CSSD nurses were significantly different from those of the CSSD logistic staff (P < 0.01). Conclusion During the epidemic, the CSSD staff’s psychological resilience was at a low level; the anxiety level of the CSSD nurses was higher than that of the CSSD logistic staff. Therefore, more attention should be given to the mental health of the CSSD staff, including taking protective measures regarding the risk factors to ensure they can maintain a healthy mental state.

Mental State of Central Sterile Supply Department Staff During COVID-19 Epidemic and CART Analysis

10.21203/rs.3.rs-37452/v2 ◽

2020 ◽

Author(s):

Wei Pan ◽

Juan Hu ◽

Liangying Yi

Keyword(s):

Mental State ◽

Factor Score ◽

Measurement Data ◽

Regression Tree ◽

General Information ◽

Chi Square ◽

Factors Affecting ◽

Abstract Background: During the COVID-19 epidemic, the central sterile supply department (CSSD) staff handled many devices, implements and non-disposable protective articles used by suspected or confirmed COVID-19 patients. As a result, the CSSD staff may have experienced psychological stress, however, the mental state of the CSSD staff during the COVID-19 epidemic has been rarely studied. We aim to investigate the mental state of the CSSD staff and relevant influencing factors experienced during the COVID-19 epidemic.Methods: The survey utilising a general information questionnaire, Chinese perceived stress scale (CPSS), self-rating anxiety scale (SAS), and Connor-Davidson resilience scale (CD-RISC) was conducted with 423 CSSD staff members from 35 hospitals in Sichuan Province, China. Data was analysed in SPSS24.0. Classification and regression tree (CART) was utilised to analyse variables and find variation between groups. A chi-square test was performed on enumeration data, and t-test and analysis of variance were performed on measurement data.Results: The CSSD staff’s SAS score was 37.39 ± 8.458, their CPSS score was 19.21 ± 7.265, and their CD-RISC score was 64.26 ± 15.129 (Tenacity factor score: 31.70 ± 8.066, Strength factor score: 21.60 ± 5.066, Optimism factor scores: 10.96 ± 3.189). The CPSS score was positively correlated with the SAS score (r = 0.66; P < 0.01), the CPSS score was negatively correlated with the CD-RISC score (r = -0.617, P < 0.01), and the SAS score was negatively correlated with the CD-RISC score (r = -0.477, P < 0.01). The job position, age, and political status of the CSSD staff were the main factors affecting their mental state; for example, the CPSS score and SAS score of the CSSD nurses were significantly different from those of the CSSD logistic staff (P < 0.01). Conclusion: During the epidemic, the CSSD staff’s psychological resilience was at a low level; the anxiety level of the CSSD nurses was higher than that of the CSSD logistic staff. Therefore, more attention should be given to the mental health of the CSSD staff, including taking protective measures regarding the risk factors to ensure they can maintain a healthy mental state.

Mental State of Central Sterile Supply Department Staff During COVID-19 Epidemic and CART Analysis

10.21203/rs.3.rs-37452/v3 ◽

2020 ◽

Author(s):

Wei Pan ◽

Juan Hu ◽

Liangying Yi

Keyword(s):

Mental State ◽

Factor Score ◽

Measurement Data ◽

Regression Tree ◽

General Information ◽

Chi Square ◽

Factors Affecting ◽

Abstract Background: During the COVID-19 epidemic, the central sterile supply department (CSSD) staff handled many devices, implements and non-disposable protective articles used by suspected or confirmed COVID-19 patients. As a result, the CSSD staff may have experienced psychological stress, however, the mental state of the CSSD staff during the COVID-19 epidemic has been rarely studied. We aim to investigate the mental state of the CSSD staff and relevant influencing factors experienced during the COVID-19 epidemic.Methods: The survey utilising a general information questionnaire, Chinese perceived stress scale (CPSS), self-rating anxiety scale (SAS), and Connor-Davidson resilience scale (CD-RISC) was conducted with 423 CSSD staff members from 35 hospitals in Sichuan Province, China. Data was analysed in SPSS24.0. Classification and regression tree (CART) was utilised to analyse variables and find variation between groups. A chi-square test was performed on enumeration data, and t-test and analysis of variance were performed on measurement data.Results: The CSSD staff’s SAS score was 37.39 ± 8.458, their CPSS score was 19.21 ± 7.265, and their CD-RISC score was 64.26 ± 15.129 (Tenacity factor score: 31.70 ± 8.066, Strength factor score: 21.60 ± 5.066, Optimism factor scores: 10.96 ± 3.189). The CPSS score was positively correlated with the SAS score (r = 0.66; P < 0.01), the CPSS score was negatively correlated with the CD-RISC score (r = -0.617, P < 0.01), and the SAS score was negatively correlated with the CD-RISC score (r = -0.477, P < 0.01). The job position, age, and political status of the CSSD staff were the main factors affecting their mental state; for example, the CPSS score and SAS score of the CSSD nurses were significantly different from those of the CSSD logistic staff (P < 0.01). Conclusion: During the epidemic, the CSSD staff’s psychological resilience was at a low level; the anxiety level of the CSSD nurses was higher than that of the CSSD logistic staff. Therefore, more attention should be given to the mental health of the CSSD staff, including taking protective measures regarding the risk factors to ensure they can maintain a healthy mental state.

A Study on Re-Engagement and Stabilization Time on Take-Over Transition in a Highly Automated Driving System

Electronics ◽

10.3390/electronics10030344 ◽

2021 ◽

Vol 10 (3) ◽

pp. 344

Author(s):

Hyunsuk Kim ◽

Woojin Kim ◽

Jungsook Kim ◽

Seung-Jun Lee ◽

Daesub Yoon ◽

...

Keyword(s):

Human Factors ◽

Response Times ◽

Regression Tree ◽

Traffic Density ◽

Automated Driving ◽

Stabilization Time ◽

Factors Affecting ◽

Cart Analysis ◽

Level 3

In the case of level 3 automated vehicles, in order to safely and quickly transfer control authority rights to manual driving, it is necessary that a study be conducted on the characteristics of human factors affecting the transition of manual driving. In this study, we conducted three experiments to compare the characteristics of human factors that influence the driver’s quality of response when re-engaging and stabilizing manual driving. The three experiments were conducted sequentially by dividing them into a normal driving situation, an obstacle occurrence situation in front, and an obstacle and congestion on surrounding roads. We performed a statistical analysis and classification and regression tree (CART) analysis using experimental data. We found that as the number of trials increased, there was a learning effect that shortened re-engagement times and increased the proportion of drivers with good response times. We found that the stabilization time increased as the experiment progressed, as obstacles appeared in front and traffic density increased in the surrounding lanes. The results of the analysis are useful for vehicle developers designing safer human–machine interfaces and for governments developing guidelines for automated driving systems.

Edible Insects: Preliminary Study about Perceptions, Attitudes, and Knowledge on a Sample of Portuguese Citizens

Foods ◽

10.3390/foods10040709 ◽

2021 ◽

Vol 10 (4) ◽

pp. 709

Author(s):

Sofia G. Florença ◽

Paula M. R. Correia ◽

Cristina A. Costa ◽

Raquel P. F. Guiné

Keyword(s):

Nutritive Value ◽

Meat Products ◽

Regression Tree ◽

Good Alternative ◽

Categorical Variables ◽

Final Conclusion ◽

Edible Insects ◽

Chi Square ◽

Alternative Sources

This study investigated the knowledge, attitudes, consumption habits, and degree of acceptability of edible insects (EI) or derived products among Portuguese consumers. This work consisted of a questionnaire survey, undertaken on a sample of 213 participants. For the treatment of data, basic descriptive statistics were used, complemented with chi-square tests to assess some associations between categorical variables. Moreover, a tree classification analysis was carried out using a classification and regression tree (CRT) algorithm with cross-validation. The results indicated that people tend to have correct perceptions about the sustainability issues associated with the use of insects as alternative sources of protein; however, the level of knowledge and overall perception about their nutritive value is low. Regarding the consumption of EI, it was found that only a small part of the participants had already eaten them, doing it mostly abroad, by self-initiative, in a restaurant or at a party or event. Additionally, it was found that the reluctance to consume insects is higher if they are whole, but when they are transformed into ingredients used in food formulations, the level of acceptance increases. Furthermore, men have shown to have a better perception about EI, be more informed about sustainability, and have a higher level of acceptability when compared to women. As a final conclusion, it was observed that the Portuguese still show some resistance to adhere to the use of insects as replacements for meat products, but the market of insect based products can be a good alternative to overpass the neophobia associated with this type of food.

Validation and verification of predictive salivary biomarkers for oral health

Scientific Reports ◽

10.1038/s41598-021-85120-w ◽

2021 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Nagihan Bostanci ◽

Konstantinos Mitsakakis ◽

Beral Afacan ◽

Kai Bao ◽

Benita Johannsen ◽

...

Keyword(s):

Oral Health ◽

Predictive Accuracy ◽

Statistical Tests ◽

Area Under The Curve ◽

Regression Tree ◽

High Sensitivity ◽

Oral Health Status ◽

Cart Analysis ◽

Salivary Biomarkers

AbstractOral health is important not only due to the diseases emerging in the oral cavity but also due to the direct relation to systemic health. Thus, early and accurate characterization of the oral health status is of utmost importance. There are several salivary biomarkers as candidates for gingivitis and periodontitis, which are major oral health threats, affecting the gums. These need to be verified and validated for their potential use as differentiators of health, gingivitis and periodontitis status, before they are translated to chair-side for diagnostics and personalized monitoring. We aimed to measure 10 candidates using high sensitivity ELISAs in a well-controlled cohort of 127 individuals from three groups: periodontitis (60), gingivitis (31) and healthy (36). The statistical approaches included univariate statistical tests, receiver operating characteristic curves (ROC) with the corresponding Area Under the Curve (AUC) and Classification and Regression Tree (CART) analysis. The main outcomes were that the combination of multiple biomarker assays, rather than the use of single ones, can offer a predictive accuracy of > 90% for gingivitis versus health groups; and 100% for periodontitis versus health and periodontitis versus gingivitis groups. Furthermore, ratios of biomarkers MMP-8, MMP-9 and TIMP-1 were also proven to be powerful differentiating values compared to the single biomarkers.

Cognitive and Behavioral Domains That Reliably Differentiate Normal Aging and Dementia in Down Syndrome

Brain Sciences ◽

10.3390/brainsci11091128 ◽

2021 ◽

Vol 11 (9) ◽

pp. 1128

Author(s):

Jordan P. Harp ◽

Lisa M. Koehl ◽

Kathryn L. Van Pelt ◽

Christy L. Hom ◽

Eric Doran ◽

...

Keyword(s):

Primary Care ◽

Down Syndrome ◽

Area Under The Curve ◽

Regression Tree ◽

Vineland Adaptive Behavior Scales ◽

Cart Analysis ◽

Dementia Screening ◽

Significant Difference ◽

Unit Increase

Primary care integration of Down syndrome (DS)-specific dementia screening is strongly advised. The current study employed principal components analysis (PCA) and classification and regression tree (CART) analyses to identify an abbreviated battery for dementia classification. Scale- and subscale-level scores from 141 participants (no dementia n = 68; probable Alzheimer’s disease n = 73), for the Severe Impairment Battery (SIB), Dementia Scale for People with Learning Disabilities (DLD), and Vineland Adaptive Behavior Scales—Second Edition (Vineland-II) were analyzed. Two principle components (PC1, PC2) were identified with the odds of a probable dementia diagnosis increasing 2.54 times per PC1 unit increase and by 3.73 times per PC2 unit increase. CART analysis identified that the DLD sum of cognitive scores (SCS < 35 raw) and Vineland-II community subdomain (<36 raw) scores best classified dementia. No significant difference in the PCA versus CART area under the curve (AUC) was noted (D(65.196) = −0.57683; p = 0.57; PCA AUC = 0.87; CART AUC = 0.91). The PCA sensitivity was 80% and specificity was 70%; CART was 100% and specificity was 81%. These results support an abbreviated dementia screening battery to identify at-risk individuals with DS in primary care settings to guide specialized diagnostic referral.

Artificial liver support system therapy in acute-on-chronic hepatitis B liver failure: Classification and regression tree analysis

Scientific Reports ◽

10.1038/s41598-019-53029-0 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 3

Author(s):

Kaizhou Huang ◽

Feiyang Ji ◽

Zhongyang Xie ◽

Daxian Wu ◽

Xiaowei Xu ◽

...

Keyword(s):

High Risk ◽

Hepatitis B ◽

Regression Tree ◽

Artificial Liver ◽

Liver Support ◽

Artificial Liver Support ◽

Cart Analysis ◽

Classification And Regression ◽

Cart Model

Abstract Artificial liver support systems (ALSS) are widely used to treat patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). The aims of the present study were to investigate the subgroups of patients with HBV-ACLF who may benefit from ALSS therapy, and the relevant patient-specific factors. 489 ALSS-treated HBV-ACLF patients were enrolled, and served as derivation and validation cohorts for classification and regression tree (CART) analysis. CART analysis identified three factors prognostic of survival: hepatic encephalopathy (HE), prothrombin time (PT), and total bilirubin (TBil) level; and two distinct risk groups: low (28-day mortality 10.2–39.5%) and high risk (63.8–91.1%). The CART model showed that patients lacking HE and with a PT ≤ 27.8 s and a TBil level ≤455 μmol/L experienced less 28-day mortality after ALSS therapy. For HBV-ACLF patients with HE and a PT > 27.8 s, mortality remained high after such therapy. Patients lacking HE with a PT ≤ 27.8 s and TBil level ≤ 455 μmol/L may benefit markedly from ALSS therapy. For HBV-ACLF patients at high risk, unnecessary ALSS therapy should be avoided. The CART model is a novel user-friendly tool for screening HBV-ACLF patient eligibility for ALSS therapy, and will aid clinicians via ACLF risk stratification and therapeutic guidance.

A Novel Comprehensive Clinical Stratification Model to Refine Prognosis of Glioblastoma Patients Undergoing Surgical Resection

Cancers ◽

10.3390/cancers12020386 ◽

2020 ◽

Vol 12 (2) ◽

pp. 386 ◽

Cited By ~ 1

Author(s):

Tamara Ius ◽

Fabrizio Pignotti ◽

Giuseppe Maria Della Pepa ◽

Giuseppe La Rocca ◽

Teresa Somma ◽

...

Keyword(s):

Surgical Resection ◽

Classification Tree ◽

Prognostic Score ◽

Regression Tree ◽

Image Data ◽

Extent Of Resection ◽

Postoperative Treatment ◽

Time Data ◽

Despite recent discoveries in genetics and molecular fields, glioblastoma (GBM) prognosis still remains unfavorable with less than 10% of patients alive 5 years after diagnosis. Numerous studies have focused on the research of biological biomarkers to stratify GBM patients. We addressed this issue in our study by using clinical/molecular and image data, which is generally available to Neurosurgical Departments in order to create a prognostic score that can be useful to stratify GBM patients undergoing surgical resection. By using the random forest approach [CART analysis (classification and regression tree)] on Survival time data of 465 cases, we developed a new prediction score resulting in 10 groups based on extent of resection (EOR), age, tumor volumetric features, intraoperative protocols and tumor molecular classes. The resulting tree was trimmed according to similarities in the relative hazard ratios amongst groups, giving rise to a 5-group classification tree. These 5 groups were different in terms of overall survival (OS) (p < 0.000). The score performance in predicting death was defined by a Harrell’s c-index of 0.79 (95% confidence interval [0.76–0.81]). The proposed score could be useful in a clinical setting to refine the prognosis of GBM patients after surgery and prior to postoperative treatment.