Analysis of social and psychological factors influencing the treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019.

Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio OR=5.618, 95% confidence interval CI) 2.136-14.776, P0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.

PSYCHOLOGICAL DISTRESS OVER 12 MONTHS POST-DIAGNOSIS IN A NATIONAL EARLY INFLAMMATORY ARTHRITIS COHORT

BackgroundIn inflammatory arthritis patients, the concomitant decline of their mental wellbeing is an increasing concern[1,2]. It is important to not only describe the trajectory of psychological distress in early disease stages, but also understand which clinical outcome measures are most associated with these changes.ObjectivesUsing data from the National Early Inflammatory Arthritis Audit (NEIAA), we assessed trends in psychological wellbeing over 12 months after initial diagnosis and mapped these against clinical outcomes to identify significant associations.MethodsNEIAA collects data from patients referred with suspected early inflammatory arthritis in rheumatology services in England and Wales. We used data provided by 20,472 patients eligible for follow-up (diagnosis of inflammatory arthritis) between May 1st, 2018, and April 1st, 2022. Data items included baseline demographics e.g., age and gender, and clinical variables e.g., rheumatic disease comorbidity index (RDCI), DAS28, and patient reported outcomes.Psychological distress was measured by the sum score of Patient Health Questionnaire Anxiety and Depression Screener (PHQ4ADS). Using mixed effects regression models, we analysed the co-variability of PHQ4ADS with demographic factors and clinical outcomes over 12 months. Time was included as a dummy-coded covariant.ResultsThe analysis included 36% of patients (7,378 out of 20,472) who completed the baseline patient outcome survey. In this cohort, PHQ4ADS scores decreased from a baseline average of 4.7 (CI: [4.6, 4.8]) to 2.62 (CI: [2.5, 2.8]) at 12 months post-diagnosis. The proportion of patients screening positive decreased from 50.0% (CI: [48.9, 51.1]) at baseline to 23.8% (CI: [21.8, 25.9]) at 12 months.At baseline, psychological distress correlated significantly with age, gender, ethnicity, RDCI, prior depression diagnosis, and baseline DAS28 (Figure 1). No significant correlations were found between psychological distress and working diagnosis, seropositivity, or the assessment being recorded after the start of the COVID-19 pandemic. Younger ages were nonlinearly associated with higher distress levels (coefficient per decade: -0.006;p<0.001;CI: [-0.009, -0.003]) (Figure 1a). Distress levels in females were higher than that of males (coefficient: 0.5;p<0.001;CI: [0.4, 0.7]) (Figure 1b). White patients reported lower PHQ4ADS scores compared to non-white patients (coefficient: -0.7;p<0.001;CI: [-1.0, -0.4]) (Figure 1c). Higher distress levels were also associated with higher RDCI (coefficient: 0.2;p<0.001;CI: [0.1, 0.3]) and prior diagnosis of depression (coefficient: 1.8;p<0.001;CI: [1.5, 2.2]) (Figure 1d, 1e). Furthermore, higher baseline DAS28 scores correlated with more severe psychological distress (coefficient: 0.8;p<0.001;CI: [0.7, 0.8]) (Figure 1f).By 12-months, psychological distress decreased significantly overall, which correlated significantly with ethnicity (coefficient: 0.8;p=0.005;CI: [0.3, 1.4]) and baseline DAS28 (coefficient: -0.5;p<0.001;CI: [-0.6, -0.4]). Compared to white patients, the reduction was significantly greater for non-white patients, but the level of distress was no longer different at 12 months (Figure 1c). While those with higher baseline DAS28 showed a greater reduction in psychological distress, the distress levels remained higher at 12 months (Figure 1f).Figure 1.Changes in psychological distress correlated with age, gender, ethnicity, RDCI, prior depression diagnosis, and baseline DAS28.[Figure omitted. See PDF]ConclusionIn this early inflammatory arthritis cohort, mental health burden was high. Age, gender, ethnicity, RDCI, prior depression diagnosis and baseline DAS28 significantly correlated with psychological distress at baseline. Supporting mental health should be a focus of clinical care for this population and it may be beneficial to use an approach that is culturally valid for non-white patients and accounts for multimorbidity.References[1]Euesden, J, et al. Psychosomatic medicine 79.6 (2017): 638.[2]Lwin, MN, et al. Rheumatology and therapy 7.3 (2020): 457-471.AcknowledgementsThe authors would like to thank the Healthcare Quality Improvement Partnership (HQIP) as the commisioner of NEIAA, British Society for Rheumatology as the audit providers, Net Solving as the audit platform developers, and the Wellcome Trust (ST12406) for funding to support L.Z..Disclosure of InterestsLucy Zhao: None declared, James Galloway Speakers bureau: Has received honoraria from AbbVie Celgene, Chugai, Gillead, Janssen, Eli Lilly, Pfizer, Roche, and UCB, Jo Ledingham: None declared, Sarah Gallagher: None declared, Neena Garnavos: None declared, Paul Amlani-Hatcher: None declared, Nicky Wilson: None declared, Lewis Carpenter Consultant of: Statistical consultancy for Pfizer, Kirsty Bannister: None declared, Sam Norton Speakers bureau: Has received honoraria from Janssen and Pfizer.

METHODOLOGY for ASSESSING the FINANCIAL SECURITY of ENTERPRISES in the POST-PANDEMIC PERIOD of DIGITAL ECONOMY

The article considers the approaches to assessing the financial security of enterprises presented in the literature, determines the rsistance of the textile industry of Uzbekistan to the negative impact of the coronavirus pandemic on the basis of statistical data, and reveals a significant differentiation of textile industry enterprises in terms of financial stability. Based on data on small enterprises in the textile industry of Uzbekistan, a method for assessing the financial security of an enterprise in the post-pandemic period is proposed and tested, taking into account the complex influence of non-financial parameters of economic security and assessing the deviations of the economic situation at a given enterprise from the patterns emerging in the relevant segment of the economy. In this research an econometric model was developed to determine the factors affecting the chemical industry and express their interrelationship, based on the conducted econometric analysis, the directions of development in our country were determined. According to the authors, it is necessary to continue these directions in order to ensure the economic security of industry enterprises in the country. © 2022 ACM.

Within-group estimators for unbalanced-panel data regression model of the open unemployment rate data in east kalimantan province

The COVID-19 pandemic has hit hard the Indonesian economy. Many businesses had to close because they could not cover operational costs, and many workers were laid off creating an unemployment crisis. Unemployment causes people's productivity and income to decrease, leading to poverty and other social problems, making it a crucial problem and great concern for the nation. Economic conditions during this pandemic have also provided an unusual pattern in economic data, in which outliers may occur, leading to biased parameter estimation results. For that reason, it is necessary to deal with outliers in research data appropriately. This study aims to find within-group estimators for unbalanced panel data regression model of the Open Unemployment Rate (OUR) in East Kalimantan Province and the factors that influence it. The method used is the within transformation with mean centering and median centering processing methods. The results of this study may provide advice on factors that can increase and decrease the OUR of East Kalimantan Province. The results show that the best model for estimating OUR data in East Kalimantan Province is the within-transformation estimation method using median centering. According to the best model, the Human Development Index (HDI) and Gross Regional Domestic Product (GRDP) are two factors that influence the OUR of East Kalimantan Province (GRDP). © 2023, International Association of Engineers. All rights reserved.

COVID-19 Data Prediction and Visualization in Mainland China

Contemporarily, COVID-19 shows a sign of recurrence in Mainland China. To better understand the situation, this paper investigates the growth pattern of COVID-19 based on the research of past data through regression models. The proposed work collects the data on COVID-19 in Mainland China from January 21st, 2020, to April 30th, 2020, including confirmed, recovered, and death cases. Based on polynomial regression and support vector machine regressor, it predicts the further trend of COVID-19. The paper uses root mean squared error to evaluate the performance of both models and concludes that there is no best model due to the high frequency of daily changes. According to the analysis, support vector machine regressors fit the growth of COVID-19 confirmed case better than polynomial regression does. The best solution is to utilize different types of models to generate a range of prediction result. These results shed light on guiding further exploration of the growth of COVID-19. © 2023 SPIE.

IMPAIRED HEALTH-RELATED QUALITY OF LIFE IN PATIENTS WITH IDIOPATHIC INFLAMMATORY MYOPATHIES: A CROSS-SECTIONAL ANALYSIS FROM AN INTERNATIONAL E-SURVEY

BackgroundComprehensive and large-scale assessment of health-related quality of life in patients with idiopathic inflammatory myopathies (IIMs) worldwide is lacking. The second COVID-19 vaccination in autoimmune disease (COVAD-2) study [1] is an international, multicentre, self-reported e-survey assessing several aspects of COVID-19 infection and vaccination as well as validated patient-reported outcome measures (PROMs) to outline patient experience in various autoimmune diseases (AIDs), with a particular focus on IIMs.ObjectivesTo investigate physical and mental health in a global cohort of IIM patients compared to those with non-IIM autoimmune inflammatory rheumatic diseases (AIRDs), non-rheumatic AIDs (NRAIDs), and those without AIDs (controls), using Patient-Reported Outcome Measurement Information System (PROMIS) global health data obtained from the COVAD-2 survey.MethodsDemographics, AID diagnoses, comorbidities, disease activity, treatments, and PROMs were extracted from the COVAD-2 database. The primary outcomes were PROMIS Global Physical Health (GPH) and Global Mental Health (GMH) scores. Secondary outcomes included PROMIS physical function short form-10a (PROMIS PF-10a), pain visual analogue scale (VAS), and PROMIS Fatigue-4a scores. Each outcome was compared between IIMs, non-IIM AIRDs, NRAIDs, and controls. Factors affecting GPH and GMH scores in IIMs were identified using multivariable regression analysis.ResultsA total of 10,502 complete responses from 1582 IIMs, 4700 non-IIM AIRDs, 545 NRAIDs, and 3675 controls, which accrued as of May 2022, were analysed. Patients with IIMs were older [59±14 (IIMs) vs. 48±14 (non-IIM AIRDs) vs. 45±14 (NRAIDs) vs. 40±14 (controls) years, p<0.001] and more likely to be Caucasian [82.7% (IIMs) vs. 53.2% (non-IIM AIRDs) vs. 62.4% (NRAIDs) vs. 34.5% (controls), p<0.001]. Among IIMs, dermatomyositis (DM) and juvenile DM were the most common (31.4%), followed by inclusion body myositis (IBM) (24.9%). Patients with IIMs were more likely to have comorbidities [68.1% (IIMs) vs. 45.7% (non-IIM AIRDs) vs. 45.1% (NRAIDs) vs. 26.3% (controls), p<0.001] including mental disorders [33.4% (IIMs) vs. 28.2% (non-IIM AIRDs) vs. 28.4% (NRAIDs) vs. 17.9% (controls), p<0.001].GPH median scores were lower in IIMs compared to NRAIDs or controls [13 (interquartile range 10–15) IIMs vs. 13 (11–15) non-IIM AIRDs vs. 15 (13–17) NRAIDs vs. 17 (15–18) controls, p<0.001] and PROMIS PF-10a median scores were the lowest in IIMs [34 (25–43) IIMs vs. 40 (34–46) non-IIM AIRDs vs. 47 (40–50) NRAIDs vs. 49 (45–50) controls, p<0.001]. GMH median scores were lower in AIDs including IIMs compared to controls [13 (10–15) IIMs vs. 13 (10–15) non-IIM AIRDs vs. 13 (11–16) NRAIDs vs. 15 (13–17) controls, p<0.001]. Pain VAS median scores were higher in AIDs compared to controls [3 (1–5) IIMs vs. 4 (2–6) non-IIM AIRDs vs. 2 (0–4) NRAIDs vs. 0 (0–2) controls, p<0.001]. Of note, PROMIS Fatigue-4a median scores were the highest in IIMs [11 (8–14) IIMs vs. 8 (10–14) non-IIM AIRDs vs. 9 (7–13) NRAIDs vs. 7 (4–10) controls, p<0.001].Multivariable regression analysis in IIMs identified older age, male sex, IBM, comorbidities including hypertension and diabetes, active disease, glucocorticoid use, increased pain and fatigue as the independent factors for lower GPH scores, whereas coexistence of interstitial lung disease, mental disorders including anxiety disorder and depression, active disease, increased pain and fatigue were the independent factors for lower GMH scores.ConclusionBoth physical and mental health are significantly impaired in patients with IIMs compared to those with non-IIM AIDs or those without AIDs. Our results call for greater attention to patient-reported experience and comorbidities including mental disorders to provide targeted approaches and optimise global well-being in patients with IIMs.Reference[1]Fazal ZZ, Sen P, Joshi M, et al. COVAD survey 2 long-term outcomes: unmet need and protocol. Rheumatol Int. 2022;42:2151–58.AcknowledgementsThe authors a e grateful to all respondents for completing the questionnaire. The authors also thank The Myositis Association, Myositis India, Myositis UK, the Myositis Global Network, Cure JM, Cure IBM, Sjögren's India Foundation, EULAR PARE for their contribution to the dissemination of the survey. Finally, the authors wish to thank all members of the COVAD study group for their invaluable role in the data collection.Disclosure of InterestsAkira Yoshida: None declared, Yuan Li: None declared, Vahed Maroufy: None declared, Masataka Kuwana Speakers bureau: Boehringer Ingelheim, Ono Pharmaceuticals, AbbVie, Janssen, Astellas, Bayer, Asahi Kasei Pharma, Chugai, Eisai, Mitsubishi Tanabe, Nippon Shinyaku, Pfizer, Consultant of: Corbus, Mochida, Grant/research support from: Boehringer Ingelheim, Ono Pharmaceuticals, Naveen Ravichandran: None declared, Ashima Makol Consultant of: Boehringer-Ingelheim, Parikshit Sen: None declared, James B. Lilleker: None declared, Vishwesh Agarwal: None declared, Sinan Kardes: None declared, Jessica Day Grant/research support from: CSL Limited, Marcin Milchert: None declared, Mrudula Joshi: None declared, Tamer A Gheita: None declared, Babur Salim: None declared, Tsvetelina Velikova: None declared, Abraham Edgar Gracia-Ramos: None declared, Ioannis Parodis Grant/research support from: Amgen, AstraZeneca, Aurinia Pharmaceuticals, Eli Lilly, Gilead Sciences, GlaxoSmithKline, Janssen Pharmaceuticals, Novartis, and F. Hoffmann-La Roche, Elena Nikiphorou Speakers bureau: Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, Eli Lilly, Consultant of: Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, Eli Lilly, Grant/research support from: Pfizer, Eli Lilly, Ai Lyn Tan Speakers bureau: AbbVie, Gilead, Janssen, Eli Lilly, Novartis, Pfizer, UCB, Consultant of: AbbVie, Gilead, Janssen, Eli Lilly, Novartis, Pfizer, UCB, Arvind Nune: None declared, Lorenzo Cavagna: None declared, Miguel A Saavedra Consultant of: AbbVie, GlaxoSmithKline, Samuel Katsuyuki Shinjo: None declared, Nelly Ziade Speakers bureau: AbbVie, Boehringer-Ingelheim, Eli Lilly, Janssen, Pfizer, Roche, Consultant of: AbbVie, Boehringer-Ingelheim, Eli Lilly, Janssen, Pfizer, Roche, Grant/research support from: AbbVie, Boehringer-Ingelheim, Eli Lilly, Janssen, Pfizer, Roche, Johannes Knitza: None declared, Oliver Distler Speakers bureau: AbbVie, Amgen, Bayer, Boehringer Ingelheim, Janssen, Medscape, Novartis, Consultant of: 4P-Pharma, AbbVie, Acceleron, Alcimed, Altavant, Amgen, AnaMar, Arxx, AstraZeneca, Baecon, Blade, Bayer, Boehringer Ingelheim, Corbus, CSL Behring, Galderma, Galapagos, Glenmark, Gossamer, iQvia, Horizon, Inventiva, Janssen, Kymera, Lupin, Medscape, Merck, Miltenyi Biotec, Mitsubishi Tanabe, Novartis, Prometheus, Redxpharma, Roivant, Sanofi, Topadur, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Kymera, Mitsubishi Tanabe, Novartis, Roche, Hector Chinoy Grant/research support from: Eli Lilly, UCB, Vikas Agarwal: None declared, Rohit Aggarwal Consultant of: Mallinckrodt, Octapharma, CSL Behring, Bristol Myers-Squibb, EMD Serono, Kezar, Pfizer, AstraZeneca, Alexion, Argenx, Boehringer Ingelheim (BI), Corbus, Janssen, Kyverna, Roivant, Merck, Galapagos, Actigraph, Abbvie, Scipher, Horizontal Therapeutics, Teva, Biogen, Beigene, ANI Pharmaceutical, Nuvig, Capella, CabalettaBio, Grant/research support from: Bristol Myers-Squibb, Pfizer, Mallinckrodt, Janssen, Q32, EMD Serono, Boehringer Ingelheim, Latika Gupta: None declared.

Impact of Teachers' Support Strategies on Students' Engagement of Online College English Class Experiences

During the covid-19 pandemic, students' online learning quality is imbued with teachers' support strategies while students' learning engagement is another great indicator underlies their learning experiences. Through a questionnaire survey of 500 freshmen who have had their college English class online in 2022 fall, an investigation using exploratory factor analysis, Pearson correlation analysis, stepwise regression analysis and parallel mediator model reveals the impact of teachers' support strategies (the six dimensions of challenge, authentic context, curiosity, autonomy, recognition and feedback) on the learners' online college English learning engagement (the four dimensions of cognitive engagement, behavioral engagement, emotional engagement, social engagement), thus particular concern is also given to the correlation with students' online learning experiences. It was found that even under diversified and comprehensive guiding strategies from teachers, university students' online college English learning engagement is at the medium level, among which the cognitive engagement should be devoted more. The experimental data also shows that teachers' support strategies have significant influence on learners' engagement, especially teachers' feedback and challenge setting will stimulate students to involve more in their study. In addition, both teachers' support strategies and students' learning engagement involves significant reflection of learning experiences accordingly. Based on this learning concept, related proposals see different degrees of prominence reflected in online instructional design, teachers' and students' feedback literacy, and technology-enabled innovative teaching practice are put forward, in order to effectively play the role of teacher scaffolding, learning experiences enrichment and students' engagement enhancement of online English learning. © 2023 IEEE.

Research on the Relationship between Teacher Expectations and College Students' Online English Learning Engagement

As a critical influencing factor of learning engagement, teacher expectation plays a vital role in ensuring the quality of online teaching under COVID-19. This paper investigates the relationship between teacher expectations (three dimensions of teacher support, teaching interaction, and academic feedback) on students' online English learning engagement (three dimensions of cognitive engagement, behavioral engagement, and emotional engagement) in e-learning through a questionnaire survey of 513 college students. Pearson correlation analysis and multiple regression analysis were applied as research methods. The results manifest that college students' online English learning engagement was above average, but emotional engagement needs improvement. In addition, teacher expectations of teaching interaction positively and significantly predict English e-learning engagement. Based on this, the article puts forward suggestions on the future of online teaching from the aspects of online teaching design, feedback quality of teachers and students, innovative teaching practice of technology empowerment to effectively play the role of teachers as scaffolding and improve the effectiveness of online English teaching. © 2023 IEEE.

Stress reactions and health problems in hospital personnel during the COVID-19 pandemic-A longitudinal, multicenter study

Background: The overarching aim of the study was to (1) investigate how working with COVID-19 patients has impacted work environment, and (2) to identify how factors in the work environment impact adverse health outcomes among hospital personnel (HP), throughout the four waves of the pandemic. Material(s) and Method(s): In a web-based survey altogether 2472 HP participated from four large university hospitals in Norway, whereof N = 680 in April-June 2020 (T1), N = 1073 in December-January 2020/2021 (T2), N = 818 in April-May 2021 (T3), and N = 972 in December 2021-February 2022 (T4). At each time point participants reported on pandemic related work tasks, work environment and adverse health outcomes. Somatic symptoms, psychological distress, posttraumatic stress symptoms and burnout served as outcomes of multivariable linear regression models. The percentage of responders involved in ICU treatment of COVID-19 patients varied between 21% and 40% from T1-T4. Result(s): Reported stressors altered in strength during the 4 waves. Preliminary results indicate that exposure to patients with COVID-19 was associated with more frequent experience of work environmental factors. Compared to colleagues not working with patients with COVID-19 HP reported challenges related to professional competency and training, predictability in teams and work environment, manageable workload, adequate help and support for work stress management, user-friendliness of Personal Protection Equipment and infection protection safety. Furthermore, these environmental factors were associated with symptoms of psychological unhealth on at least one timepoint. Conclusion(s): The results may help guide organizational efforts to maintain professional competency and to reduce stress more efficiently among hospital personnel at different stages in response to long-term crises.

Workplace violence and associations with health outcomes in public health administration agencies in Taiwan: a survey during the COVID-19 pandemic

Objectives: To investigate the prevalence of workplace violence in public health administration agencies and its effects on health outcomes. Methods: A survey was conducted in March 2022. Staff who had been working for at least one year in the Ministry of Health and Welfare or its subordinate agencies, the Department of Health, or in public health centers were recruited. Data were collected anonymously with a structured, online questionnaire. A total of 492 valid questionnaires were collected. Results: A total of 48.17% participants reported having experienced workplace violence (physical, psychological, verbal, or sexual). The most common type of violence was verbal (43.50%), followed by psychological (31.71%). Supervisors were the primary perpetrators of verbal and psychological violence, followed by clients and colleagues. Staff reported long working hours and high levels of psychological and physical stress. Furthermore, 22.97% of workers reported poor self-rated health, 60.57% had personal burnout levels higher than 50, and 63.41% reported poor mental health. Regression analyses showed that low workplace justice was most strongly associated with internal verbal and psychological violence, whereas routine work requiring interaction with the public was most strongly associated with external verbal violence. Staff who had experienced workplace violence in the past year had significantly higher risks of poor self-rated health, mental health, and personal burnout, and poor health was more strongly associated with workplace violence that originated inside the organization than with workplace violence that originated from outside the organization. Conclusions: This survey was conducted on-line anonymously, so the representativeness of our findings might be limited. However, heavy workloads and workplace violence in public health administration agencies during the COVID-19 pandemic are important issues deserving urgent attention. (Taiwan J Public Health. 2023;42(1) :42-61)

The Application of PageRank model in urban epidemic prevention and control

The ongoing COVID-19 epidemic has had a great impact on social activities and the economy. The usage technical analysis tools to provide a more accurate and efficient reference for epidemic control measures is of great significance. This paper analyzes the characteristics and deficiencies of the existing technical methods, such as regression model, simulation calculation, differential equation and so on. By analyzing past outbreak cases and comparing the epidemic prevention measures of different cities, we discuss the importance of early and timely prevention in controlling the epidemic, and the importance of analyzing and formulating plans in advance. We then make the key observation that the spread of the virus is related to the topology of the urban network. This paper further proposes an epidemic analysis model of the optimized PageRank model, and gives a ranking algorithm for virus transmission risk levels based on road nodes, forming a visual risk warning level map, and applies the algorithm to the epidemic analysis of Yuegezhuang area in Beijing. Finally, more in-depth research directions and suggestions for prevention and control measures are put forward. © 2023 SPIE.

Using the "omnicell" automatic drug dispensing cabinet to monitor sedative drugs in a critical care unit

Introduction: Automatic drug dispensers are now widely used in critical care.1-2 They can provide information about dispensed drugs. Good practice in sedation restricts the use of sedatives and titrates doses to defined responses.3-4 Objectives: To extract drug dispenser issuing records for sedatives and link these to patient records to evaluate sedative use. Method(s): in October 2019, we introduced two Omnicell XT automated dispensing cabinets (Omnicell inc. CA, USA) into a 42 bedded general/neurological unit. ICNARC (Intensive care national audit and research centre) and CCMDS (Critical care minimum data set) data was collected using the Ward Watcher program. Dispenser issuing records for alfentanil, propofol and midazolam were obtained as Excel files for 13 months from January 2020. Output time stamps were converted to dates and times. Outputs were linked to outputs of the ICNARC and CCMDS records for the patients that the drugs were issued to. All the outputs had patients identified by their unique hospital numbers. These were used in Excel "power queries" to produce a spread sheet with a single row per patient. Multiple admissions used the first diagnosis, the final outcome and the total length of stay. The total dose of sedatives was calculated from ampoule dose and number. The duration of treatment was calculated from the first and last issues of the drug. ICNARC codes were used to identify the primary system in the admission diagnostic code and those patients admitted for COVID-19. Variables were compared using Chi Squared, Mann-Whitney U and Kruskal Wallis Tests. The significance of associations was established using Spearman's Rho. Linear regression was used to define relationships more clearly. Result(s): Table one summarises the patient characteristics with respect to all admissions during the study period and for patients who had had the studied drugs issued to them. Midazolam was used in fewer patients, they were more likely to be male, heavier (p>0001) and to die than patients receiving Propofol or Alfentanil (p>0.001). With respect to diagnostic groups, all the sedatives, particularly Midazolam (p<0.001), were more likely to be used in patients with COVID-19. The relationship between the dose of sedative drugs and patient age and weight was explored using the dose per advanced respiratory day. All three drugs had a significant but weak negative relationship with age, lower doses being given to older people (Propofol r2 = 0.02, p=0.01. Alfentanil r2 = 0.04, p=0.00. Midazolam r2 = 0.07, p=0.00.). There was also a weak but significant relationship between increasing dose of Propofol with patient weight (r2 = 0.02, p=0.01), but there was no relation between weight and doses of the other drugs. Conclusion(s): Information from automatic drug dispensers can be interpreted and combined with other datasets to produce clinically relevant information. The limited weak relationships between drug dose and age and weight suggests that sedative drugs could have been better titrated to response.

The Impact of Strategic Experiential Modules (SEMs) Dimension on Visitor's Revisit Intention: A Lesson from the Sunrise of Java, Indonesia: Acces la Success

Mangrove tourism is one of the tourist destinations offered by tourism managers that is currently gaining popularity and popularity among tourists. Keeping tourists coming back can be a very effective strategy for developing tourist destinations. This study employs Experiential Marketing as a strategy to increase tourist interest. Because research in the field of experiential marketing in nature tourism destinations such as mangrove tourism is still limited, the topics of this study are experiential marketing and visitor visit intention. The purpose of this study was to determine the impact of strategic experiential modules (SEMs) on visitor revisits intention. The research method used is quantitative with the variable dimensions of SEMs and visitor revisits intention, a sample of 93 tourists with a purposive sampling technique, and multiple linear regression analysis techniques. The results showed that the sense, act, and relate variables had a positive and significant impact on the visitor revisits intention, while the feel variable had a positive but not significant impact, and the think variable had a negative but not significant impact on the visitor revisits intention.

Digital Banking through the Uncertain COVID Period: A Panel Data Study

This research investigates how the uncertainty caused by the COVID-19 pandemic has affected digital banking usage in India. The study is made by utilizing a panel of data consisting of 108 firm-month observations during covid period from 2020 to 2022, with data mainly collected to analyze the impact of COVID-19 uncertainty. Most of the determinants were collected from the RBI data website. The main emphasis of this study is on the utilization of digital banking services in the context of the pandemic, and the research assesses the factors that have influenced this trend, including the number of physical bank branches, the utilization of debit and credit cards at automated teller machines (ATMs) and points of sale (PoS), as well as the level of economic policy uncertainty (EPU). The analysis was conducted using panel regression analysis, a suitable method for handling the error components in the model that are either fixed or random. The findings indicate that the uncertainty caused by the pandemic has had a negative impact on the use of digital banking services. Additionally, the study highlights that the usage of debit and credit cards at PoS has significantly contributed to promoting the progress of digital banking services during the pandemic. Overall, this study provides valuable insights into how digital banking services have evolved during a period of significant uncertainty and disruption. © 2023 by the authors.

Unraveling the Impact of COVID-19 Pandemic Dynamics on Commercial Water-Use Variation

Water use was impacted significantly by the COVID-19 pandemic. Although previous studies quantitatively investigated the effects of COVID-19 on water use, the relationship between water-use variation and COVID-19 dynamics (i.e., the spatial-temporal characteristics of COVID-19 cases) has received less attention. This study developed a two-step methodology to unravel the impact of COVID-19 pandemic dynamics on water-use variation. First, using a water-use prediction model, the water-use change percentage (WUCP) indicator, which was calculated as the relative difference between modeled and observed water use, i.e., water-use variation, was used to quantify the COVID-19 effects on water use. Second, two indicators, i.e., the number of existing confirmed cases (NECC) and the spatial risk index (SRI), were applied to characterize pandemic dynamics, and the quantitative relationship between WUCP and pandemic dynamics was examined by means of regression analysis. We collected and analyzed 6-year commercial water-use data from smart meters of Zhongshan District in Dalian City, Northeast China. The results indicate that commercial water use decreased significantly, with an average WUCP of 59.4%, 54.4%, and 45.7%during the three pandemic waves, respectively, in Dalian. Regression analysis showed that there was a positive linear relationship between water-use changes (i.e., WUCP) and pandemic dynamics (i.e., NECC and SRI). Both the number of COVID-19 cases and their spatial distribution impacted commercial water use, and the effects were weakened by restriction strategy improvement, and the accumulation of experience and knowledge about COVID-19. This study provides an in-depth understanding of the impact of COVID-19 dynamics on commercial water use. The results can be used to help predict water demand under during future pandemic periods or other types of natural and human-made disturbance.

THE EMERGENCE OF FIBROMYALGIA FOLLOWING ACUTE COVID-19 INFECTION

BackgroundThe exact pathogenesis of fibromyalgia (FM) syndrome is unclear. However, different infections including hepatitis C virus, Human immunodeficiency virus and Lyme disease have already been implicated with the development of FM after their acute phase[1]. Imbalance between pro-inflammatory and anti-inflammatory cytokines has been suggested as a possible mechanism that facilitates the neuropathic pain[2].ObjectivesTo investigate the incidence of FM syndrome among convalesced individuals following hospitalization for Acute Coronavirus Disease-2019 (COVID-19) and to identify possible risk factors.MethodsWe performed a cross-sectional study on patients who were discharged after COVID-19 hospitalization from the Sheba Medical Center, Israel, between July 2020 to November 2020. A phone interview was performed consisting of the following questionnaires: the Fibromyalgia Survey Diagnostic Criteria Questionnaire, Sense of Coherence Questionnaire to evaluate resilience, and the Subjective Traumatic Outlook Questionnaire to assess the associated psychological aspects of the trauma. The incidence of post-COVID FM was calculated and regression models were performed to identify predictors.ResultsThe study population consisted of 198 eligible patients who completed the phone interview. The median age was 64 (52-72) and 37% were women. The median follow-up was 5.2 months (IQR 4.4-5.8). The incidence of FM was 15% (30 patients) and 87% (172 patients) had at least one FM-related symptom. Female gender was significantly associated with post-COVID FM (OR 3.65, p=0.002). In addition, high median Subjective Traumatic Outlook scores and low median Sense of Coherence scores were both significantly associated with post-COVID FM (OR 1.19, p<0.001 and OR 0.92, p<0.001, respectively).ConclusionFM is highly prevalent among COVID-19 convalescent patients. Our finding suggests that a significant subjective traumatic experience and a low resilience are highly associated with post-COVID FM.References[1]Buskila D, Atzeni F, Sarzi-Puttini P. Etiology of fibromyalgia: the possible role of infection and vaccination. Autoimmun Rev. 2008;8: 41-43. https://doi.org/10.1016/j.autrev.2008.07.023[2]Amital M, Ben-Shabat N, Amital H, Buskila D, Cohen AD, Amital D. COVID-19 associated hospitalization in 571 patients with fibromyalgia—A population-based study. PLoS ONE. 2021:16: e0261772. https://doi.org/10.1371/journal.pone.0261772Acknowledgements:NIL.Disclosure of InterestsNone Declared.

IMPACT OF THE COVID-19 PANDEMIC ON ADHERENCE TO DISEASE MODIFYING DRUGS AMONG PATIENTS WITH RHEUMATIC DISEASES: A POPULATION-BASED, INTERRUPTED TIME SERIES ANALYSIS

BackgroundAlthough studies have quantified adherence to medications among patients with rheumatic diseases (RD) during the COVID-19, lack of direct pre-pandemic comparison precludes understanding of impact of the pandemic.ObjectivesOur objective was to evaluate the effect of the COVID-19 pandemic on adherence to disease modifying drugs (DMARDs) including conventional synthetic (csDMARDs) and targeted synthetic (tsDMARDs).MethodsWe linked population-based health data on all physician visits, hospital admissions, and all dispensed medications, regardless of payer in British Columbia from 01/01/1996 to 3/31/2021. We identified prescriptions for csDMARDs (including methotrexate, hydroxychloroquine) and tsDMARDs, namely anti-TNFs (including infliximab, etanercept, adalimumab) and rituximab using drug identification numbers among indicated individuals with RD. We defined March 11, 2020, as the ‘index date' which corresponded to the date that mitigation measures for the COVID-19 pandemic were first introduced. We assessed adherence as proportion days covered (PDC), calculated monthly in the 12 months before and 12 months after the index date. We used interrupted time-series models, namely segmented regression to estimate changes and trends in adherence before and after the index date.ResultsOur analysis showed that the mean PDCs for all included DMARDs stayed relatively steady in the 12 months before and after mitigation measures were introduced (see Table 1). Adherence was highest among anti-TNFs, methotrexate, and azathioprine. Anti-TNFs were on a downward trajectory 12 months prior to the index date. Interrupted time-series modeling demonstrated statistically significant differences in the trends in PDCs post- vs. pre-mitigation measures for all anti-TNFS (slope [∂]: 1.38, standard error [SE]: 0.23), infliximab (∂: 1.35, SE: 0.23), adalimumab (∂: 0.82, SE: 0.25), and etanercept (∂: 1.07, SE: 0.25) (see Figure 1a). Conversely, the csDMARDs were on a flatter trajectory, and methotrexate (∂: -0.53, SE: 0.16), leflunomide (∂: 0.43, SE: 0.08), mycophenolate (∂: -1.26, SE: 0.48), cyclophosphamide (∂: 0.29, SE: 0.05), minocycline (∂: 0.04, SE: 0.02), chloroquine (∂: 0.02, SE: 0.00) showed statistically significant changes in estimated PDC trajectory after mitigation measures were introduced (see Figure 1b).ConclusionThis population-based study demonstrates that messaging and pandemic mitigation measures did not affect adherence to DMARDs.Table 1.Mean PDC 1 year before and after mitigation measures for the COVID-19 pandemic were introduced.MedicationMean PDC (%) 12 months before index dateMean PDC (%) 12 months after index datecsDMARDsmethotrexate28.926.8azathioprine21.819.5sulfasalazine16.214.9leflunomide14.313.0cyclosporine13.711.5hydroxychloroquine10.59.6mycophenolate4.52.9antimalarials4.43.9penicillamine3.53.4cyclophosphamide1.50.7chlorambucil1.20.4minocycline1.10.9gold0.50.2chloroquine0.10.0tsDMARDsanti-TNFs52.149.2infliximab41.838.3adalimumab40.336.8etanercept31.828.9rituximab3.42.9REFERENCES:NIL.Acknowledgements:NIL.Disclosure of InterestsNone Declared.

ASSOCIATION RULE MINING FOR PREDICTION OF COVID-19

COVID-19 is a raging pandemic that has created havoc with its impact ranging from loss of millions of human lives to social and economic disruptions of the entire world. Therefore, error-free prediction, quick diagnosis, disease identification, isolation and treatment of a COVID patient have become extremely important. Nowadays, mining knowledge and providing scientific decision making for diagnosis of diseases from clinical datasets has found wide-ranging applications in healthcare sector. In this direction, among different data mining tools, association rule mining has already emerged out as a popular technique to extract invaluable information and develop important knowledge-base to help in intelligent diagnosis of distinct diseases quickly and automatically. In this paper, based on 5434 records of COVID cases collected from a popular data science community and using Rapid Miner Studio software, an attempt is put forward to develop a predictive model based on frequent pattern growth algorithm of association rule mining to determine the likelihood of COVID-19 in a patient. It identifies breathing problem, fever, dry cough, sore throat, abroad travel and attended large gathering as the main indicators of COVID-19. Employing the same clinical dataset, a linear regression model is also proposed having a moderately high coefficient of determination of 0.739 in accurately predicting the occurrence of COVID-19. A decision support system can also be developed using the association rules to ease out and automate early detection of other diseases. © 2023 by the authors.

Sociopsychological Factors Related to Information Seeking during the COVID-19 Pandemic

Objectives: To limit the risk of contracting the coronavirus, it is crucial for individuals to attain accurate COVID-19 related information. Once they are equipped with such information, they can engage in risk preventive behaviors. This study aimed to examine the sociopsychological factors predisposing individuals' information-seeking intentions. Method(s): Based on the risk information seeking and processing (RISP) model, we hypothesized that individuals perceiving the risk of COVID-19 were likely to seek risk-related information through increased affective response (i.e., anxiety and fear) and information insufficiency. We considered perceived information gathering capacity as a moderator in the prediction of information-seeking intention. Using an online survey platform, study participants were recruited from US adults. Multivariate linear regressions were conducted in a hierarchical fashion while controlling for numerous covariates. Result(s): A total of 510 responses were included in our analyses. Respondents' mean age was 46.6+/-17.8 years;about half (53.3%) were females. Results showed that respondents' perceived risk provoked affective responses (regression coefficient (b) = 0.8417, 95% CI [0.7408, 0.9426]), which then increased self-perceived information insufficiency (b = 0.1857, 95% CI [0.0859, 0.2855]). This finding indicated that after perceiving the risk of coronavirus, individuals experienced worry and fear associated with the risk. Such affective responses made them realize that their current COVID-19 related knowledge was insufficient. Also, respondents who acknowledged information insufficiency were motivated to seek information about the coronavirus (b = 0.1099, 95% CI [0.0198, 0.1999]). The relation between information insufficiency and information-seeking intentions was moderated by perceived information gathering capacity (b = 0.0070, 95% CI [0.0001, 0.0151]), indicating that individuals with a higher capacity of gathering information were more likely to intend information seeking. Conclusion(s): Study findings suggest the importance of interventions to promote information seeking for individuals with a low information gathering capacity. Policy makers and clinicians assist the public in obtaining accurate information from reliable sources.Copyright © 2023

Patient Survey in Medical Practices on their Visit during the SARS-CoV-2 Pandemic.

Background: Since the beginning of the SARS-CoV2 pandemic medical practices have implemented diverse protective measures to contain the pandemic, practice organization and structures were adapted. In order to get information about patients' perception of their doctors' visit during the pandemic, we conducted a patient survey in medical practices. Method(s): Cross-sectional study of 58 patients, who were interviewed in four medical practices (family physicians and specialists) in the South West of Munich from 02.04.-17.04.2020 on the following topics: "personal risk assessment", "sense of security and perception of protection measures in the practice setting", "importance of the doctor's visit" and "change of medication, nicotine consumption". By means of a questionnaire with 24 items, data were collected anonymously. Results are presented descriptively and via ANOVA as well as via linear regression. Result(s): The personal risk assessments for COVID-19-disease and for a severe course of COVID-19 were rated low moderate, independent of sex or age. Around 8% of the surveyed patients discussed their personal risk with their doctors. The sense of security in the practice setting was rated high. The rating of the protection equipment was good as well, and closely met expectations. The personal importance of the visit varied. Only 6% had considered cancelling their visit beforehand. A change of medication due to SARS-CoV-2 pandemic was not observed. Conclusion(s): The patient survey provides a snapshot of the outpatient setting from the patient's perspective in a hyperdynamic pandemic situation. Yet, due to the small study population, the results have to be interpreted with caution.Copyright © 2021, Deutscher Arzteverlag.