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1.
Clin Exp Med ; 2022 Jun 13.
Article in English | MEDLINE | ID: covidwho-1888899

ABSTRACT

To investigate the relationship between human immunodeficiency virus (HIV) infection and the risk of mortality among coronavirus disease 2019 (COVID-19) patients based on adjusted effect estimate by a quantitative meta-analysis. A random-effects model was used to estimate the pooled effect size (ES) with corresponding 95% confidence interval (CI). I2 statistic, sensitivity analysis, Begg's test, meta-regression and subgroup analyses were also conducted. This meta-analysis presented that HIV infection was associated with a significantly higher risk of COVID-19 mortality based on 40 studies reporting risk factors-adjusted effects with 131,907,981 cases (pooled ES 1.43, 95% CI 1.25-1.63). Subgroup analyses by male proportion and setting yielded consistent results on the significant association between HIV infection and the increased risk of COVID-19 mortality. Allowing for the existence of heterogeneity, further meta-regression and subgroup analyses were conducted to seek the possible source of heterogeneity. None of factors might be possible reasons for heterogeneity in the further analyses. Sensitivity analysis indicated the robustness of this meta-analysis. The Begg's test manifested that there was no publication bias (P = 0.2734). Our findings demonstrated that HIV infection was independently associated with a significantly increased risk of mortality in COVID-19 patients. Further well-designed studies based on prospective study estimates are warranted to confirm our findings.

3.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-337041

ABSTRACT

Recent studies have investigated post-acute sequelae of SARS-CoV-2 infection (PASC) using real-world patient data such as electronic health records (EHR). Prior studies have typically been conducted on patient cohorts with small sample sizes 1 or specific patient populations 2,3 limiting generalizability. This study aims to characterize PASC using the EHR data warehouses from two large national patient-centered clinical research networks (PCORnet), INSIGHT and OneFlorida+, which include 11 million patients in New York City (NYC) and 16.8 million patients in Florida respectively. With a high-throughput causal inference pipeline using high-dimensional inverse propensity score adjustment, we identified a broad list of diagnoses and medications with significantly higher incidence 30-180 days after the laboratory-confirmed SARS-CoV-2 infection compared to non-infected patients. We found more PASC diagnoses and a higher risk of PASC in NYC than in Florida, which highlights the heterogeneity of PASC in different populations.

4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-337039

ABSTRACT

The post-acute sequelae of SARS-CoV-2 infection (PASC) refers to a broad spectrum of symptoms and signs that are persistent, exacerbated, or newly incident in the post-acute SARS-CoV-2 infection period of COVID-19 patients. Most studies have examined these conditions individually without providing concluding evidence on co-occurring conditions. To answer this question, this study leveraged electronic health records (EHRs) from two large clinical research networks from the national Patient-Centered Clinical Research Network (PCORnet) and investigated patients' newly incident diagnoses that appeared within 30 to 180 days after a documented SARS-CoV-2 infection. Through machine learning, we identified four reproducible subphenotypes of PASC dominated by blood and circulatory system, respiratory, musculoskeletal and nervous system, and digestive system problems, respectively. We also demonstrated that these subphenotypes were associated with distinct patterns of patient demographics, underlying conditions present prior to SARS-CoV-2 infection, acute infection phase severity, and use of new medications in the post-acute period. Our study provides novel insights into the heterogeneity of PASC and can inform stratified decision-making in the treatment of COVID-19 patients with PASC conditions.

5.
Sustainability ; 14(9):5619, 2022.
Article in English | ProQuest Central | ID: covidwho-1843243

ABSTRACT

Blended synchronous learning (BSL) is becoming increasingly widely implemented in many higher education institutions due to its accessibility and flexibility. However, little research has been conducted to explore students’ engagement and persistence and their possible predictors in such a learning mode. The purpose of this study was to investigate how to facilitate students’ engagement and persistence in BSL. In detail, this study used structural equation modeling to explore the relationships among specific predictors (self-regulation, teaching presence, and social presence), learning engagement, and learning persistence in BSL. We recruited 319 students who were enrolled in BSL at a Chinese university. The online survey was administered to gather data on the variables of this study. The results demonstrated that self-regulation, teaching presence, and social presence were positively associated with learning engagement. Self-regulation and learning engagement were positively associated with learning persistence. Moreover, learning engagement mediated the relationships between self-regulation, teaching presence, social presence, and learning persistence. This study suggests that self-regulation, teaching presence, and social presence are significant predictors for student learning engagement and persistence in BSL.

6.
IEEE Transactions on Automation Science & Engineering ; 19(2):620-631, 2022.
Article in English | Academic Search Complete | ID: covidwho-1788782

ABSTRACT

In the coronavirus epidemic, many Chinese hospitals have established buffer zones to prevent the spread and transmission of the virus. The buffer zone is a monitored and separate area where the patients who need hospitalizations after the quick treatments in the emergency department can temporarily wait for the Covid-19 test and receive some healthcare services to stabilize their conditions. Because the beds in the buffer zones are limited, the managers face the patient admission control problem for the buffer zone. This management and control problem is challenging since the patient arrivals are uncertain, and the patients’ conditions are different. In this paper, we build the infinite- and finite-horizon Markov decision process (MDP) models for this problem. We use the uniformization method to discretize the patient flow. We propose various iteration algorithms to solve the MDP models and obtain the optimal and threshold policies. Numerical experiments validate the advantages of the policies obtained by the algorithms in this paper over the current policies of hospitals. Note to Practitioners—The ongoing COVID-19 pandemic has been causing enormous damage to people’s health, jobs, and well-being. COVID-19 has affected almost all countries globally and has changed the operation mode of the healthcare system, especially the hospitals. The hospitals are the frontlines of healthcare service and the battle with the COVID-19 pandemic. This article is motivated by our collaborations with hospitals in Shanghai, China. In China, many hospitals establish buffer zones: a monitored area where the patients who need hospitalizations after the quick treatments in the emergency department can temporarily wait for the Covid-19 test and receive some healthcare services to stabilize their conditions. Because the zone’s capacity is limited, the managers must make dynamic patient admission control decisions according to multiple factors, such as patients’ health conditions and the usage of beds in the zone. We propose two MDP models to solve this complex problem. Several iteration algorithms are designed to solve the MDP models and obtain the optimal and threshold policies. Based on hospitals’ real-life data, we show the methods presented in this paper can help hospital managers make more reasonable decisions. Although we focus on the hospital’s buffer zone in China, the methodology and approach for this problem can be extended to other practical hospital management scenarios in the coronavirus pandemic. For example, For example, some hospitals have admission control problems for coronavirus patients due to hospital capacity limitations. The hospital has to decide if a patient is accepted as an inpatient or suggested to home quarantine. In such a case, the admission control problem can also be solved by the methodologies in the paper. [ FROM AUTHOR] Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

7.
Neurol Sci ; 43(7): 4049-4059, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1756822

ABSTRACT

OBJECTIVE: To investigate the association between stroke and the risk for mortality among coronavirus disease 2019 (COVID-19) patients. METHODS: We performed systematic searches through electronic databases including PubMed, Embase, Scopus, and Web of Science to identify potential articles reporting adjusted effect estimates on the association of stroke with COVID-19-related mortality. To estimate pooled effects, the random-effects model was applied. Subgroup analyses and meta-regression were performed to explore the possible sources of heterogeneity. The stability of the results was assessed by sensitivity analysis. Publication bias was evaluated by Begg's test and Egger's test. RESULTS: This meta-analysis included 47 studies involving 7,267,055 patients. The stroke was associated with higher COVID-19 mortality (pooled effect = 1.30, 95% confidence interval (CI): 1.16-1.44; I2 = 89%, P < 0.01; random-effects model). Subgroup analyses yielded consistent results among area, age, proportion of males, setting, cases, effect type, and proportion of severe COVID-19 cases. Statistical heterogeneity might result from the different effect type according to the meta-regression (P = 0.0105). Sensitivity analysis suggested that our results were stable and robust. Both Begg's test and Egger's test indicated that potential publication bias did not exist. CONCLUSION: Stroke was independently associated with a significantly increased risk for mortality in COVID-19 patients.


Subject(s)
COVID-19 , Stroke , Humans , Male , Stroke/complications
9.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325397

ABSTRACT

Background: Severe cytokine storm syndrome (CSS) is considered as the cause of death among critically ill COVID-19 cases. Early identification of the high-risk severe cases is crucial to lower the fatality and healthcare costs. Methods: : In this study, we retrospectively analyzed the first and second-week serum levels of IL-6, IL-8, and IL-10 of 50 COVID-19 cases. We calculated the ratios of IL-6/IL-10 and IL-8/IL-10 at 3 rd , 6 th , 9 th , and 12 th days of hospitalization. Results: : We collected 50 COVID-19 cases (male 54%, mean age 51.2, range 18 - 86), including 39 mild cases (78%), 7 severe/recovered cases (14%), and 4 died cases (8%).The ratios of IL 6/IL-10 and IL-8/IL-10 among mild cases were below 27 (the highest, 26.9) along the 4 testing points of two week hospitalization, while we found that the IL-6/IL-10 and IL-8/IL-10 ratios were as high as 187.51 and 225.3 respectively in the death group on 3 rd day with the highest IL-6/IL-10 ratio of 297.28 on the 6 th day of hospitalization. Conclusions: : Our preliminary results suggest that the ratios of IL-6/IL-10 and IL-8/IL-10 at the early stage (the first two weeks) of COVID-19 could be a predictive marker for the disease prognosis, of which the cut-off lines were suggested below 50 for a mild and recoverable severe cases.

10.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-324307

ABSTRACT

Background: Cardiovascular disease (CVD), one of the most common comorbidities of coronavirus disease 2019 (COVID-19), has been suspected to be associated with adverse outcomes in COVID-19 patients, but their correlation remains controversial. Method This is a quantitative meta-analysis on the basis of adjusted effect estimates. PubMed, Web of Science, MedRxiv, Scopus, Elsevier ScienceDirect, Cochrane Library and EMBASE were searched comprehensively to obtain a complete data source up to January 7, 2021. Pooled effects (hazard ratio (HR), odds ratio (OR)) and the 95% confidence intervals (CIs) were estimated to evaluate the risk of the adverse outcomes in COVID-19 patients with CVD. Heterogeneity was assessed by Cochran’s Q-statistic, I²test, and meta-regression. In addition, we also provided the prediction interval, which was helpful for assessing whether the variation across studies was clinically significant. The robustness of the results was evaluated by sensitivity analysis. Publication bias was assessed by Begg’s test, Egger’s test, and trim-and-fill method. Result Our results revealed that COVID-19 patients with pre-existing CVD tended more to adverse outcomes on the basis of 203 eligible studies with 24,033,838 cases (pooled ORs = 1.41, 95% CIs: 1.32–1.51, prediction interval: 0.84–2.39;pooled HRs = 1.34, 95% CIs: 1.23–1.46, prediction interval: 0.82–2.21). Further subgroup analyses stratified by age, the proportion of male, study design, disease types, sample size, region and disease outcomes also showed that pre-existing CVD was significantly associated with adverse outcomes among COVID-19 patients. Conclusion Our findings demonstrated that pre-existing CVD was an independent risk factor associated with adverse outcomes among COVID-19 patients.

11.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324114

ABSTRACT

Background: The impact of corticosteroid therapy on outcomes of patients with Coronavirus disease-2019 (COVID-19) is highly controversial. We aimed to compare the risk of death between COVID-19-related ARDS patients with corticosteroid treatment and those without. Methods In this single-centre retrospective observational study, patients with ARDS caused by COVID-19 between 24 December 2019 and 24 February 2020 were enrolled. The primary outcome was 60-day in-hospital death. The exposure was prescribed systemic corticosteroids or not. Time-dependent Cox regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for 60-day in-hospital mortality. Results A total of 382 patients including 226 (59.2%) patients who received systemic corticosteroids and 156 (40.8%) patients with standard treatment were analyzed. The maximum dose of corticosteroids was 80.0 (IQR 40.0–80.0) mg equivalent methylprednisolone per day, and duration of corticosteroid treatment was 7.0 (4.0–12.0) days in total. In Cox regression analysis using corticosteroid treatment as a time-varying variable, corticosteroid treatment was associated with a significant reduction in risk of in-hospital death within 60 days (HR, 0.48;95% CI, 0.25, 0.93;p  = 0.0285). The association remained significantly after adjusting for age, sex, Sequential Organ Failure Assessment score at hospital admission, propensity score of corticosteroid treatment, and comorbidities (HR: 0.51;CI: 0.27, 0.99;p  = 0.0471). Corticosteroids were not associated with delayed viral RNA clearance in our cohort. Conclusion In this clinical practice setting, low-to-moderate dose corticosteroid treatment was associated with reduced risk of death in COVID-19 patients who developed ARDS.

12.
Front Psychol ; 12: 806756, 2021.
Article in English | MEDLINE | ID: covidwho-1662619

ABSTRACT

The COVID-19 pandemic severely hit small and micro-businesses. In the face of the impact of the pandemic, how to help entrepreneurs, especially small- and micro-businesses that are more sensitive to the impact of the pandemic, make decisions to reduce losses has become an issue worth paying attention to. From the perspective of personality approach, this article studied openness, which is the strongest predictor of entrepreneurial performance among the big five personality traits, and explored the impact of entrepreneurs' openness on entrepreneurial performance during the COVID-19 pandemic, as well as the inconsistent mediating role of strategic decision comprehensiveness on entrepreneurial performance. An online questionnaire survey was conducted among 238 entrepreneurs of small- and micro-businesses when China was recovering from the pandemic and starting to resume work and production (February 18 - February 26, 2020). Entrepreneurial performance during the COVID-19 pandemic was measured by comparing the business conditions before and after the pandemic. The results showed that entrepreneurs' openness positively impacted strategic decision comprehensiveness and entrepreneurial performance during the COVID-19 pandemic. Among the two competing hypotheses proposed by summarizing previous research, the results supported that strategic decision comprehensiveness negatively affected entrepreneurial performance. It indicated that entrepreneurs who tend to collect and analyze information extensively and then make decisions during the pandemic could not seize opportunities and improve their entrepreneurial performance. The results further supported that strategic decision comprehensiveness was an inconsistent mediator between openness and entrepreneurial performance, showing that entrepreneurs with low openness can also reduce the loss of entrepreneurial performance during the pandemic by making incomplete but rapid strategic decisions. This study found that the openness of entrepreneurs had a positive impact on strategic decision comprehensiveness for the first time and provided more empirical evidence for the negative effect of strategic decision comprehensiveness on entrepreneurial performance in the context of information uncertainty and unanalyzable situations. The inconsistent mediating effect of strategic decision comprehensiveness revealed in this study also has practical significance for helping entrepreneurs make correct decisions to reduce the losses caused by the pandemic.

14.
Int Immunopharmacol ; 102: 108390, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1525826

ABSTRACT

OBJECTIVE: The aim of this study was to investigate the impact of asthma on the risk for mortality among coronavirus disease 2019 (COVID-19) patients in the United States by a quantitative meta-analysis. METHODS: A random-effects model was used to estimate the pooled odds ratio (OR) with corresponding 95% confidence interval (CI). I2 statistic, sensitivity analysis, Begg's test, meta-regression and subgroup analyses were also performed. RESULTS: The data based on 56 studies with 426,261 COVID-19 patients showed that there was a statistically significant association between pre-existing asthma and the reduced risk for COVID-19 mortality in the United States (OR: 0.82, 95% CI: 0.74-0.91). Subgroup analyses by age, male proportion, sample size, study design and setting demonstrated that pre-existing asthma was associated with a significantly reduced risk for COVID-19 mortality among studies with age ≥ 60 years old (OR: 0.79, 95% CI: 0.72-0.87), male proportion ≥ 55% (OR: 0.79, 95% CI: 0.72-0.87), male proportion < 55% (OR: 0.81, 95% CI: 0.69-0.95), sample sizes ≥ 700 cases (OR: 0.80, 95% CI: 0.71-0.91), retrospective study/case series (OR: 0.82, 95% CI: 0.75-0.89), prospective study (OR: 0.83, 95% CI: 0.70-0.98) and hospitalized patients (OR: 0.82, 95% CI: 0.74-0.91). Meta-regression did reveal none of factors mentioned above were possible reasons of heterogeneity. Sensitivity analysis indicated the robustness of our findings. No publication bias was detected in Begg's test (P = 0.4538). CONCLUSION: Our findings demonstrated pre-existing asthma was significantly associated with a reduced risk for COVID-19 mortality in the United States.


Subject(s)
Asthma/epidemiology , COVID-19/mortality , Asthma/drug therapy , Asthma/immunology , COVID-19/immunology , COVID-19/virology , Humans , Prevalence , Prospective Studies , Protective Factors , Retrospective Studies , SARS-CoV-2/immunology , United States/epidemiology
15.
Non-conventional in English | [Unspecified Source], Grey literature | ID: grc-750455

ABSTRACT

BACKGROUND AND OBJECTIVES: Public health interventions were associated with reduction in coronavirus disease 2019 (COVID-19) transmission in China, but their impacts on COVID-19 epidemiology in other countries are unclear. We examined the associations of stay-at-home order (SAHO) and face-masking recommendation with epidemiology of laboratory-confirmed COVID-19 in the United States. METHODS: In this quasi-experimental study, we modeled the temporal trends in daily new cases and deaths of COVID-19, and COVID-19 time-varying reproduction numbers (Rt) in the United States between March 1 and April 20, 2020, and conducted simulation studies. RESULTS: The number and proportion of U.S. residents under SAHO increased between March 19 and April 7, and plateaued at 29,0829,980 and 88.6%, respectively. Trends in COVID-19 daily cases and Rt reduced after March 23 (P<0.001) and further reduced on April 3 (P<0.001), which was associated with implementation of SAHO by 10 states on March 23, and face-masking recommendation on April 3, respectively. The estimates of Rt eventually fell below/around 1.0 on April 13. Similar turning points were identified in the trends of daily deaths with a lag time. Early implementation and early-removal of SAHO would be associated with significantly reduced and increased daily new cases and deaths, respectively.

16.
Arch Pathol Lab Med ; 145(11): 1350-1354, 2021 11 01.
Article in English | MEDLINE | ID: covidwho-1485407

ABSTRACT

CONTEXT.­: The main focus of education in most pathology residency and subspecialty pathology fellowships is the light microscopic examination of pathology specimens. Classes with multiheaded scopes are the most popular among pathology trainees. Until recently, it was difficult to imagine that this educational approach could change. In the beginning of March 2020, our country faced a serious challenge, which all of us now know as the coronavirus disease 2019 (COVID-19) pandemic. The rules of social distancing and work from home were applied. These types of restrictions were implemented in almost all parts of our life, including work and pathology education. OBJECTIVE.­: To share our experience in the Department of Hematopathology at the University of Texas MD Anderson Cancer Center during the COVID-19 pandemic. We describe our experience in modifying our approaches to education. We show how we overcame many obstacles to learning by building one of the largest virtual hematopathology educational platforms via Cisco WebEx and using social media, in particular Twitter. These tools facilitated the learning of hematopathology by medical students, pathology trainees, and practicing pathologists from all over the world. DATA SOURCES.­: During the first 3 months of the pandemic (April, May, and June, 2020), we evaluated the visitor attendance to the MD Anderson Cancer Center Hematopathology Virtual Educational Platform using data collected by the Cisco WebEx Web site. To determine the impact that the platform had on medical education for the hematopathology community on Twitter, the analytic metrics obtained from Symplur LLC (www.symplur.com, April 27, 2020) were used via its Symplur Signals program. CONCLUSIONS.­: Our experience using the MD Anderson Hematopathology Virtual Platform showed that there is substantial global interest and desire for virtual hematopathology education, especially during the COVID-19 pandemic.


Subject(s)
COVID-19/prevention & control , Education, Distance/methods , Education, Medical/methods , Hematology/education , Pathology/education , Social Media , Education, Distance/organization & administration , Education, Distance/trends , Education, Medical/organization & administration , Education, Medical/trends , Humans , Texas
17.
BMC Public Health ; 21(1): 1533, 2021 08 11.
Article in English | MEDLINE | ID: covidwho-1477304

ABSTRACT

BACKGROUND: Cardiovascular disease (CVD), one of the most common comorbidities of coronavirus disease 2019 (COVID-19), has been suspected to be associated with adverse outcomes in COVID-19 patients, but their correlation remains controversial. METHOD: This is a quantitative meta-analysis on the basis of adjusted effect estimates. PubMed, Web of Science, MedRxiv, Scopus, Elsevier ScienceDirect, Cochrane Library and EMBASE were searched comprehensively to obtain a complete data source up to January 7, 2021. Pooled effects (hazard ratio (HR), odds ratio (OR)) and the 95% confidence intervals (CIs) were estimated to evaluate the risk of the adverse outcomes in COVID-19 patients with CVD. Heterogeneity was assessed by Cochran's Q-statistic, I2test, and meta-regression. In addition, we also provided the prediction interval, which was helpful for assessing whether the variation across studies was clinically significant. The robustness of the results was evaluated by sensitivity analysis. Publication bias was assessed by Begg's test, Egger's test, and trim-and-fill method. RESULT: Our results revealed that COVID-19 patients with pre-existing CVD tended more to adverse outcomes on the basis of 203 eligible studies with 24,032,712 cases (pooled ORs = 1.41, 95% CIs: 1.32-1.51, prediction interval: 0.84-2.39; pooled HRs = 1.34, 95% CIs: 1.23-1.46, prediction interval: 0.82-2.21). Further subgroup analyses stratified by age, the proportion of males, study design, disease types, sample size, region and disease outcomes also showed that pre-existing CVD was significantly associated with adverse outcomes among COVID-19 patients. CONCLUSION: Our findings demonstrated that pre-existing CVD was an independent risk factor associated with adverse outcomes among COVID-19 patients.


Subject(s)
COVID-19 , Cardiovascular Diseases , Cardiovascular Diseases/epidemiology , Comorbidity , Humans , Male , Risk Factors , SARS-CoV-2
19.
Stem Cells Int ; 2021: 5902824, 2021.
Article in English | MEDLINE | ID: covidwho-1458469

ABSTRACT

With the rapid development of stem cell technology, the advent of three-dimensional (3D) cultured brain organoids has opened a new avenue for studying human neurodevelopment and neurological disorders. Brain organoids are stem-cell-derived 3D suspension cultures that self-assemble into an organized structure with cell types and cytoarchitectures recapitulating the developing brain. In recent years, brain organoids have been utilized in various aspects, ranging from basic biology studies, to disease modeling, and high-throughput screening of pharmaceutical compounds. In this review, we overview the establishment and development of brain organoid technology, its recent progress, and translational applications, as well as existing limitations and future directions.

20.
Journal of Intelligent & Fuzzy Systems ; : 1-18, 2021.
Article in English | Academic Search Complete | ID: covidwho-1453202

ABSTRACT

The video conferencing software is regarded as a significant tool for social distancing and getting incorporations up and going. Due to the indeterminacy of epidemic evolution and the multiple criteria, this paper proposes a video conferencing software selection method based on hybrid multi-criteria decision making (HMCDM) under risk and cumulative prospect theory (CPT), in which the criteria values are expressed in various mathematical forms (e.g., real numbers, interval numbers, and linguistic terms) and can be changed with natural states of the epidemic. Initially, the detailed description of video conferencing software selection problem under an epidemic are given. Subsequently, a whole procedure for video conferencing software selection is conducted, the approaches for processing and normalizing the multi-format evaluation values are presented. Furthermore, the expectations provided by DMs under different natural states of the epidemic are considered as the corresponding reference points (RP). Based on this, the matrix of gains and losses is constructed. Then, the prospect values of all criteria and the perceived probabilities of natural states are calculated according to the value function and the weighting function in CPT respectively. Finally, the proposed method is illustrated by an empirical case study, and the comparison analysis and the sensitivity analysis for the loss aversion parameter are conducted to prove the effectiveness and robustness. The results show that considering the psychological characteristics of DMs in selection decision is beneficial to avoid the unacceptable and potential loss risks. This study could provide a useful guideline for managers who intend to select appropriate video conferencing software. [ABSTRACT FROM AUTHOR] Copyright of Journal of Intelligent & Fuzzy Systems is the property of IOS Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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