Factors In Different Dimensions Research Articles

Perceived social support and professional quality of life of health professionals during COVID-19 pandemic in Nepal: a cross-sectional study

ObjectiveTo assess the perceived social support and professional quality of life (ProQOL) among healthcare professionals during COVID-19 pandemic in Nepal, encompassing both positive (compassion satisfaction) and negative (compassion fatigue) dimensions...

Analysis of the Driving Mechanism of Land Comprehensive Carrying Capacity from the Perspective of Urban Renewal

After a period of rapid development, the process of urbanization in China has gradually shifted from “scale expansion” to “enhanced quality”. The scarcity of urban land resources has created constraints on resources and economic development. This paper examines the carrying capacity of urban land resources from the perspective of urban renewal. A conceptual model of the driving mechanism of land comprehensive carrying capacity is constructed, incorporating six dimensions and 22 indicators, including urban renewal and urban ecology. Through questionnaire surveys and structural equation modeling, feedback data are analyzed, and measurement models, structural models, and mediation effects are examined to analyze the causal paths of factors in different dimensions on the comprehensive carrying capacity of urban land. The research results indicate that all six dimensions in the conceptual model have a direct positive impact on the land carrying capacity. In terms of direct effects, the influencing factors are ranked in descending order of magnitude as follows: urban development, urban disaster prevention and mitigation capacity, infrastructure development, urban renewal, social economy, and urban ecology. In terms of overall effects, factors are ranked in descending order of magnitude as follows: urban development, social economy, urban ecology, urban renewal, urban disaster prevention and mitigation capacity, and infrastructure development.

Progress in research of determinants of healthy life expectancy

Objective: To analyze the influencing factors of healthy life expectancy (HLE). Methods: Seven Chinese and English databases were used for the retrieval of related literatures published by May 7, 2022 to identify influencing factors of HLE, including diseases and injuries and their risk factors. Based on the ecological model of health determinants, this study classifies the risk factors of diseases and injuries into five levels: personal characteristics, individual behavior and lifestyle, social network, living and working conditions, and macroscopic socio-economic, cultural and environmental conditions. Contents of research area, HLE indicators, research population, influencing factors, data sources and results were extracted. The frequencies of reported documents of different HLE indicators and influencing factors of different dimensions were visualized by using evidence map, and the empirical studies of four authoritative English medical journals and Chinese core medical journals were further compared and described. Results: A total of 90 studies were selected, in which 26 were conducted in China (28.9%). Fifty-three studies are about diseases and injuries in the first dimension, and all of them have studied non-communicable diseases, accounting for the highest proportion (58.9%). There were 77 studies about the analysis on the determinants of health at five levels by an ecological model, all the studies reported multi-level results. Among them, 53 studies reported personal characteristics (58.9%), 47 studies reported individual behavior and lifestyle (52.2%), 10 studies reported social networks (11.1%), 35 studies reported living and working environment (38.9%), 8 studies reported social economy, culture status and environment condition (8.9%). The literatures about HLE published by 4 authoritative English medical journals and 21 Chinese core medical journals in recent three years were selected. Non-communicable diseases and personal characteristics were the top two most commonly studied factors of HLE, and 11 (52.3%) and 12 (57.1%) studies reported these two kinds of factors respectively. The most important factor contributing to the global disability-adjusted life years of non-communicable diseases was individual behavior and lifestyle, which was the most changeable factor. Conclusions: In recent three years, studies involving influencing factors of HLE were mainly non-communicable diseases and personal characteristics. In the future, individual behavior, lifestyle and working environment should be strengthened.

Modifiable Risk Factors Are Important Predictors of COVID-19-Related Mortality in Patients on Hemodialysis.

Patients with end-stage kidney disease face a higher risk of severe outcomes from SARS-CoV-2 infection. Moreover, it is not well known to what extent potentially modifiable risk factors contribute to mortality risk. In this historical cohort study, we investigated the incidence and risk factors for 30-day mortality among hemodialysis patients with SARS-CoV-2 infection treated in the European Fresenius Medical Care NephroCare network using conventional and machine learning techniques. We included adult hemodialysis patients with the first documented SARS-CoV-2 infection between February 1, 2020, and March 31, 2021, registered in the clinical database. The index date for the analysis was the first SARS-CoV-2 suspicion date. Patients were followed for up to 30 days until April 30, 2021. Demographics, comorbidities, and various modifiable risk factors, expressed as continuous parameters and as key performance indicators (KPIs), were considered to tap multiple dimensions including hemodynamic control, nutritional state, and mineral metabolism in the 6 months before the index date. We used logistic regression (LR) and XGBoost models to assess risk factors for 30-day mortality. We included 9,211 patients (age 65.4 ± 13.7 years, dialysis vintage 4.2 ± 3.7 years) eligible for the study. The 30-day mortality rate was 20.8%. In LR models, several potentially modifiable factors were associated with higher mortality: body mass index (BMI) 30-40 kg/m2 (OR: 1.28, CI: 1.10-1.50), single-pool Kt/V (OR off-target vs on-target: 1.19, CI: 1.02-1.38), overhydration (OR: 1.15, CI: 1.01-1.32), and both low (<2.5 mg/dl) and high (≥5.5 mg/dl) serum phosphate levels (OR: 1.52, CI: 1.07-2.16 and OR: 1.17, CI: 1.01-1.35). On-line hemodiafiltration was protective in the model using KPIs (OR: 0.86, CI: 0.76-0.97). SHapley Additive exPlanations analysis in XGBoost models shows a high influence on prediction for several modifiable factors as well, including inflammatory parameters, high BMI, and fluid overload. In both LR and XGBoost models, age, gender, and comorbidities were strongly associated with mortality. Both conventional and machine learning techniques showed that KPIs and modifiable risk factors in different dimensions ascertained 6 months before the COVID-19 suspicion date were associated with 30-day COVID-19-related mortality. Our results suggest that adequate dialysis and achieving KPI targets remain of major importance during the COVID-19 pandemic as well.

Users’ needs and expectations of immersive learning spaces in an academic library: A survey

This research aims to investigate users’ space requirements, facilities, equipment, environmental needs, management services, and food services in immersive learning space. Descriptive statistical analysis is used to study the degree of users’ demand on spatial factors of different dimensions. The influence of identity and gender on the spatial needs is measured through t-test and one-way analysis of variance. The study found that in terms of space requirements, users are inclined to choose private and quiet seats; in terms of facilities and equipment, the higher the user’s academic status, the correspondingly higher requirements for some space facilities and equipment. Users attach great importance to the environmental elements of the immersive learning space, especially the cleanliness, lighting, acoustic environment, and temperature. Users also hope to use the online reservation services and increase the open time of the library. Although the main purpose of the immersive learning space is to learn, users hope to get food services. According to the research results, suggestions for the improvement of library spaces are put forward: adding special areas for doctoral candidate and faculty community, enhancing space planning, building better online services, building a 24-hour open learning space, and seting up a dining area outside the library.

Hierarchical Clustering with Spatial Constraints and Standardized Incidence Ratio in Tuberculosis Data

In this paper, we propose presenting a solution based on socio-epidemiological variables of tuberculosis, considering a clustering with spatial/geographical constraints; and, determine a value of alpha that increases spatial contiguity without significantly deteriorating the quality of the solution based on the variables of interest, i.e. those of the feature space. For the application of Ward’s hierarchical clustering method, two dissimilarity matrices were calculated, the first provides the dissimilarities in the feature space calculated from the socio-epidemiological variables D0 and the second provides the dissimilarities in the calculated constraints space from the geographical distances D1, together with an α mixing parameter and the non-uniform weight w assigned to the calculation of the dissimilarity matrix defined by the standardized incidence ratio (SIR) of TB and that contributed significantly to the increase in clarity, both from a spatial and socio-epidemiological point of view. The method is shown to be feasible in epidemiological studies in the joint understanding of factors of different dimensions, aggregated from a spatial perspective. It is analysis tool that allows making a better understanding of the socio-epidemiological reality of the municipality.

Associated factors of different fatigue dimensions in elderly patients with rheumatoid arthritis

Objective: To investigate the associated factors of different dimensions of fatigue in elderly patients with rheumatoid arthritis (RA). Methods: A cross-sectional analysis was performed in the elderly outpatients with RA (age ≥ 60 years) in the First Affiliated Hospital of Sun Yat-sen University from January 2018 to June 2019. Fatigue was measured by Multidimensional Fatigue Inventory-20 (MFI-20) and 36-item Short Form Health Survey-Vitality (SF-36-VT). Physical fatigue and mental fatigue were subsequently measured by MFI-20 subscales. Results: A total of 104 patients were included. Male-to-female ratio was 1∶3.3. The average age was (68±6) years. The MFI-20 score and SF-36-VT score were 60±14 and 64±20, respectively. The score of physical fatigue measured by MFI-20 was 14±3, and mental fatigue scored 10±4 (P<0.001). Arthralgia, disease activity, disability, insomnia, depression and anxiety were correlated with fatigue assessed by MFI-20 (correlated coefficient: 0.48-0.62). Multivariable regression analysis showed that arthralgia and depression were associated with physical fatigue (Standardized regression coefficients were 0.44 and 0.38, respectively). Insomnia, depression and anxiety were associated factors of mental fatigue (Standardized regression coefficients were 0.20, 0.32 and 0.24, respectively). Conclusions: Elderly patients with RA experiencehigh level of fatigue, mainly presenting as physical fatigue. Arthralgia and depression mainly affect physical fatigue, and arthralgia is a critical factor. Insomnia, depression and anxiety are associated with mental fatigue.

Assessing the biophysical and social drivers of burned area distribution at the local scale

Understanding the characteristics of wildfire-affected communities and the importance of particular factors of different dimensions, is paramount to improve prevention and mitigation strategies, tailored to people's needs and abilities. In this study, we explored different combinations of biophysical and social factors to characterize wildfire-affected areas in Portugal. By means of machine-learning methods based on classification trees, we assessed the predictive ability of various models to discriminate different levels of wildfire incidence at the local scale. The model with the best performance included a reduced set of both biophysical and social variables and we found that, oveall, the exclusion of specific variables improved prediction rates of group classification. The most important variables were related to landcover; the civil parishes covered by more than 20% of shrublands were more fire-prone, whereas those parishes with at least 40% of agricultural land were less affected by wildfires. Regarding social variables, the most-affected parishes showed a lower proportion of foreign residents and lower purchasing power, conditions likely associated with the socioeconomic context of inland low-density rural areas, where rural abandonment, depopulation and ageing trends have been observed in the last decades. Further research is needed to investigate how other particular parameters representing the social context, and its evolution, can be integrated in wildfire occurrence modelling, and how these interact with the biophysical conditions over time.

Multidimensional influencing factors of public opinion information dissemination in social media: Evidence from Weibo dataset

The factors influencing the dissemination of public opinion on social media, the main carrier of public opinion, are diverse, complex and changeable. Existing studies of influential factors of public opinion dissemination focus on the information itself and information sources in the dissemination process, failing to consider the comprehensive influence of multidimensional factors, such as information content, sources and channels. This study takes the identification of multidimensional influential factors of social media information dissemination as the research object and comprehensively sorts out the influencing factors of public opinion. To improve the scientific basis and accuracy of the research, multidimensional factors, including information characteristics, dissemination network structure and user-level attributes, are selected to analyze the effect of influential factors in different dimensions on the dissemination of social media public opinion information using econometric models. Three main conclusions of this paper are as follows: (1) The traditional information characteristics (information content) and information source attributes (user-level factor) are not the only key factors affecting information dissemination, while the information channel (network structure) is worth more consideration. (2) Netizens tend to pay more attention to the psychological and emotional attributes of information when forwarding public opinions. The communication mode in which offline social elites enlighten the public no longer exists; whether a user is a network celebrity or lives in the central area no longer significantly affects public opinion dissemination. (3) The higher the total amount of information users release, the more the information would interfere with the public opinion. This is mainly because users with a higher level of activity may release more invalid information about advertising that has nothing to do with public opinion events.

Evaluating and Ranking Cloud-Based E-Learning Critical Success Factors (CSFs) Using Combinatorial Approach

Cloud computing has been regarded as one of the significant Information Technology (IT) tools. Many sectors are adopting cloud computing services for its business support. It has also become a new IT paradigm that has transformed the E-Learning system to become more user-friendly. As a result, the E-Learning usage is growing rapidly and being preferred over the conventional teaching-learning process in a big way. This revolutionary change is attributed to the advancement in digital technology. The transformation in digital technology has made the teaching-learning process flexible, easy and convenient for effective knowledge transfer. The cloud-based E-Learning process depends upon many factors of different dimensions that are of significant importance for cloud-based-E-Learning success. Hence they must be studied to successfully analyze their level of importance and fulfill Cloud-based E-Learning positive effectiveness. The current research provides a detailed literature review for cloud-based E-Learning Critical Success Factors (CSFs) of teaching–learning process. Further, the research employs the combinatorial approach to evaluate the diversified dimensions and CSFs of cloud-based E-Learning that helps in quantifying and comparing the influence of various dimensions and CSFs of cloud-based-E-Learning. Four dimensions and fourteen factors have been identified through in-depth literature review and later on evaluated for the prioritization using a combinatorial approach. The influence of such dimensions and factors will help various stakeholders to plan their strategy and resources for the betterment of knowledge transfer through cloud-based-E-Learning.

Integrated decision-making model for community-based rehabilitation service utilisation among persons with severe mental illness in China: protocol for a cross-sectional, mixed-methods study

IntroductionA common problem low-income and middle-income countries face is the scarcity of community-based rehabilitation (CBR) resources and low service utilisation among persons with severe mental illness (SMI). Despite this problem,...

Is college education an equalizer for social disparities in health literacy? A case study in Shanghai, China.

The aim of the study was to illustrate the immediate effect of the college education process (across college grades) on the strength of association between parental education and college attendees' health literacy. Cross-sectional analysis was conducted based on data from a random sample of students in one university in Shanghai, China (N = 574). Exploratory factor analysis was used to generate factors of different dimensions of health literacy. Ordinary least square regression models were estimated to investigate how college education process alters the family-based disparity in health literacy. The link between parental education and health-related skills did not vary significantly across grades of participants, but participants in their third (p < 0.05) and fourth year (p < 0.001) revealed a significantly weaker association between health-promoting proactivity and parental education, relative to the first-year counterparts. Also, the impact of parental education on health-related attitudes significantly declined among the fourth-year seniors, compared with first-year students (p < 0.05). Higher education experience is an important mechanism to alleviate the socioeconomic gap in health literacy. Such an equalizer effect, nevertheless, is contingent on the particular dimensions of health literacy.

A Survey on PARATREE and SUSVD Decomposition Techniques and Their Use in Array Signal Processing

The present manuscript is intended to review few applications of tensor decomposition model in array signal processing. Tensor decomposition models like HOSVD, SVD and PARAFAC are useful in signal processing. In this paper we shall use higher order tensor decomposition in signal processing. Also, a novel orthogonal non-iterative tensor decomposition technique (SUSVD), which is scalable to arbitrary high dimensional tensor, has been applied in MIMO channel estimation. The SUSVD provides a tensor model with hierarchical tree structure between the factors in different dimensions. We shall use a new model known as PARATREE, which is related to PARAFAC tensor models. The PARAFAC and PARATREE both describe a tensor as a sum of rank-1 tensors, but PARATREE has several advantages over PARAFAC, when it is applied as a lower rank approximation technique. PARATREE is orthogonal, fast and reliable to compute, and the order of the decomposition can be adaptively adjusted. The low rank PARATREE approximation has been applied to measure noise suppression for tensor valued MIMO channel sounding measurements.

Exploring Individual Trust Factors in Computer Mediated Group Collaboration: A Case Study Approach

Trust has become more and more important in the context of mixed use of longitudinal face-to-face and computer mediated group collaboration using Group Support System tools. Previous research has investigated trust factors in different dimensions. This paper takes the perspective of individual trust and aims to explore the new trust factors and also their detailed second level trust sub-factors in computer mediated collaboration over time. We have taken the interviews using the student groups during the two year-long collaboration project based case studies. We have validated the previous factors and found seven new trust factors and thirty one sub-factors which are associated with the main factors. Furthermore, based on the new factors, this paper has also designed an innovative trust traffic light model with suggested steps which could be easily used to help analyze the trust factors development over time for future longitudinal studies.

Quality of life of childbearing age women and its associated factors: an application of seemingly unrelated regression (SUR) models

This article is a report of using seemingly unrelated regression (SUR) models to examine the determinants of different dimensions of quality of life (QoL) among childbearing age women. There are a limited number of studies on QoL and its associated factors among women in developing countries such as Iran. Therefore, more attention should be focused on identifying these issues. We administered the Persian's abbreviated version of the World Health Organization Quality of Life (WHOQOL-BREF) questionnaire to 1,067 married women aged between 15 and 49 years. The women were chosen via a multistage research design from the rural region of Shiraz, the center of Fars Province in Iran in 2008. Clinical and socio-demographic characteristics as well as their reproductive health-related characteristics were investigated. To identify associated factors of QoL dimensions, ordinary least squares (OLS) regression and SUR were used and their findings were compared. The WHOQOL-BREF showed acceptable consistency (Cronbach's alpha range: 0.62-0.75 across domains). Lower age, absence of long-term illness, economic status satisfaction, higher level of education, lower number of pregnancies, and higher body mass index were important associated factors of different dimensions of the QoL among these women. The estimated parameters for these factors were in close agreement in both OLS and SUR estimation methods. However, the SUR estimator provided the higher precision of the estimates than the OLS estimator, as the parameters obtained by SUR are characterized by lower standard errors. Women's age, income satisfaction, and level of education were common for all domains. This study presents a novel approach to simultaneously predict QoL domains using the SUR estimators and the results are relevant for implementing objective QoL. SUR estimators performed consistently better than the OLS estimators, since SUR takes the correlation between error terms into account. Thus, the SUR method could be a useful methodology for predicting QoL domains.