An Assessment of Influencing Factors for Motherhood During Childhood in Bangladesh Using Factor Analysis and Logistic Regression Methods

2020 ◽  
pp. 237-251
Author(s):  
Mohammad Salim Zahangir ◽  
Mosammat Zamilun Nahar
Keyword(s):  
Factor Analysis ◽  
Logistic Regression ◽  
Influencing Factors ◽  
Regression Methods

PELAYANAN PUBLIK KESEHATAN PUSKESMAS DALAM MEMBERIKAN KEPUASAN MASYARAKAT DI KABUPATEN SUMENEP

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Aryo Wibisono ◽  
R. Amilia Destryana
Keyword(s):  
Public Health ◽  
Logistic Regression ◽  
Patient Satisfaction ◽  
Health Center ◽  
Public Service ◽  
Public Health Center ◽  
The Public ◽  
Regression Methods ◽  
Total Satisfaction ◽  
The Relationship

This study aims to determine the index of public satisfaction in public health center services in Sumenep Regency and the relationship between the services to the public satisfaction. The analysis measured the index of public satisfaction and logistic regression methods to determine the effect of the relationship on total satisfaction in the health services of Public Health Center. The results of the study are the alignment between interests and patient satisfaction is still not aligned, there are still differences between interests and satisfaction, the pattern of the result is the relationship between the assurance dimension to the service satisfaction of the public health center, and the results of the index of public satisfaction  values show that the results of the community assess the public health center performance is very good by getting an A grade. Keywords: public service, logistic regretion, index of public satisfaction

scholarly journals Knowledge, attitudes, practices, and influencing factors of anxiety among pregnant women in Wuhan during the outbreak of COVID-19: a cross-sectional study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenping Ding ◽  
Jianmei Lu ◽  
Yan Zhou ◽  
Weizhong Wei ◽  
Zhihong Zhou ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Pregnant Women ◽  
Influencing Factors ◽  
Information Source ◽  
Influential Factors ◽  
Public Health Issue ◽  
Cross Sectional ◽  
Factors Associated ◽  
Attitudes And Practices ◽  
Prenatal Anxiety

Abstract Background Prenatal anxiety has been a significant public health issue globally, leading to adverse health outcomes for mothers and children. The study aimed to evaluate the sociodemographic characteristics, knowledge, attitudes, and practices (KAP), and anxiety level of pregnant women during the coronavirus disease 2019 (COVID-19) epidemic in Wuhan and investigate the influencing factors for prenatal anxiety in this specific context. Methods Pregnant subjects’ KAP towards COVID-19 and their sociodemographics and pregnancy information were collected using questionnaires. The Zung Self-Rating Anxiety Scale (SAS) was used to assess anxiety status. Factors associated with the level of prenatal anxiety were analyzed by Pearson’s chi-square test and multivariable logistic regression analyses. Results The prenatal anxiety prevalence in this population was 20.8%. The mean score of knowledge was 13.2 ± 1.1 on a 0 ~ 14 scale. The attitudes and practices data showed that 580/ 817 (71.0%) were very concerned about the news of COVID-19, 455/817 (55.7%) considered the official media to be the most reliable information source for COVID-19, and 681/817 (83.4%) were anxious about the possibility of being infected by COVID-19. However, only 83/817 (10.2%) worried about contracting COVID-19 infection through the ultrasound transducer during a routing morphology scan. About two-thirds 528/817 (64.6%) delayed or canceled the antenatal visits. Approximately half of them 410/817 (50.2%) used two kinds of personal protection equipments (PPEs) during hospital visits. Logistic regression analysis revealed that the influential factors for prenatal anxiety included previous children in the family, knowledge score, media trust, worry of contracting the COVID-19 infection and worry about getting infected with COVID-19 from the ultrasound probe antenatal care (ANC) schedule. Conclusion Prenatal anxiety was prevalent among pregnant women in Wuhan during the outbreak of COVID-19. The current findings identified factors associated with the level of prenatal anxiety that could be targeted for psychological care.

Experimental study on the factors affecting squeak noise occurrence in automotive suspension bushings

2021 ◽  
pp. 095440702110241
Author(s):  
Byunghyun Kang ◽  
Cheol Choi ◽  
Daeun Sung ◽  
Seongho Yoon ◽  
Byoung-Ho Choi
Keyword(s):  
Neural Network ◽  
Logistic Regression ◽  
Influencing Factors ◽  
Frictional Force ◽  
Prediction Models ◽  
Statistical Tests ◽  
Network Models ◽  
Multiple Logistic Regression ◽  
Neural Network Models ◽  
Automotive Suspension

In this study, friction tests are performed, via a custom-built friction tester, on specimens of natural rubber used in automotive suspension bushings. By analyzing the problematic suspension bushings, the eleven candidate factors that influence squeak noise are selected: surface lubrication, hardness, vulcanization condition, surface texture, additive content, sample thickness, thermal aging, temperature, surface moisture, friction speed, and normal force. Through friction tests, the changes are investigated in frictional force and squeak noise occurrence according to various levels of the influencing factors. The degree of correlation between frictional force and squeak noise occurrence with the factors is determined through statistical tests, and the relationship between frictional force and squeak noise occurrence based on the test results is discussed. Squeak noise prediction models are constructed by considering the interactions among the influencing factors through both multiple logistic regression and neural network analysis. The accuracies of the two prediction models are evaluated by comparing predicted and measured results. The accuracies of the multiple logistic regression and neural network models in predicting the occurrence of squeak noise are 88.2% and 87.2%, respectively.

Analyzing the Sustainability of Water-Cultural Industry and Their Influencing Factors in China

2021 ◽  
Author(s):  
Shubing Qiu ◽  
Yong Liu ◽  
Yang Ye
Keyword(s):  
Sustainable Development ◽  
Factor Analysis ◽  
Influencing Factors ◽  
Indicator System ◽  
Cultural Industry ◽  
The Sustainable Development ◽  
Relational Analysis ◽  
Analysis Theory ◽  
Cultural Ideology ◽  
Grey Relational

This study is an empirical analysis of China’s “sustainable development ability of water cultural industry” based on the attributes of water cultural industry (economic attribute and cultural ideology). First, using “factor analysis” and “grey relational analysis theory,” establish an indicator-system for the level of sustainable development of the cultural industry, then quantify the relationships between the water cultural industry and its influencing factors, and finally, propose some solutions for enhancing the sustainable development of the water cultural industry from the perspective of “improving resiliency.”

scholarly journals Factors Influencing on E-Banking Practices: Evidence from Sri Lanka

2017 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Anusiga Gunaratnam ◽  
Konalingam Kajenthiran ◽  
Umanakenan Ratnam ◽  
Achchuthan Sivapalan
Keyword(s):  
Factor Analysis ◽  
Sri Lanka ◽  
Influencing Factors ◽  
Likert Scale ◽  
Total Variance ◽  
Critical Factors ◽  
Factors Influencing ◽  
Unique Model

The purpose of this paper is to explore the influencing factors of e-banking practices in Sri Lanka. A questionnaire with seven-point Likert scale is applied to 388 usable responses. The study was exploratory in nature and employed factor analysis to identify the important factors of e-banking practices. Results indicate that mainly four factors are significant with respect to the e-banking practices. Privacy & convenience, content & website layout, speed of delivery, and accessibility are the critical factors influencing the e-banking practices. In addition, factors extracted from the analysis accounted for 53.704% of the total variance. This study expected to provide a unique model in the realm of e-banking.

The Influencing Factors Analysis of Implementing Green Supply Chain Based on the Investigation Data in Shandong Province of China

2013 ◽  
Vol 671-674 ◽  
pp. 3049-3054
Author(s):  
Cao Qian ◽  
Xi Jian Quan ◽  
Yu Yan Wang
Keyword(s):  
Factor Analysis ◽  
Supply Chain ◽  
Energy Consumption ◽  
Product Design ◽  
Influencing Factors ◽  
Shandong Province ◽  
Raw Material ◽  
Green Supply Chain ◽  
Manufacturing Enterprises ◽  
Factors Analysis

On the basis of investigation and research, we firstly determined factors that impact manufacturing enterprises to implement green supply chain. Then, based on data of Parts of manufacturing enterprises in Shandong Province implementing green supply chain, the influencing factors of manufacturing enterprises implementing green supply chain is analyzed by factor analysis. The conclusion show that the influencing factors mainly concentrates in seven aspects that is raw material purchase, the enterprise internal management, the worn recycling, the product design, the enterprise prestige, the enterprise energy consumption, the reject processes.

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