scholarly journals Workload and influencing factors in non-emergency medical transfers: a multiple linear regression analysis of a cross-sectional questionnaire study

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Johann Georg Keunecke ◽  
Christine Gall ◽  
Torsten Birkholz ◽  
Andreas Moritz ◽  
Christian Eiche ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Influencing Factors ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Task Demands ◽  
Measurement Tool ◽  
Online Questionnaire ◽  
Cross Sectional ◽  
Emergency Medical

Abstract Background Human workload is a key factor for system performance, but data on emergency medical services (EMS) are scarce. We investigated paramedics’ workload and the influencing factors for non-emergency medical transfers. These missions make up a major part of EMS activities in Germany and are growing steadily in number. Methods Paramedics rated missions retrospectively through an online questionnaire. We used the NASA-Task Load Index (TLX) to quantify workload and asked about a variety of medical and procedural aspects for each mission. Teamwork was assessed by the Weller teamwork measurement tool (TMT). With a multiple linear regression model, we identified a set of factors leading to relevant increases or decreases in workload. Results A total of 194 non-emergency missions were analysed. Global workload was rated low (Mean = 27/100). In summary, 42.8% of missions were rated with a TLX under 20/100. TLX subscales revealed low task demands but a very positive self-perception of performance (Mean = 15/100). Teamwork gained high ratings (Mean TMT = 5.8/7), and good teamwork led to decreases in workload. Aggression events originating from patients and bystanders occurred frequently (n = 25, 12.9%) and increased workload significantly. Other factors affecting workload were the patient’s body weight and the transfer of patients with transmittable pathogens. Conclusion The workload during non-emergency medical transfers was low to very low, but performance perception was very positive, and no indicators of task underload were found. We identified several factors that led to workload increases. Future measures should attempt to better train paramedics for aggression incidents, to explore the usefulness of further technical aids in the transfer of obese patients and to reconsider standard operating procedures for missions with transmittable pathogens.

scholarly journals Association between the Type of Workplace and Lung Function in Copper Miners

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Anna Skoczyńska ◽  
Leszek Gruszczyński ◽  
Anna Wojakowska ◽  
Marek Ścieszka ◽  
Barbara Turczyn ◽  
...  
Keyword(s):  
Lung Function ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Longitudinal Data Analysis ◽  
Multiple Linear Regression Model ◽  
Multiple Linear Regression Analysis ◽  
Analysis Software ◽  
Cross Sectional ◽  
Sectional Analysis

The aim of the analysis was to retrospectively assess changes in lung function in copper miners depending on the type of workplace. In the groups of 225 operators, 188 welders, and 475 representatives of other jobs, spirometry was performed at the start of employment and subsequently after 10, 20, and 25 years of work. Spirometry Longitudinal Data Analysis software was used to estimate changes in group means for FEV1and FVC. Multiple linear regression analysis was used to assess an association between workplace and lung function. Lung function assessed on the basis of calculation of longitudinal FEV1 (FVC) decline was similar in all studied groups. However, multiple linear regression model used in cross-sectional analysis revealed an association between workplace and lung function. In the group of welders, FEF75 was lower in comparison to operators and other miners as early as after 10 years of work. Simultaneously, in smoking welders, the FEV1/FVC ratio was lower than in nonsmokers (p< 0,05). The interactions between type of workplace and smoking (p< 0,05) in their effect on FVC, FEV1, PEF, and FEF50 were shown. Among underground working copper miners, the group of smoking welders is especially threatened by impairment of lung ventilatory function.

Beneficial impact of education on cognition in amyloid-positive individuals with subjective cognitive decline: The SILCODE study

2020 ◽  
Author(s):  
Guanqun Chen ◽  
Chunhua Liu ◽  
Kun Yang ◽  
Jiehui Jiang ◽  
Ying Han
Keyword(s):  
Executive Function ◽  
Linear Regression ◽  
Cognitive Decline ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Multiple Linear Regression Analysis ◽  
Subjective Cognitive Decline ◽  
Cross Sectional ◽  
Function Language

Abstract Background: Previous studies suggest that education is associated with a decreased risk of dementia in individuals with subjective cognitive decline (SCD). However, the influence of education on cognition in amyloid-positive SCD subjects is not clear.Methods: We performed a cross-sectional study that involved 43 amyloid-negative and 29 amyloid-positive SCD subjects from the Sino Longitudinal Study on Cognitive Decline (SILCODE) project. Cognitive assessment included episodic memory, executive function, language, and general cognitive function. Multiple linear regression model was used to assess the association of education on cognitive performance.Results: Multiple linear regression analysis suggested that education has a protective effect on executive function, language for the amyloid-negative SCD group and language, global cognition for the amyloid-positive SCD group.Conclusions: The present study indicated that education has the potential to delay disease progression in amyloid-positive SCD subjects.

Predictive Factors for Hamstring Autograft Diameter in Anterior Cruciate Ligament Reconstruction

2019 ◽  
Author(s):  
Willem M.P. Heijboer ◽  
Mathijs A.M. Suijkerbuijk ◽  
Belle L. van Meer ◽  
Eric W.P. Bakker ◽  
Duncan E. Meuffels
Keyword(s):  
Anterior Cruciate Ligament ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Acl Reconstruction ◽  
Cruciate Ligament ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Gracilis Tendon ◽  
Thigh Circumference ◽  
Anterior Cruciate

AbstractMultiple studies found hamstring tendon (HT) autograft diameter to be a risk factor for anterior cruciate ligament (ACL) reconstruction failure. This study aimed to determine which preoperative measurements are associated with HT autograft diameter in ACL reconstruction by directly comparing patient characteristics and cross-sectional area (CSA) measurement of the semitendinosus and gracilis tendon on magnetic resonance imaging (MRI). Fifty-three patients with a primary ACL reconstruction with a four-stranded HT autograft were included in this study. Preoperatively we recorded length, weight, thigh circumference, gender, age, preinjury Tegner activity score, and CSA of the semitendinosus and gracilis tendon on MRI. Total CSA on MRI, weight, height, gender, and thigh circumference were all significantly correlated with HT autograft diameter (p < 0.05). A multiple linear regression model with CSA measurement of the HTs on MRI, weight, and height showed the most explained variance of HT autograft diameter (adjusted R 2 = 44%). A regression equation was derived for an estimation of the expected intraoperative HT autograft diameter: 1.2508 + 0.0400 × total CSA (mm2) + 0.0100 × weight (kg) + 0.0296 × length (cm). The Bland and Altman analysis indicated a 95% limit of agreement of ± 1.14 mm and an error correlation of r = 0.47. Smaller CSA of the semitendinosus and gracilis tendon on MRI, shorter stature, lower weight, smaller thigh circumference, and female gender are associated with a smaller four-stranded HT autograft diameter in ACL reconstruction. Multiple linear regression analysis indicated that the combination of MRI CSA measurement, weight, and height is the strongest predictor.

Musculoskeletal symptoms, psychosocial factors and work ability in Brazilian labor justice workers

Work ◽  
2021 ◽  
pp. 1-10
Author(s):  
Fauzi El Kadri Filho ◽  
Tha&ıs Moreira São-João ◽  
Neusa Maria Costa Alexandre ◽  
Sergio Roberto de Lucca ◽  
Cristiane Helena Gallasch ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Psychosocial Factors ◽  
Work Ability ◽  
Multiple Linear Regression Model ◽  
Female Gender ◽  
Musculoskeletal Symptoms ◽  
Judicial Process ◽  
Cross Sectional ◽  
Important Relationship

BACKGROUND: The implementation of the electronic judicial process (PJe) in recent years is associated with an increase in workload and stricter control through productivity targets in the Brazilian labor judiciary. OBJECTIVES: To evaluate the relations between musculoskeletal symptoms, psychosocial factors and work ability in civil servants of a labor justice body in the context of the PJe. METHODS: A cross-sectional exploratory study with a quantitative approach involving 449 workers. Sociodemographic, occupational and related data were collected through questionnaires validated in the Brazilian context. Data analysis was conducted by descriptive and inferential statistics: Mann-Whitney test, Spearman’s correlation coefficient and multiple linear regression. RESULTS: There was a correlation between musculoskeletal symptoms and psychosocial factors (p <  0.05), as well as between both musculoskeletal symptoms and psychosocial factors with reduced work ability (p <  0.05). The multiple linear regression model pointed to the female gender and the dimensions “demands”, “control” and “peer support” as related to the musculoskeletal symptoms. CONCLUSION: We highlight the importance of a broader approach, involving psychosocial factors in preventive actions related to musculoskeletal disorders considering the important relationship with work ability.

scholarly journals Prevalence of asymptomatic hyperuricemia and its association with prediabetes, dyslipidemia and subclinical inflammation markers among young healthy adults in Qatar

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Yasemin Al Shanableh ◽  
Yehia Y. Hussein ◽  
Abdul Haseeb Saidwali ◽  
Maryam Al-Mohannadi ◽  
Budoor Aljalham ◽  
...  
Keyword(s):  
Young Adults ◽  
Uric Acid ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Correlation Coefficient ◽  
Uric Acid Level ◽  
Acid Level ◽  
Linear Regression Analysis ◽  
Subclinical Inflammation ◽  
Cross Sectional

Abstract Aim The aim of this study is to investigate the prevalence of asymptomatic hyperuricemia in Qatar and to examine its association with changes in markers of dyslipidemia, prediabetes and subclinical inflammation. Methods A cross-sectional study of young adult participants aged 18 - 40 years old devoid of comorbidities collected between 2012 and 2017. Exposure was defined as uric acid level, and outcomes were defined as levels of different blood markers. De-identified data were collected from Qatar Biobank. T-tests, correlation tests and multiple linear regression were all used to investigate the effects of hyperuricemia on blood markers. Statistical analyses were conducted using STATA 16. Results The prevalence of asymptomatic hyperuricemia is 21.2% among young adults in Qatar. Differences between hyperuricemic and normouricemic groups were observed using multiple linear regression analysis and found to be statistically and clinically significant after adjusting for age, gender, BMI, smoking and exercise. Significant associations were found between uric acid level and HDL-c p = 0.019 (correlation coefficient -0.07 (95% CI [-0.14, -0.01]); c-peptide p = 0.018 (correlation coefficient 0.38 (95% CI [0.06, 0.69]) and monocyte to HDL ratio (MHR) p = 0.026 (correlation coefficient 0.47 (95% CI [0.06, 0.89]). Conclusions Asymptomatic hyperuricemia is prevalent among young adults and associated with markers of prediabetes, dyslipidemia, and subclinical inflammation.

scholarly journals Effects of Total Quality Management (TQM) Dimensions on Innovation—Evidence from SMEs

2021 ◽  
Vol 13 (18) ◽  
pp. 10095
Author(s):  
Marina Godinho Antunes ◽  
Pedro Ribeiro Mucharreira ◽  
Maria Rosário Texeira Justino ◽  
Joaquín Texeira-Quirós
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Continuous Improvement ◽  
Product Innovation ◽  
Research Study ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Process Innovation ◽  
Total Quality ◽  
Innovation Strategies

This research study aims to study and identify which dimensions of TQM have influence on and support innovation strategies within the Portuguese small and medium enterprises (SMEs), in the context of products or services’ innovation and process innovation, as well as to analyze the extent to which this relationship occurs. To examine the linkage between TQM dimensions and innovation strategies, concerning innovation products and innovation processes, a multiple linear regression analysis was chosen and an eight-predictor multiple linear regression model was proposed. The data was collected through a questionnaire sent by email. This research study allows to conclude that several dimensions of TQM, such as benchmarking, quality/conception and product design, and continuous improvement, have a significant and positive association with product innovation. Although the data analysis/measurement of the results dimension has a significant association with product innovation, this association is negative. Conversely, several TQM dimensions, such as leadership/management’s commitment, benchmarking, involvement/empowerment of employees, and continuous improvement, revealed a positive and significant association with process innovation. Our research is of crucial importance for the knowledge of Portuguese SMEs and the fundamental factors that companies must address to both improve their efficiency and be more competitive, thereby increasing profitability and ensuring financial sustainability in the medium and long term.

scholarly journals ANALISIS PENGARUH LIKUIDITAS, STRUKTUR AKTIVA, FREE CASH FLOW, DAN UKURAN PERUSAHAAN TERHADAP KEBIJAKAN UTANG (DER) PADA PT JASA MARGA Tbk PERIODE 2009-2018

KEUNIS ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 92
Author(s):  
Anita Kristina ◽  
Prihatiningsih Prihatiningsih ◽  
Ida Savitri Kusmargiani
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Cash Flow ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Multiple Linear Regression Analysis ◽  
Free Cash Flow ◽  
Company Size ◽  
Analysis Model ◽  
Debt Policy

<em>This research is based on the problems of the company PT Jasa Marga Tbk which has a problem with the performance of the company which is indicated by the DER of companie increased during the period 2009-2018. The purpose of this research is to analyze the influance of direction and significance of Liquidity, Asset Structure, Free Cash Flow and Company Size on Debt Policy (DER) in PT Jasa Marga Tbk for the period 2009-2018. The population and sample in this study were PT Jasa Marga Tbk. The analysis model used in this study is a multiple linear regression model. The results of the multiple linear regression analysis showed that (1) the influance of Liquidity (CR) on Debt Policy (DER) was positive and significant (2) the influance Asset Structure on Debt Policy (DER) was negative and not significant (3) the influance of Free Cash Flow on Debt Policy (DER) is positive and significant (4) the influance of Company Size on Debt Policy (DER) is positive and significant.</em>

scholarly journals Development of a Multiple Linear Regression Model for Meteorological Drought Index Estimation Based on Landsat Satellite Imagery

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3393
Author(s):  
Seon Woo Kim ◽  
Donghwi Jung ◽  
Yun-Jae Choung
Keyword(s):  
Remote Sensing ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Drought Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Index Estimation ◽  
Cumulative Precipitation

Climate polarization due to global warming has increased the intensity of drought in some regions, and the need for drought estimation studies to help minimize damage is increasing. In this study, we constructed remote sensing and climate data for Boryeong, Chungcheongnam-do, Korea, and developed a model for drought index estimation by classifying data characteristics and applying multiple linear regression analysis. The drought indices estimated in this study include four types of standardized precipitation indices (SPI1, SPI3, SPI6, and SPI9) used as meteorological drought indices and calculated through cumulative precipitation. We then applied statistical analysis to the developed model and assessed its ability as a drought index estimation tool using remote sensing data. Our results showed that its adj.R2 value, achieved using cumulative precipitation for one month, was very low (approximately 0.003), while for the SPI3, SPI6, and SPI9 models, the adj.R2 values were significantly higher than the other models at 0.67, 0.64, and 0.56, respectively, when the same data were used.

A Mathematical Comparison of the Lachance - Traill Matrix Correction Procedure with Statistical Multiple Linear Regression Analysis in XRF Applications

1992 ◽  
Vol 36 ◽  
pp. 1-10
Author(s):  
Anthony J. Klimasara
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Mathematical Meaning ◽  
Matrix Correction ◽  
Independent Variables ◽  
Xrf Analysis

AbstractIt will be shown that the Lachance-Traill XRF matrix correction equations can be derived from the statistical multiple linear regression model. By selecting and properly transforming the independent variables and then applying the statistical multiple linear regression model, the following form of the matrix correction equation is obtained:Furthermore, it will be shown that the Lachance-Traill influence coefficients have a deeper mathematical meaning. They can be related to the multiple regression coefficients of the transformed system:Finally, it will be proposed that the Lachance-Traill model is equivalent to the statistical multiple linear regression model with the transformed independent variables. Knowing these facts will simplify correction subroutines in Quantitative/Empirical XRF Analysis programs. These mathematical facts have already been implemented and presented in a paper: “Automated Quantitative XRF Analysis Software in Quality Control Applications” (Pacific-International Congress on X-ray Analytical Methods, Hawaii, 1991).This demonstrates that the Lachance-Traill model has a strong mathematical foundation and is naturally justified mathematically.

scholarly journals Post-traumatic growth and influencing factors among frontline nurses fighting against COVID-19

2020 ◽  
pp. oemed-2020-106540
Author(s):  
Pan pan Cui ◽  
Pan pan Wang ◽  
Kun Wang ◽  
Zhiguang Ping ◽  
Peng Wang ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Influencing Factors ◽  
Psychological Intervention ◽  
Linear Regression Analysis ◽  
Bivariate Analysis ◽  
Related Factors ◽  
Self Confidence ◽  
Post Traumatic Growth ◽  
Post Traumatic

ObjectiveTo explore the level and influencing factors of frontline nurses’ post-traumatic growth (PTG) during COVID-19 epidemic.MethodsA cross-sectional survey was conducted in February 2020 in three hospitals in China. The Post-traumatic Growth Inventory (PTGI) was used to investigate the PTG of frontline nurses. Data on related factors, including demographic characteristics and subjective variables, were collected. The Event-Related Rumination Inventory was used to assess rumination. Pearson’s or Spearman’s correlation was calculated for bivariate analysis. Independent sample t-tests or one-way analysis of variance and multiple linear regression analysis were used to examine the related factors.ResultsA total of 179 frontline nurses were recruited, and 167 were included in the analyses. The mean PTG score was 70.53±17.26. The bivariate analyses showed that deliberate rumination was modestly positively correlated with PTG (r=0.557, p<0.01), while intrusive rumination had a modest negative correlation with PTG (r=−0.413, p<0.01). Multiple linear regression demonstrated that working years, self-confidence in frontline work, awareness of risk, psychological intervention or training during the epidemic and deliberate rumination were the main influencing factors of PTG among frontline nurses and accounted for 42.5% of the variance (F=31.626, p<0.001).ConclusionsThe PTG of frontline nurses was at a medium to high level and was influenced by working years, self-confidence in frontline work, awareness of risk, psychological intervention or training and deliberate rumination. It is necessary to strengthen psychological guidance and training for frontline nurses and promote their deliberate rumination on epidemic events to improve their PTG.

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