The relationship between plasma MHPG and NE: employing regression models in estimating centrally derived MHPG and peripheral NE turnover rate in panic disorder

Malaysia has recorded the second highest involuntary turnover rate at 6% and third highest voluntary rate at 6.5% in South East Asia. Employee loyalty becomes critical towards employer. Thus, the purpose of this study was to examine the relationship between career development, compensation, job security, work environment and employee loyalty. In conducting this study, convenience sampling technique has been employed and respondents have been chosen in the area of Kuala Lumpur. Hypothesis were tested using regression analysis by using Smart-PLS. Based on the result, career development, compensation and job security were found to be significant with employee loyalty. However, work environment was found to be not significant with employee loyalty. It is suggested for future research to explore other variables in order to find the factors contributed in employee loyalty. Keywords: Career Development, Compensation, Job Security, Work Environment, Employee Loyalty

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785 Reported Restful Sleep Predicting Emotional Distress: Does Exercise (and its modalities) moderate?

SLEEP ◽

10.1093/sleep/zsab072.782 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A305-A306

Author(s):

Jesse Moore ◽

Ellita Williams ◽

Collin Popp ◽

Anthony Briggs ◽

Judite Blanc ◽

...

Keyword(s):

Logistic Regression ◽

Aerobic Exercise ◽

Regression Models ◽

Regression Analyses ◽

Logistic Regression Models ◽

The Past ◽

Strengthening Exercise ◽

Waking Up ◽

The Relationship ◽

Age And Sex

Abstract Introduction Literature shows that exercise moderates the relationship between sleep and emotional distress (ED.) However, it is unclear whether different types of exercise, such as aerobic and strengthening, affect this relationship differently. We investigated the moderating role of two types of exercise (aerobic and strengthening) regarding the relationship between ED and sleep. Methods Our analysis was based on data from 2018 National Health Interview Survey (NHIS), a nationally representative study in which 2,814 participants provided all data. Participants were asked 1) “how many days they woke up feeling rested over the past week”, 2) the Kessler 6 scale to determine ED (a score >13 indicates ED), and 3) the average frequency of strengthening or aerobic exercise per week. Logistic regression analyses were performed to determine if the reported days of waking up rested predicted level of ED. We then investigated whether strengthening or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Logistic regression analyses were performed to determine if subjective reporting of restful sleep predicted level of ED. We investigated whether strengthening exercise or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Results On average, participants reported 4.41 restful nights of sleep (SD =2.41), 3.43 strengthening activities (SD = 3.19,) and 8.47 aerobic activities a week (SD=5.91.) We found a significant association between days over the past week reporting waking up feeling rested and ED outcome according to K6, Χ2(1) = -741, p= <.001. The odds ratio signified a decrease of 52% in ED scores for each unit of restful sleep (OR = .48, (95% CI = .33, .65) p=<.001.) In the logistic regression model with moderation, aerobic exercise had a significant moderation effect, Χ2(1) = .03, p=.04, but strengthening exercise did not. Conclusion We found that restful sleep predicted reduction in ED scores. Aerobic exercise moderated this relationship, while strengthening exercise did not. Further research should investigate the longitudinal effects of exercise type on the relationship between restful sleep and ED. Support (if any) NIH (K07AG052685, R01MD007716, K01HL135452, R01HL152453)

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Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽

10.3390/w13010037 ◽

2020 ◽

Vol 13 (1) ◽

pp. 37

Author(s):

Tomás de Figueiredo ◽

Ana Caroline Royer ◽

Felícia Fonseca ◽

Fabiana Costa de Araújo Schütz ◽

Zulimar Hernández

Keyword(s):

Soil Moisture ◽

Soil Water ◽

Regression Models ◽

Meteorological Data ◽

Water Storage ◽

Model Performance ◽

Soil Water Balance ◽

Soil Water Storage ◽

The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

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The Impact of Weather and Seasons on Falls and Physical Activity among Older Adults with Glaucoma: A Longitudinal Prospective Cohort Study

Sensors ◽

10.3390/s21103415 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3415

Author(s):

Hursuong Vongsachang ◽

Aleksandra Mihailovic ◽

Jian-Yu E ◽

David S. Friedman ◽

Sheila K. West ◽

...

Keyword(s):

Physical Activity ◽

Older Adults ◽

Fall Prevention ◽

Regression Models ◽

Activity Promotion ◽

Injurious Fall ◽

Multivariable Regression ◽

Multivariable Regression Models ◽

The Impact ◽

The Relationship

Understanding periods of the year associated with higher risk for falling and less physical activity may guide fall prevention and activity promotion for older adults. We examined the relationship between weather and seasons on falls and physical activity in a three-year cohort of older adults with glaucoma. Participants recorded falls information via monthly calendars and participated in four one-week accelerometer trials (baseline and per study year). Across 240 participants, there were 406 falls recorded over 7569 person-months, of which 163 were injurious (40%). In separate multivariable regression models incorporating generalized estimating equations, temperature, precipitation, and seasons were not significantly associated with the odds of falling, average daily steps, or average daily active minutes. However, every 10 °C increase in average daily temperature was associated with 24% higher odds of a fall being injurious, as opposed to non-injurious (p = 0.04). The odds of an injurious fall occurring outdoors, as opposed to indoors, were greater with higher average temperatures (OR per 10 °C = 1.46, p = 0.03) and with the summer season (OR = 2.69 vs. winter, p = 0.03). Falls and physical activity should be understood as year-round issues for older adults, although the likelihood of injury and the location of fall-related injuries may change with warmer season and temperatures.

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Online News and Protest Participation in a Political Context: Evidence from Self-Reported Cross-Sectional Data

Social Media + Society ◽

10.1177/2056305120984456 ◽

2021 ◽

Vol 7 (1) ◽

pp. 205630512098445

Author(s):

Nora Kirkizh ◽

Olessia Koltsova

Keyword(s):

Digital Media ◽

Regression Models ◽

Online News ◽

Political Context ◽

Government Control ◽

Multilevel Regression ◽

Traditional Media ◽

Cross Sectional ◽

Internet Media ◽

The Relationship

Availability of alternative information through social media, in particular, and digital media, in general, is often said to induce social discontent, especially in states where traditional media are under government control. But does this relation really exist, and is it generalizable? This article explores the relationship between self-reported online news consumption and protest participation across 48 nations in 2010–2014. Based on multilevel regression models and simulations, the analysis provides evidence that those respondents who reported that they had attended a protest at least once read news online daily or weekly. The study also shows that the magnitude of the effect varies depending on the political context: surprisingly, despite supposedly unlimited control of offline and online media, autocratic countries demonstrated higher effects of online news than transitional regimes, where the Internet media are relatively uninhibited.

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Investigating the Relationship Between Emotion Recognition Software and Usability Metrics

i-com ◽

10.1515/icom-2020-0009 ◽

2020 ◽

Vol 19 (2) ◽

pp. 139-151

Author(s):

Thomas Schmidt ◽

Miriam Schlindwein ◽

Katharina Lichtner ◽

Christian Wolff

Keyword(s):

Emotion Recognition ◽

Regression Models ◽

Affective Computing ◽

Large Scale ◽

General Purpose ◽

Thinking Aloud ◽

Continue Research ◽

Usability Metrics ◽

Recognition Software ◽

The Relationship

AbstractDue to progress in affective computing, various forms of general purpose sentiment/emotion recognition software have become available. However, the application of such tools in usability engineering (UE) for measuring the emotional state of participants is rarely employed. We investigate if the application of sentiment/emotion recognition software is beneficial for gathering objective and intuitive data that can predict usability similar to traditional usability metrics. We present the results of a UE project examining this question for the three modalities text, speech and face. We perform a large scale usability test (N = 125) with a counterbalanced within-subject design with two websites of varying usability. We have identified a weak but significant correlation between text-based sentiment analysis on the text acquired via thinking aloud and SUS scores as well as a weak positive correlation between the proportion of neutrality in users’ voice and SUS scores. However, for the majority of the output of emotion recognition software, we could not find any significant results. Emotion metrics could not be used to successfully differentiate between two websites of varying usability. Regression models, either unimodal or multimodal could not predict usability metrics. We discuss reasons for these results and how to continue research with more sophisticated methods.

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An analysis of Italian university students’ performance through segmented regression models: gender differences in STEM courses

Genus ◽

10.1186/s41118-021-00118-6 ◽

2021 ◽

Vol 77 (1) ◽

Author(s):

Andrea Priulla ◽

Nicoletta D’Angelo ◽

Massimo Attanasio

Keyword(s):

Gender Differences ◽

Regression Models ◽

First Year ◽

Strongly Correlated ◽

Segmented Regression ◽

Freshmen Students ◽

Female Performance ◽

And Mathematics ◽

The Relationship ◽

Better Than

AbstractThis paper investigates gender differences in university performances in Science, Technology, Engineering and Mathematics (STEM) courses in Italy, proposing a novel application through the segmented regression models. The analysis concerns freshmen students enrolled at a 3-year STEM degree in Italian universities in the last decade, with a focus on the relationship between the number of university credits earned during the first year (a good predictor of the regularity of the career) and the probability of getting the bachelor degree within 4 years. Data is provided by the Italian Ministry of University and Research (MIUR). Our analysis confirms that first-year performance is strongly correlated to obtaining a degree within 4 years. Furthermore, our findings show that gender differences vary among STEM courses, in accordance with the care-oriented and technical-oriented dichotomy. Males outperform females in mathematics, physics, chemistry and computer science, while females are slightly better than males in biology. In engineering, female performance seems to follow the male stream. Finally, accounting for other important covariates regarding students, we point out the importance of high school background and students’ demographic characteristics.

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694 Insufficient sleep linked with higher COVID-19 infection cases and deaths in the United States

SLEEP ◽

10.1093/sleep/zsab072.692 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A271-A271

Author(s):

Azizi Seixas ◽

Nicholas Pantaleo ◽

Samrachana Adhikari ◽

Michael Grandner ◽

Giardin Jean-Louis

Keyword(s):

Regression Models ◽

Negative Binomial ◽

The United States ◽

Poor Sleep ◽

County Level ◽

Infection Rates ◽

Insufficient Sleep ◽

Death Rates ◽

Rural Counties ◽

The Relationship

Abstract Introduction Causes of COVID-19 burden in urban, suburban, and rural counties are unclear, as early studies provide mixed results implicating high prevalence of pre-existing health risks and chronic diseases. However, poor sleep health that has been linked to infection-based pandemics may provide additional insight for place-based burden. To address this gap, we investigated the relationship between habitual insufficient sleep (sleep <7 hrs./24 hr. period) and COVID-19 cases and deaths across urban, suburban, and rural counties in the US. Methods County-level variables were obtained from the 2014–2018 American community survey five-year estimates and the Center for Disease Control and Prevention. These included percent with insufficient sleep, percent uninsured, percent obese, and social vulnerability index. County level COVID-19 infection and death data through September 12, 2020 were obtained from USA Facts. Cumulative COVID-19 infections and deaths for urban (n=68), suburban (n=740), and rural (n=2331) counties were modeled using separate negative binomial mixed effects regression models with logarithmic link and random state-level intercepts. Zero-inflated models were considered for deaths among suburban and rural counties to account for excess zeros. Results Multivariate regression models indicated positive associations between cumulative COVID-19 infection rates and insufficient sleep in urban, suburban and rural counties. The incidence rate ratio (IRR) for urban counties was 1.03 (95% CI: 1.01 – 1.05), 1.04 (95% CI: 1.02 – 1.05) for suburban, and 1.02 (95% CI: 1.00 – 1.03) rural counties.. Similar positive associations were observed with county-level COVID-19 death rates, IRR = 1.11 (95% CI: 1.07 – 1.16) for urban counties, IRR = 1.04 (95% CI: 1.01 – 1.06) for suburban counties, and IRR = 1.03 (95% CI: 1.01 – 1.05) for rural counties. Level of urbanicity moderated the association between insufficient sleep and COVID deaths, but not for the association between insufficient sleep and COVID infection rates. Conclusion Insufficient sleep was associated with COVID-19 infection cases and mortality rates in urban, suburban and rural counties. Level of urbanicity only moderated the relationship between insufficient sleep and COVID death rates. Future studies should investigate individual-level analysis to understand the role of sleep mitigating COVID-19 infection and death rates. Support (if any) NIH (K07AG052685, R01MD007716, R01HL142066, K01HL135452, R01HL152453

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EEG-correlates of work efficiency level among young persons with stress-induced bruxism

Medical alphabet ◽

10.33667/2078-5631-2021-36-25-29 ◽

2021 ◽

pp. 25-29

Author(s):

A. E. Barulin ◽

S. V. Klauchek ◽

A. E. Klauchek

Keyword(s):

Regression Models ◽

Alpha Rhythm ◽

Negative Relationship ◽

Maximum Amplitude ◽

Dominant Frequency ◽

Regression Equations ◽

Microsoft Excel ◽

The Subject ◽

Males And Females ◽

The Relationship

Purpose of the study. To establish the relationship between neurophysiological status and the level of efficiency in young people with bruxism.Materials and methods. Two groups of 64 and 53 subjects (males and females) aged 20–35 years old with bruxism and non-bruxers were formed according to questionnaire results and physical examination. The level of efficiency was assessed by the results of sensorimotor tracking of a moving object (the ‘Smile’ model). Spectral analysis was performed for evaluation of the baseline electroencephalograms. Microsoft Excel and Statistica 10.0 programs were used for statistical data processing.Results. The level of efficiency was statistically significantly lower in the hardest test of Smile model among the individuals with bruxism (p < 0.05). The bruxers also demonstrated a significantly lower dominant frequency and maximum amplitude of alpha-rhythm (p < 0.05), and significantly higher dominant frequency of beta2 rhythm (p < 0.05). The dominant frequency and the maximum amplitude of the alpha-rhythm are parameters corresponding to significant coefficients of the regression analysis. A negative relationship was found between the degree of error during sensorimotor tracking and the frequency and amplitude of alpha-rhythm.Conclusion. Regression models present the relationship between the level of efficiency and the alpha-rhythm severity. The regression equations make it possible to determine the functional state of the subject using an electroencephalogram.

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Relationship Between Mental Health, Resilience, and Physical Activity in Older Adults: A 2-Year Longitudinal Study

Journal of Aging and Physical Activity ◽

10.1123/japa.2020-0264 ◽

2021 ◽

pp. 1-9

Author(s):

Maria Priscila Wermelinger Ávila ◽

Jimilly Caputo Corrêa ◽

Alessandra Lamas Granero Lucchetti ◽

Giancarlo Lucchetti

Keyword(s):

Mental Health ◽

Physical Activity ◽

Older Adults ◽

Regression Models ◽

Linear Regression Models ◽

Physically Active ◽

Effective Interventions ◽

Self Sufficiency ◽

The Relationship

The aim of this study was to longitudinally investigate the association between resilience and mental health in older adults and to determine the influence of physical activity on this relationship. A total of 291 older adults were included in a 2-year follow-up study. Adjusted linear regression models evaluated the association between resilience at baseline and mental health after 2 years in sufficiently and insufficiently physically active older adults. A negative correlation was found between resilience at baseline and depression, anxiety, and stress after 2 years for the overall sample. This association changed after stratifying the group. Sufficiently physically active individuals made greater use of the resilience components “Self-Sufficiency” and “Perseverance,” whereas insufficiently physically active individuals made greater use of “Meaning of Life” and “Existential Singularity.” Physical activity can influence the relationship between resilience and mental health. These results can help guide the devising of more effective interventions for this age group.

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