scholarly journals Poor Sleep Quality’s Association With Soccer Injuries: Preliminary Data

2020 ◽  
Vol 15 (5) ◽  
pp. 671-676
Author(s):  
Andressa Silva ◽  
Fernanda V. Narciso ◽  
Igor Soalheiro ◽  
Fernanda Viegas ◽  
Luísa S.N. Freitas ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Sleep Quality ◽  
Injury Severity ◽  
Linear Regression Analysis ◽  
Sleep Efficiency ◽  
Total Variance ◽  
Soccer Players ◽  
Poor Sleep ◽  
Injury Characteristics

Purpose: To investigate the relationship between sleep quality and quantity and injuries in elite soccer players and to compare sleep–wake variables and injury characteristics. Methods: The current investigation was a prospective cohort study of 23 elite male soccer players competing for 2 teams over 6 mo in the highest-level Brazilian competition. The players’ sleep behavior was monitored for 10 d in the preseason using self-reporting sleep diaries and wrist activity monitors to determine sleep duration and quality. Furthermore, injuries were recorded by the respective club’s medical teams into a specific database. Details of injuries recorded included the type, location, and severity of each injury. The results were expressed as descriptive statistics, and the significance level was set at 5%. The Mann–Whitney U test was performed to compare the sleep variables between groups. Spearman correlation coefficient and linear-regression analysis were used. Results: The results indicated a moderate negative correlation between sleep efficiency and particular injury characteristics, including absence time, injury severity, and amount of injuries. The linear-regression analysis indicated that 44% of the total variance in the number of injuries can be explained by sleep efficiency, 24% of the total variance in the absence time after injury (days) can be explained by sleep efficiency, and 47% of the total variance in the injury severity can be explained by sleep efficiency. Conclusions: Soccer players who exhibit lower sleep quality or nonrestorative sleep show associations with increased number and severity of musculoskeletal injuries.

Predictors of problematic Internet use in school going adolescents of Bhavnagar, India

2019 ◽  
Vol 65 (2) ◽  
pp. 151-157 ◽  
Author(s):  
Sneha B Vadher ◽  
Bharat N Panchal ◽  
Ashok U Vala ◽  
Imran J Ratnani ◽  
Kinjal J Vasava ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Regression Analysis ◽  
Linear Regression ◽  
Sleep Quality ◽  
Internet Use ◽  
Linear Regression Analysis ◽  
Poor Quality ◽  
Problematic Internet Use ◽  
Quality Of Sleep

Background: Problematic Internet use (PIU) is the inability of individuals to control their Internet use, resulting in marked distress and/or functional impairment in daily life. Aim/Objective: We assessed the frequency of PIU and predictors of PIU, including social anxiety disorder (SAD), quality of sleep, quality of life and Internet-related demographic variables among school going adolescents. Methods: This was an observational, single-centered, cross-sectional, questionnaire-based study of 1,312 school going adolescents studying in Grades 10, 11 and 12 in Bhavnagar, India. Every participant was assessed by a pro forma containing demographic details, questionnaires of Internet Addiction Test (IAT), Social Phobia Inventory (SPIN), Pittsburgh Sleep Quality Index (PSQI) and Satisfaction With Life Scale (SWLS) for PIU severity, SAD severity, Quality of Sleep assessment and Quality of Life assessment, respectively. The statistical analysis was done with SPSS Version 23 (IBM Corporation) using chi-square test, Student’s t test and Pearson’s correlation. Multiple linear regression analysis was applied to find the predictors of PIU. Results: We found frequency of PIUs as 16.7% and Internet addiction as 3.0% among school going adolescents. Participants with PIU are more likely to experience SAD ( p < .0001), poor quality of sleep ( p < .0001) and poor quality of life ( p < .0001). There is positive correlation between severity of PIU and SAD ( r = .411, p < .0001). Linear regression analysis shows PIU can be predicted by SAD, sleep quality, quality of life, English medium, male gender, total duration of Internet use, monthly cost of Internet use, education, social networking, gaming, online shopping and entertainment as purpose of Internet use. Conclusion: Participants with PIU are more likely to experience SAD, poor quality of sleep and poor quality of life.

scholarly journals Effect of Opioid Limiting Legislation on Postoperative Opioid Utilization in Patients Treated for Ankle Fractures

2020 ◽  
Vol 5 (4) ◽  
pp. 247301142093950
Author(s):  
Connor G. Hoge ◽  
Robert N. Matar ◽  
Colin D. F. Cotton ◽  
Michael G. Rubeiz ◽  
Tonya L. Dixon ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Postoperative Period ◽  
Injury Severity ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Ankle Fractures ◽  
Level Of Evidence ◽  
The Mean

Background: The state of Ohio implemented legislation in August of 2017 limiting the quantity of opioids a provider could prescribe. The purpose of this study was to identify if implementation of legislation affected opioid and nonopioid utilization in patients operatively treated for ankle fractures in the initial 90-day postoperative period after controlling for injury severity and preoperative narcotic usage. Methods: A retrospective review of 144 patients treated for isolated ankle fractures in a pre-law group (January 2017–July 2017; n = 73) and post-law group (January 2018–July 2018; n = 71) was completed using electronic medical records and a legal prescriber database. Total number of opioid prescriptions, pills, milligrams of morphine equivalents (MMEs), and nonopioid prescriptions were recorded. Multiple regression analysis was run to identify predictors of opioid prescribing after controlling for law group, demographic, preoperative narcotic use, and injury severity characteristics. Results: Mean MME prescribed per patient significantly decreased from 817.2 MME pre-law to 380.9 post-law ( P < .01). Mean number of opioid pills prescribed per patient decreased from 99.1 in the pre-law group and 55.3 in the post law group ( P < .001), respectively. Multiple linear regression analysis to predict the mean number of opioid pills prescribed was statistically significant ( R 2 = 0.33; P < .001), with law group adding significantly to the prediction ( P < .001). The multiple linear regression analysis to predict MME per patient was found to be statistically significant ( R 2 = 0.31; P < .001), with the law group contributing significantly ( P < .001). Conclusion: The Ohio prescriber law successfully contributed to the decreased number of opioid pills and MME prescribed in the initial 90-day postoperative period after controlling for injury severity and preoperative narcotic usage. Policies on opioid prescriptions may serve as an important public health tool in the fight against the opioid epidemic. Level of Evidence: Level III, retrospective comparative series.

scholarly journals Facial Injury Severity Scale Score as a Predictor of Length of Stay for Maxillofacial Fracture at Sanglah General Hospital, Denpasar, Bali, Indonesia

2020 ◽  
Vol 8 (B) ◽  
pp. 291-294
Author(s):  
Esther Felicita Tambayong ◽  
Nengah Kuning Atmadjaya ◽  
Nyoman Golden ◽  
Ketut Wiargitha ◽  
Gede Bagus Mahadewa Tjokorda
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Length Of Stay ◽  
General Hospital ◽  
Injury Severity ◽  
Linear Regression Analysis ◽  
Facial Injury ◽  
Severity Scale ◽  
Operating Characteristics ◽  
Maxillofacial Fracture

INTRODUCTION: Maxillofacial fracture is the most common trauma that happened in the developing countries. One of the methods to evaluate the severity of maxillofacial fracture is by using the Facial Injury Severity Scale (FISS) score. Maxillofacial trauma causes multiple injuries, thus resulted in various periods of hospitalization. AIM: The aim of this study is to use the employment of the FISS score to predict a patient’s length of stay. METHODS: This research was a retrospective cohort and cross-sectional study on maxillofacial fracture patients whom treated in Sanglah General Hospital, Denpasar, Bali. As much as 89 subjects were included in this study and information about their age, gender, mechanism of injury, FISS score, treatments, and length of stay was collected. The data were statistically analyzed using bivariate, receiver operating characteristics (ROC), and linear regression analysis. RESULTS: A total of 89 subjects were included in this study. Among them, 50 subjects had a high FISS score, and 39 subjects had low FISS score. The average age was 28.9 ± 13.3 years with a mean length of stay 6.39 ± 4.29 days. Bivariate analysis showed that the patients with high FISS score have 5.3 times higher risk to get a longer length of stay compared to those with low FISS score (95% CI: 2.289–12.289; p = 0.001). The mean of length of stay in subjects with a high FISS score was significantly higher compared to subjects with a low FISS score (mean for subjects with high score: 8.46 ± 4.63; mean for subjects with low score: 3.74 ± 1.46; p = 0.001) with a correlation value r = 0.718 (p = 0.001). ROC analysis represented that FISS score ˂4 was categorized as mild. The linear regression analysis showed that the length of stay for maxillofacial fracture patients was able to be predicted by LOS = 1.476 + 1.032 × FISS score. CONCLUSION: The FISS score can predict the length of stay for patients with maxillofacial fracture.

scholarly journals Evaluation of the predictive power of job satisfaction by sleep quality and Morningness –eveningness types in nurses of academic centers in urmia 2019

2020 ◽  
Author(s):  
Masumeh HEMMATI MASLAK PAK ◽  
Farzin MOLLAZADEH ◽  
Hossein JAMSHIDI ◽  
Mohadeseh AMINI
Keyword(s):  
Job Satisfaction ◽  
Regression Analysis ◽  
Linear Regression ◽  
Sleep Quality ◽  
Correlation Coefficient ◽  
Predictive Power ◽  
Pearson Correlation ◽  
Linear Regression Analysis ◽  
Teaching Hospitals ◽  
Pearson Correlation Coefficient

Introduction: Nurses' job satisfaction is a serious issue for health care systems so that decreased job satisfaction can cause problems for nurses and health systems. Job satisfaction can be affected by sleep quality and the morningness- eveningness preference (chronotypes) of nurses. The present study aimed to determine the predictive power of job satisfaction by sleep quality and morningness-eveningness chronotypes of nurses working in Urmia teaching hospitals in 2020. Methods: A total of 327 nurses working in teaching hospitals affiliated to Urmia University of Medical Sciences were enrolled in the study. Sampling was conducted using simple random method. Data were collected using Demographic information questionnaires, Pittsburgh Sleep Quality Index, Minnesota Satisfaction Questionnaire, and Composite Scale of Morningness. Data were analyzed using descriptive statistics, measures of central tendency, Pearson correlation coefficient, independent samples t-test, two-way ANOVA, and linear regression analysis. All statistical analysis were conducted using SPSS software version 16.0 (SPSS Inc., Chicago, Ill., USA). Results: The results of linear regression analysis and Pearson correlation coefficient indicated that there is a significant correlation between the job satisfaction and the sleep quality in nurses as an improvement in sleep quality leads to higher job satisfaction (P <0.01) and the sleep quality is one of the predictors of job satisfaction (P = 0.002). However, there was no significant correlation between the nurses’ job satisfaction and their morningness-eveningness chronotypes (P> 0.01). Conclusion: Nurses with higher levels of sleep quality have higher job satisfaction, although the morningness-eveningness chronotypes of nurses have no significant effect on their job satisfaction.

scholarly journals Evaluation of Sleep Disorder in Orthopaedic Trauma Patients: a Retrospective Analysis of 1129 Cases

2021 ◽  
Author(s):  
Hai Yang ◽  
Yi-jia Liu ◽  
Jia-lu Ye ◽  
Li-hong Zhao ◽  
Ling-li Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Sleep Quality ◽  
Sleep Disorder ◽  
Daily Living ◽  
Quality Index ◽  
Pittsburgh Sleep Quality Index ◽  
Linear Regression Analysis ◽  
Trauma Patients ◽  
Orthopaedic Trauma

Abstract Background In the ward of trauma center, It’s not unusual that the patients have sleep disorder, especially in the acute injury patients. Meanwhile, there is substantial evidence that sleep disorder is a predictor of depression and the important features of posttraumatic stess disorder.Methods From April 2018 to July 2019, all orthopaedic trauma patients were included in the retrospective study. Patients with mental impairment and craniocerebral injury were excluded from the study. Basic demographic data were collected. Pittsburgh sleep quality index(PSQI) was used to evaluate sleep quality, Visual Analog Scale (VAS) was used to evaluate physical pain, Pittsburgh sleep quality index(PSQI) was used to evaluate sleep quality, Barthel Index (BI) was used to evaluate activities of daily living(ADL) and Injury Severity Score (ISS) classification in medical records were collected. Univariate linear regression analysis and multivariate linear regression analysis were used to identify independently related factors.Results The average PSQI score was 6.3 (±4.0). Five hundred eighty-one (51.4%) patients had a PSQI score more than 5, indicating the presence of sleep disorder. The PSQI score was more than 10 in one hundred seventy-four (15.4%) patients. Univariate statistical analysis showed that age, gender, education, ADL (activities of daily living), and ISS classification were associated with increased PSQI scores. Marital status and pain were not associated with increased PSQI scores. When we used multivariate analysis to control for confounding variables, the gender, ADL, and ISS classification remained independently associated with PSQI (P =0.002, <0.000, and 0.002, respectively).Conclusions In our study, the sleep disorder is both common (51.4% PSQI >5) and serious (15.4% PSQI >10) in patients who suffered from traumatic orthopaedic injury. The following factors are closed associated with sleep disorder: gender, ADL and ISS classification. Besides, age and education level have independently impact on sleep quality. Unexpectedly, we find the VAS of pain was not independently associated with seriousness of sleep quality. This is inconsistent with the results reported in some literature.

Smart phone usage, sleep quality and depression in university students

2020 ◽  
pp. 002076402096020
Author(s):  
Fadime Kaya ◽  
Nihal Bostanci Daştan ◽  
Erkan Durar
Keyword(s):  
Regression Analysis ◽  
University Students ◽  
Sleep Quality ◽  
Linear Regression Analysis ◽  
Smart Phone ◽  
Analysis Data ◽  
Smart Phones ◽  
Short Version ◽  
Poor Sleep ◽  
Multivariate Linear Regression Analysis

Background: The smart phone contains various mobile applications specifically targeting their contents, such as information, messages, e-mail, education and entertainment towards youths. Problematic and excessive smart phone usage can cause many health problems including anxiety, depression and sleep disorders. Aims: The aim of this study is to analyse the relationship between smart phone usage, sleep quality and depression. Methods: Eight hundred and four students who owned smart phones were given the Information Form, Smart Phone Addiction Scale-Short Version, Pittsburgh Sleep Quality Index (PSQI) and Beck Depression Inventory (BDI). The descriptive statistics, independent sample t-test, one-way ANOVA, correlation analysis and multivariate regression analysis were used for analysis data. Results: The mean age of the students in the sample was 20.93 ± 2.44. It comprised female (65.0%) and male (35.0%) students. All of the students used smart phones. The daily smart phone usage duration was 7.85 ± 4.55 hour. According to the multivariate linear regression analysis results, significant relationships were statistically determined in the positive way between the smart phone addiction and PSQI point ( p  < .01) and BDI point ( p  < .01). Conclusion: Consequently, a relationship exists between smart phone usage, poor sleep quality and depressive symptoms in university students. The university students, whose depression point is high and sleep quality is poor, should be followed up with regarding the smart phone addiction.

scholarly journals Evaluation of sleep disorder in orthopedic trauma patients: a retrospective analysis of 1129 cases

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Hai Yang ◽  
Yi-jia Liu ◽  
Jia-lu Ye ◽  
Li-hong Zhao ◽  
Ling-li Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Sleep Quality ◽  
Sleep Disorders ◽  
Sleep Disorder ◽  
Linear Regression Analysis ◽  
Trauma Patients ◽  
Multivariate Linear Regression Analysis ◽  
Orthopedic Trauma ◽  
Orthopedic Injury

Abstract Background In the trauma center wards, it is not unusual for patients to have sleep disorders, especially patients with an acute injury. Meanwhile, there is substantial evidence that sleep disorder is a predictor of depression and is an important feature of posttraumatic stress disorder. Methods All orthopedic trauma patients confined in a trauma ward in West China Hospital of Sichuan University between April 2018 and July 2019 were included in this retrospective study. Patients with mental impairment or craniocerebral injuries were excluded from the study. Basic demographic data and the Injury Severity Score (ISS) classification based on medical records were collected. The Pittsburgh sleep quality index (PSQI) was used to evaluate sleep quality, the visual analog scale (VAS) was used to evaluate physical pain, and the Barthel Index (BI) was used to evaluate activities of daily living (ADL). Univariate linear regression analysis and multivariate linear regression analysis were used to identify independently related factors. Results The average PSQI score was 6.3 (± 4.0). A total of 581 (51.4%) patients had a PSQI score > 5, indicating the presence of sleep disorders. The PSQI score was > 10 in 174 (15.4%) patients. Univariate statistical analysis showed that age, sex, education, ADL, and ISS classification were associated with increased PSQI scores. Marital status and pain were not associated with increased PSQI scores. When we used multivariate analysis to control for confounding variables, sex, ADL, and ISS classification remained independently associated with PSQI (P = 0.002, < 0.000, and 0.002, respectively). Conclusions In our study, sleep disorders were common (51.4% with PSQI > 5) and serious (15.4% with PSQI > 10) in patients with traumatic orthopedic injury. The following factors were closely associated with sleep disorders: sex, ADL, and ISS classification. Moreover, age and educational attainment have an independent impact on sleep quality. Unexpectedly, the VAS score for pain was not independently associated with the seriousness of sleep quality, which may be related to preemptive and multimodal analgesia. Further studies are required to clarify this ambiguity.

ANALISIS PENGARUH INFLASI, KURS DAN IHSG TERHADAP RETURN REKSA DANA SAHAM PT NIKKO SECURITIES INDONESIA PERIODE 2014-2017

2019 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Muhammad Rois Rois ◽  
Manarotul Fatati Fatati ◽  
Winda Ihda Magfiroh
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Equity Fund ◽  
Stock Price Index

This study aims to determine the effect of Inflation, Exchange Rate and Composite Stock Price Index (IHSG) to Return of PT Nikko Securities Indonesia Stock Fund period 2014-2017. The study used secondary data obtained through documentation in the form of PT Nikko Securities Indonesia Monthly Net Asset (NAB) report. Data analysis is used with quantitative analysis, multiple linear regression analysis using eviews 9. Population and sample in this research are PT Nikko Securities Indonesia. The result of multiple linear regression analysis was the coefficient of determination (R2) showed the result of 0.123819 or 12%. This means that the Inflation, Exchange Rate and Composite Stock Price Index (IHSG) variables can influence the return of PT Nikko Securities Indonesia's equity fund of 12% and 88% is influenced by other variables. Based on the result of the research, the variables of inflation and exchange rate have a negative and significant effect toward the return of PT Nikko Securities Indonesia's equity fund. While the variable of Composite Stock Price Index (IHSG) has a negative but not significant effect toward Return of Equity Fund of PT Nikko Securities Indonesia

Struktur Organisasi, Desain Kerja, Budaya Organisasi Dan Pengaruhnya Terhadap Produktivitas Karyawan Studi Kasus Pada PT. XX Di Jakarta

Liquidity ◽  
2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Yanti Budiasih
Keyword(s):  
Organizational Culture ◽  
Regression Analysis ◽  
Linear Regression ◽  
Organizational Structure ◽  
Research Method ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Job Design ◽  
Employee Productivity ◽  
Dominant Influence

The objectives of this study are to analyze changes in organizational structure, job design, organizational culture and its influence on employee productivity at PT. XX in Jakarta and to identify variables that have a dominant influence on the productivity of employees. The research method used is using multiple linear regression analysis. The results show that the all variables simultaneously and partially change the organizational structure, job design, and organizational culture has a significant impact on employee productivity at PT. XXin Jakarta.

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