İŞE BAĞLILIĞIN TÜKENMİŞLİK VE DEPRESYON DÜZEYLERİ ÜZERİNDEKİ ETKİLERİ: SAĞLIK ÇALIŞANLARI ÜZERİNDE BİR ARAŞTIRMA

2014 ◽  
Vol 1 (2) ◽  
pp. 206
Author(s):  
Haluk TANRIVERDİ ◽  
Mucize SARIHAN
Keyword(s):  
Regression Analysis ◽  
Correlation Analysis ◽  
Health Workers ◽  
Personal Information ◽  
Depression Scale ◽  
Work Commitment ◽  
Statistical Software ◽  
Research Hospital ◽  
Training And Research

The main purpose of this study is to examine the effects of health workers’ levels of work commitment on the levels of depression and burnout.  Having this purpose in mind, a questionnaire consisting of personal information form, work commitment scale, burnout scale and depression scale was conducted with 266 health workers of İstanbul Kartal Training and Research Hospital in May 2013. Data obtained from questionnaires were analyzed by SPSS 17,0 statistical software. Correlation analysis was utilized in order to determine the relationships among work commitment, burnout and depression levels of health workers whereas regression analysis was utilized in order to determine the effects of health workers’ levels of work commitment on the levels of depression and burnout. According to the results, it has been found that there are statistically relevant relationships among work commitment, burnout and depression levels of health workers. It has been concluded that the more health workers’ levels of work commitment increase, their levels of depression and burnout decrease.

İŞE BAĞLILIĞIN TÜKENMİŞLİK VE DEPRESYON DÜZEYLERİ ÜZERİNDEKİ ETKİLERİ: SAĞLIK ÇALIŞANLARI ÜZERİNDE BİR ARAŞTIRMA THE EFFECTS OF WORK COMMITMENT ON THE LEVELS OF BURNOUT AND DEPRESSION: A RESEARCH ON THE HEALTH CARE EMPLOYEES

2014 ◽  
Vol 1 (2) ◽  
pp. 206
Author(s):  
Haluk TANRIVERDİ ◽  
Mucize SARIHAN
Keyword(s):  
Health Care ◽  
Regression Analysis ◽  
Correlation Analysis ◽  
Health Workers ◽  
Personal Information ◽  
Depression Scale ◽  
Work Commitment ◽  
Statistical Software ◽  
Health Care Employees ◽  
Training And Research

The main purpose of this study is to examine the effects of health workers’ levels of work commitment on the levels of depression and burnout.  Having this purpose in mind, a questionnaire consisting of personal information form, work commitment scale, burnout scale and depression scale was conducted with 266 health workers of İstanbul Kartal Training and Research Hospital in May 2013. Data obtained from questionnaires were analyzed by SPSS 17,0 statistical software. Correlation analysis was utilized in order to determine the relationships among work commitment, burnout and depression levels of health workers whereas regression analysis was utilized in order to determine the effects of health workers’ levels of work commitment on the levels of depression and burnout. According to the results, it has been found that there are statistically relevant relationships among work commitment, burnout and depression levels of health workers. It has been concluded that the more health workers’ levels of work commitment increase, their levels of depression and burnout decrease.

scholarly journals The Role of Campus Data in Representing Depression Among College Students: Exploratory Research (Preprint)

2018 ◽  
Author(s):  
Guang Mei ◽  
Weisheng Xu ◽  
Li Li ◽  
Zhen Zhao ◽  
Hao Li ◽  
...  
Keyword(s):  
Academic Performance ◽  
Depressive Symptoms ◽  
Correlation Analysis ◽  
Personal Information ◽  
Influencing Factor ◽  
Depression Scale ◽  
Machine Learning Algorithms ◽  
Daily Routine ◽  
Exploratory Research ◽  
Online Questionnaire

BACKGROUND Depression is a predominant feature of many psychological problems leading to extreme behaviors and, in some cases, suicide. Campus information systems keep detailed and reliable student behavioral data; however, whether these data can reflect depression and we know the differences in behavior between depressive and nondepressive students are still research problems. OBJECTIVE The purpose of this paper is to investigate the behavioral patterns of depressed students by using multisource campus data and exploring the link between behavioral preferences and depressive symptoms. The campus data described in this paper include basic personal information, academic performance, poverty subsidy, consumption habit, daily routine, library behavior, and meal habit, totaling 121 features. METHODS To identify potentially depressive students, we developed an online questionnaire system based on a standard psychometric instrument, the Zung Self-Rating Depression Scale (SDS). To explore the differences in behavior of depressive and nondepressive students, the Mann-Whitney U test was applied. In order to investigate the behavioral features of different depressive symptoms, factor analysis was used to divide the questionnaire items into different symptom groups and then correlation analysis was employed to study the extrinsic characteristics of each depressive symptom. RESULTS The correlation between these factors and the features were computed. The results indicated that there were 25 features correlated with either 4 factors or SDS score. The statistical results indicated that depressive students were more likely to fail exams, have poor meal habits, have increased night activities and decreased morning activities, and engage less in social activities (eg, avoiding meal times with friends). Correlation analysis showed that the somatic factor 2 (F4) was negatively correlated with the number of library visits (<i>r</i>=–.179, <i>P</i>&lt;.001), and, compared with other factors, had the greatest impact on students’ daily schedule, eating and social habits. The biggest influencing factor to poor academic performance was cognitive factor F1, and its score was found to be significantly positively correlated with fail rate (<i>r</i>=.185, <i>P</i>=.02). CONCLUSIONS The results presented in this study indicate that campus data can reflect depression and its symptoms. By collecting a large amount of questionnaire data and combining machine learning algorithms, it is possible to realize an identification method of depression and depressive symptoms based on campus data.

scholarly journals The Role of Campus Data in Representing Depression Among College Students: Exploratory Research

10.2196/12503 ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. e12503 ◽  
Author(s):  
Guang Mei ◽  
Weisheng Xu ◽  
Li Li ◽  
Zhen Zhao ◽  
Hao Li ◽  
...  
Keyword(s):  
Academic Performance ◽  
Depressive Symptoms ◽  
Correlation Analysis ◽  
Personal Information ◽  
Influencing Factor ◽  
Depression Scale ◽  
Machine Learning Algorithms ◽  
Daily Routine ◽  
Exploratory Research ◽  
Online Questionnaire

Background Depression is a predominant feature of many psychological problems leading to extreme behaviors and, in some cases, suicide. Campus information systems keep detailed and reliable student behavioral data; however, whether these data can reflect depression and we know the differences in behavior between depressive and nondepressive students are still research problems. Objective The purpose of this paper is to investigate the behavioral patterns of depressed students by using multisource campus data and exploring the link between behavioral preferences and depressive symptoms. The campus data described in this paper include basic personal information, academic performance, poverty subsidy, consumption habit, daily routine, library behavior, and meal habit, totaling 121 features. Methods To identify potentially depressive students, we developed an online questionnaire system based on a standard psychometric instrument, the Zung Self-Rating Depression Scale (SDS). To explore the differences in behavior of depressive and nondepressive students, the Mann-Whitney U test was applied. In order to investigate the behavioral features of different depressive symptoms, factor analysis was used to divide the questionnaire items into different symptom groups and then correlation analysis was employed to study the extrinsic characteristics of each depressive symptom. Results The correlation between these factors and the features were computed. The results indicated that there were 25 features correlated with either 4 factors or SDS score. The statistical results indicated that depressive students were more likely to fail exams, have poor meal habits, have increased night activities and decreased morning activities, and engage less in social activities (eg, avoiding meal times with friends). Correlation analysis showed that the somatic factor 2 (F4) was negatively correlated with the number of library visits (r=–.179, P<.001), and, compared with other factors, had the greatest impact on students’ daily schedule, eating and social habits. The biggest influencing factor to poor academic performance was cognitive factor F1, and its score was found to be significantly positively correlated with fail rate (r=.185, P=.02). Conclusions The results presented in this study indicate that campus data can reflect depression and its symptoms. By collecting a large amount of questionnaire data and combining machine learning algorithms, it is possible to realize an identification method of depression and depressive symptoms based on campus data.

Incidence of depression and its influencing factors in 387 patients with asthma from Xinjiang, China

2020 ◽  
Vol 41 (2) ◽  
pp. e45-e53 ◽  
Author(s):  
Dilinuer Wufuer ◽  
Haidiya Aierken ◽  
Yan Fang ◽  
Mihereguli Simayi ◽  
Kelibiena Tuerxun ◽  
...  
Keyword(s):  
Risk Factors ◽  
Regression Analysis ◽  
Depression Scale ◽  
High Morbidity ◽  
Hamilton Depression Scale ◽  
Multiple Factors ◽  
Asthma Symptoms ◽  
Depression Status ◽  
Treatment Of Depression ◽  
Quality Life

Background: Our study aimed to investigate the incidence of depression in 387 patients with asthma. Methods: The Zung self-rating depression scale and the Hamilton depression scale were used to evaluate the depression status in patients with asthma. Results: Results of logistic regression analysis indicated that, severity of asthma symptoms, taking medicine, frequency of asthma onset, and lack of education were the major risk factors for depression in patients with asthma. Conclusion: Depression is a complication with high morbidity in patients with asthma. It largely affects disease control of asthma and the quality life in patients. Multiple factors are relevant for depression in the patient with asthma. This study provided a comprehensive horizon for clinical management and treatment of depression in patients with asthma.

The Effects of Exercise Commitment Facilitated by Service Quality of Smartphone Exercise Applications on Continued Exercise Intention

2019 ◽  
Vol 118 (1) ◽  
pp. 14-19
Author(s):  
Boo-Gil Seok ◽  
Hyun-Suk Park
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Regression Analysis ◽  
Statistical Analysis ◽  
Correlation Analysis ◽  
Service Quality ◽  
Frequency Analysis ◽  
Primary Data ◽  
Exercise Intention

Background/Objectives: The purpose of this study is to examine the effects of exercise commitment facilitated by service quality of smartphone exercise Apps on continued exercise intention and provide primary data for developing and/or improving smartphone exercise Apps. Methods/Statistical analysis: A questionnaire survey was conducted amongst college students who have experiences in using exercise App(s) and regularly exercise. The questionnaire is composed of four parts asking about service quality, exercise commitment, continued exercise intention, which were measured with a 5-point Likert Scale, and demographics. Frequency analysis, factor analysis, correlation analysis, and regression analysis were carried out to analyze the obtained data with PASW 18.0.

Analysis of variations in and correlations between selected physical parameters of common beech (Fagus silvatica L.) nuts

2017 ◽  
Vol 1 (21) ◽  
pp. 49-63
Author(s):  
Zdzisław Kaliniewicz ◽  
Piotr Markowski ◽  
Andrzej Anders ◽  
Paweł Tylek ◽  
Zbigniew Krzysiak ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Correlation Analysis ◽  
Cross Sections ◽  
Linear Regression Analysis ◽  
Physical Parameters ◽  
Common Beech ◽  
Mesh Screen ◽  
Before And After ◽  
Fagus Silvatica ◽  
Highly Correlated

The basic dimensions and the mass of common beech nuts and seeds from five nut batches, harvested from tree stands in northern Poland, were determined. Environmental conditions had a greater influence on seed plumpness than the age of tree stands. The results of measurements were analyzed statistically by analysis of variance, correlation analysis and linear regression analysis. Despite differences in their plumpness, nuts were characterized by nearly identical cross-sections which resembled an equilateral triangle. The thickness of nuts and seeds was highly correlated with their mass, and this information can facilitate seed husking and separation into mass categories. Before and after husking, seeds should be separated with the use of a mesh screen with longitudinal openings. Medium-sized (most numerous) seeds were separated into the following plumpness categories using a screen separator with ≠6 mm and ≠7 mm openings: 84% of moderately plump seeds, 3% of seeds with reduced plumpness, and 13% of plump seeds.

PREVALENCE AND RELATED FACTORS OF POSTNATAL DEPRESSION IN HIV INFECTED WOMEN

2014 ◽  
pp. 140-152
Author(s):  
Manh Hoan Nguyen ◽  
Ngoc Thanh Cao
Keyword(s):  
Regression Analysis ◽  
Postpartum Depression ◽  
Hiv Infection ◽  
Postnatal Depression ◽  
Past History ◽  
Depression Scale ◽  
Multivariate Regression Analysis ◽  
Related Factors ◽  
History Of ◽  
History Of Depression

Background and Objective: HIV infection is also a cause of postpartum depression, however, in Vietnam, there has not yet the prevalence of postpartum depression in HIV infected women. The objective is to determine prevalence and related factors of postpartum depression in HIV infected women. Materials and Methods: From November 30th, 2012 to March 30th, 2014, a prospective cohort study is done at Dong Nai and Binh Duong province. The sample includes135 HIV infected women and 405 non infected women (ratio 1/3) who accepted to participate to the research. We used “Edinburgh Postnatal Depression Scale (EPDS) as a screening test when women hospitalized for delivery and 1 week, 6weeks postpartum. Mother who score EPDS ≥ 13 are likely to be suffering from depression. We exclude women who have EPDS ≥ 13 since just hospitalize. Data are collected by a structural questionaire. Results: At 6 weeks postpartum, prevalence of depression in HIV infected women is 61%, in the HIV non infected women is 8.7% (p < 0.001). There are statistical significant differences (p<0.05) between two groups for some factors: education, profession, income, past history of depression, child’s health, breast feeding. Logistical regression analysis determine these factors are related with depression: late diagnosis of HIV infection, child infected of HIV, feeling guilty of HIV infected and feeling guilty with their family. Multivariate regression analysis showed 4 factors are related with depression: HIV infection, living in the province, child’s health, past history of depression. Conclusion: Prevalence of postpartum depression in HIV infected women is 61.2%; risk of depression of postnatal HIV infected women is 6.4 times the risk of postnatal HIV non infected women, RR=6.4 (95% CI:4.3 – 9.4). Domestic women have lower risk than immigrant women from other province, RR=0.72 (95% CI:0.5 – 0.9). Past history of depression is a risk factor with RR=1.7 (95% CI:1.02 – 0.9. Women whose child is weak or die, RR=1.7(95% CI:0.9 – 3.1). Keywords: Postpartum depression, HIV-positive postpartum women

scholarly journals Estimation of Outdoor PM2.5 Infiltration into Multifamily Homes Depending on Building Characteristics Using Regression Models

2021 ◽  
Vol 13 (10) ◽  
pp. 5708
Author(s):  
Bo-Ram Park ◽  
Ye-Seul Eom ◽  
Dong-Hee Choi ◽  
Dong-Hwa Kang
Keyword(s):  
Regression Analysis ◽  
Correlation Analysis ◽  
Field Test ◽  
Outer Surface ◽  
Regression Models ◽  
Field Tests ◽  
Test Results ◽  
Correlation And Regression Analysis ◽  
Building Characteristics ◽  
Pm2.5 Concentration

The purpose of this study was to evaluate outdoor PM2.5 infiltration into multifamily homes according to the building characteristics using regression models. Field test results from 23 multifamily homes were analyzed to investigate the infiltration factor and building characteristics including floor area, volume, outer surface area, building age, and airtightness. Correlation and regression analysis were then conducted to identify the building factor that is most strongly associated with the infiltration of outdoor PM2.5. The field tests revealed that the average PM2.5 infiltration factor was 0.71 (±0.19). The correlation analysis of the building characteristics and PM2.5 infiltration factor revealed that building airtightness metrics (ACH50, ELA/FA, and NL) had a statistically significant (p < 0.05) positive correlation (r = 0.70, 0.69, and 0.68, respectively) with the infiltration factor. Following the correlation analysis, a regression model for predicting PM2.5 infiltration based on the ACH50 airtightness index was proposed. The study confirmed that the outdoor-origin PM2.5 concentration in highly leaky units could be up to 1.59 times higher than that in airtight units.

scholarly journals Psychotropic Drug Use in Children with Autism Spectrum Disorder Admitted to a Training and Research Hospital Outpatient Clinic: A Retrospective Cross-Sectional Study

2020 ◽  
Vol 10 (01) ◽  
pp. e233-e239
Author(s):  
Sabide Duygu Uygun ◽  
Fatma Hülya Çakmak ◽  
Merve Canlı ◽  
Rahime Duygu Temeltürk ◽  
Ayşegül Efe ◽  
...  
Keyword(s):  
Drug Use ◽  
Psychotropic Drug ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Psychiatric Comorbidities ◽  
Research Hospital ◽  
Clinical Variables ◽  
Hospital Outpatient Clinic ◽  
Psychotropic Drug Use ◽  
Training And Research

AbstractThis study aimed to examine demographic and clinical variables, psychiatric comorbidities, the prevalence of psychotropic drug use, relationships between drug use, demographic and clinical variables, and predictors of drug use in children with autism spectrum disorder (ASD) admitted to a training and research hospital outpatient clinic. Four hundred and eleven children with ASD admitted to the Department of Child and Adolescent Psychiatry, Dr. Sami Ulus Maternity and Children's Health and Diseases Training and Research Hospital, between October 1, 2019 and December 31, 2019, were retrospectively reviewed. Demographic and clinical variables, psychiatric comorbidities, and characteristics of drug use for the cases were recorded. Psychotropic drug use was found in 34.3% (n = 141) of the cases. Our results revealed male sex and psychiatric comorbidity as predictors of psychotropic drug use. Antipsychotics were the most prescribed drugs, and the most common psychiatric comorbidity was conduct disorder. Also, children with ASD who had been toilet-trained, and could express sentences but were illiterate, were using psychotropic drugs more often than others. Future multicentered, large clinic-based studies from training and research hospitals should focus on trends of treatment in psychiatric comorbidities accompanying ASD, and constitute a systematic approach for the psychopharmacological treatment of these cases.

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