scholarly journals Determining the Factors of Social Phobia Levels of University Students: A Logistic Regression Analysis

2016 ◽  
Vol 5 (1) ◽  
pp. 38-53 ◽  
Author(s):  
Hamit Ozen
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
University Students ◽  
Social Phobia ◽  
Logistic Regression Analysis

scholarly journals Attitudes towards the New Zealand Government’s Smokefree 2025 goal associated with smoking and vaping in university students aged 18 to 24 years: results of a 2018 national cross-sectional survey

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e037362
Author(s):  
Ben Wamamili ◽  
Mark Wallace-Bell ◽  
Ann Richardson ◽  
Randolph C Grace ◽  
Pat Coope
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
New Zealand ◽  
University Students ◽  
Confidence Intervals ◽  
Logistic Regression Analysis ◽  
Smoking Prevalence ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Lower Odds

ObjectiveIn March 2011, New Zealand (NZ) launched an aspirational goal to reduce smoking prevalence to 5% or less by 2025 (Smokefree 2025 goal). Little is known about university students’ awareness of, support for and perceptions about this goal. We sought to narrow the knowledge gap.SettingUniversity students in NZ.MethodsWe analysed data from a 2018 cross-sectional survey of university students across NZ. Logistic regression analysis examined the associations between responses about the Smokefree goal with smoking and vaping, while controlling for age, sex and ethnicity. Confidence intervals (95% CI) were reported where appropriate.ParticipantsThe sample comprised 1476 students: 919 (62.3%) aged 18 to 20 and 557 (37.7%) aged 21 to 24 years; 569 (38.6%) male and 907 (61.4%) female; 117 (7.9%) Māori and 1359 (92.1%) non-Māori. Of these, 10.5% currently smoked (ie, smoked at least monthly) and 6.1% currently vaped (ie, used an e-cigarette or vaped at least once a month).ResultsOverall awareness of the Smokefree goal was 47.5% (95% CI: 44.9 to 50.1); support 96.9% (95% CI: 95.8 to 97.8); belief that it can be achieved 88.8% (95% CI: 86.8 to 90.7) and belief that e-cigarettes/vaping can help achieve it 88.1% (95% CI: 86.0 to 89.9).Dual users of tobacco cigarettes and e-cigarettes had greater odds of being aware of the Smokefree goal (OR=3.07, 95% CI: 1.19 to 7.92), current smokers had lower odds of supporting it (OR=0.13, 95% CI: 0.06 to 0.27) and of believing that it can be achieved (OR=0.15, 95% CI: 0.09 to 0.24) and current vapers had greater odds of believing that e-cigarettes/vaping can help to achieve it (OR=8.57, 95% CI: 1.18 to 62.52) compared with non-users.ConclusionsThe results suggest strong overall support for the Smokefree goal and belief that it can be achieved and that e-cigarettes/vaping can help achieve it. Smoking and vaping were associated with high awareness of the Smokefree goal, but lower support and optimism that it can be achieved.

scholarly journals Factors affecting internet use among university students in Sarawak, Malaysia: an empirical study

2020 ◽  
Vol 7 (3) ◽  
pp. 848
Author(s):  
M. Mizanur Rahman ◽  
M. Taha Arif ◽  
Fready Luke ◽  
Santha Letchumi ◽  
Fatin Nabila ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
University Students ◽  
Logistic Regression Analysis ◽  
Internet Use ◽  
Binary Logistic Regression ◽  
Problematic Internet Use ◽  
The Internet ◽  
Binary Logistic Regression Analysis ◽  
Factors Affecting

Background: The internet has become an indispensable tool for communication, academic research, information and entertainment. However, heavy users of the internet lead to less confidence in social skills and the tendency to be isolated. The study aimed to assess the pattern of internet use and factors affecting problematic internet use among university students.Methods: This cross-sectional study conducted among the students of a university in Sarawak, Malaysia. A multistage cluster sampling technique was adapted to select the participants. Data were collected from 463 students by self-administered questionnaire. Hierarchical binary logistic regression analysis was done to determine the potential factors for problematic internet use.Results: The mean age of the students was 22 years, with a standard deviation of 1.6 years. Two-fifths (61.8%) of the students had no problematic internet use. However, 35.4% had moderate and 2.8% had severe problematic internet use. Hierarchical binary logistic regression analysis found that age of the students, year of study, duration of daily internet use and use of social networking like Skype appeared to be potential predictors of problematic internet use (p<0.05).Conclusions: This study was conducted in only one university, thus did not depict the overall scenarios of the country. The implications of the findings are still worth noting in the process of designing internet addiction studies among university students. Overall, this study has unearthed some useful insights which can serve as a guide to more elaborate studies.

scholarly journals Investigation of Factors Affecting the Achievement of University Students with Logistic Regression Analysis: School of Physical Education and Sport Example

SAGE Open ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 215824402090208
Author(s):  
Yeliz Eratlı Şirin ◽  
Mustafa Şahin
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Academic Success ◽  
Physical Education ◽  
University Students ◽  
Logistic Regression Analysis ◽  
Factors Affecting ◽  
Course Success ◽  
Effective Factor ◽  
The Way

In this study, the factors affecting the success of university students were analyzed by logistic regression analysis. In the study, success variable was defined according to the survey information applied to 360 university students studying in School of Physical Education and Sport in Çukurova University and Kahramanmaraş Sütçü İmam University in Turkey, in 2017–2018 academic year. The relationship between the answers to the Likert-type scale questions affecting success variables and the course success was estimated by logistic regression analysis. According to the results of the research, because independent variables such as mother’s education status, age, and class were statistically insignificant, they were not included in the multivariate model. According to the findings, variables such as gender, the university they studied, the way they chose their department, and father’s education are seen as important in the growth of students’ academic success. In addition to this, the variables such as counseling about their profession, support of department’s instructors, and communication with instructor have been found to be considerably effective on success. It was observed that the way they chose their department (willingly–compulsorily) was the most effective factor, and father’s education was the second effective factor. As a result, the success levels of the students were found to differ according to the sociodemographic characteristics and their relations with the instructors. On the contrary, as the instructors’ guidance, support, and communication skills are effective contributors on student’s success, it has been concluded that instructors should take these factors into account.

The relationship between social phobia and internet addiction in adolescents (Preprint)

2021 ◽  
Author(s):  
Ramazan Saglan ◽  
Tulin Fidan ◽  
Muhammed Fatih Onsuz ◽  
Selma Metintas
Keyword(s):  
High School ◽  
Logistic Regression ◽  
Regression Analysis ◽  
High School Students ◽  
Social Phobia ◽  
Logistic Regression Analysis ◽  
Internet Addiction ◽  
The Internet ◽  
School Students ◽  
The Relationship

BACKGROUND Adolescence is a risky stage for internet addiction and social phobia. Internet addiction is a major public health problem, especially among adolescents. OBJECTIVE The study was conducted to determine the frequency of internet addiction and social phobia, to evaluate the relationship between them among high school students in Eskişehir. METHODS The study is a cross-sectional study conducted on high school students studying in Eskişehir during the 2017-2018 academic year. In the study, two stage cluster sampling method was used according to settlement units and school types. The study group consisted of 3353 students who are found in selected schools for sampling and agreed to participate in the study. Multivariate logistic regression analysis was performed to determine the independent variables associated with social phobia and internet addiction. RESULTS In the study, the prevalence rates of internet addiction, social phobia, internet addiction and social phobia among the students was 13.8%, 8.7% and 2.7% respectively. Logistic regression analysis shows that internet addiction can be predicted by family type, tool for connecting to internet, age of first internet use, time to access the internet after waking up in the morning, total duration of internet use, self-limitation on the use of the internet and social phobia. CONCLUSIONS Internet addiction and social phobia are important health problems which are found to be related to each other in adolescents. Prevention and intervention studies should be planned about social phobia and internet addiction. CLINICALTRIAL 80558721/G-312

scholarly journals Depressive Symptoms among Haramaya University Students in Ethiopia: A Cross-Sectional Study

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Mitiku Teshome Hambisa ◽  
Andualem Derese ◽  
Tilahun Abdeta
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Depressive Symptoms ◽  
University Students ◽  
Logistic Regression Analysis ◽  
Associated Factors ◽  
Mental Health Problems ◽  
Cross Sectional Study ◽  
Cross Sectional

Background. The prevalence of mental health problems including depression is increasing in severity and number among higher institution students, and it has a lot of negative consequences like poor academic performance and committing suicide. Identifying the prevalence and associated factors of mental illness among higher institution students is important in order to administer appropriate preventions and interventions. In Ethiopia, only a few studies tried to report associated factors of depression among university students. Objective. The objective of this study was to determine the prevalence and factors associated with depressive symptoms among Haramaya University students, Ethiopia. Methods. Institution-based, cross-sectional study design was conducted among 1040 students. A standard, self-administered questionnaire was used to get data from a sample of randomly selected 1040 undergraduate university students using a multistage systematic random sampling technique. The questionnaire used was the Beck Depression Inventory (BDI) scale which is a self-report 21-item scale that is used to assess the presence of depressive symptoms. All 21 items are rated on a three-point scale (0 to 3). Each question is scored on a 0 to 3 scale, and total scores range from 0 to 63, with higher scores reflecting greater levels of depressive symptoms. The questionnaire has been well validated as a measure of depressive symptomatology with scores 1-13 indicating minimal depressive symptoms, 14-19 showing mild depressive symptoms, 20-28 showing moderate depressive symptoms, and 29-63 indicating severe depressive symptoms. Logistic regression analysis was used to identify variables independently associated with depressive symptoms after we dichotomized the depressive symptoms screening tool to “yes/no” depressive symptoms. This means students who did not report any depressive symptoms were given “no” depressive symptoms and who reported at least one (≥1) depressive symptoms were given “yes” (depressive symptoms). Results. A total of 1022 (98.3%) out of 1040 students participated in this study. The mean age of participants was 20.9 years (SD±2.17), and the majority of them (76.0%) were male students. Prevalence of depressive symptoms among undergraduate students was 26.8% (95% CI: 24.84, 28.76). Among those who had reported depressive symptoms: 10%, 12%, 4%, and 1% of students reported minimal, mild, moderate, and severe depressive symptoms, respectively. Multivariable logistic regression analysis in the final model revealed that being a first-year student (AOR 6.99, 95% CI: 2.31, 21.15, p value < 0.001), being a second-year student (AOR 6.25, 95% CI: 2.05, 19.07, p value < 0.001), and being a third-year student (AOR 3.85, 95% CI: 1.26, 11.78, p value < 0.018) and being divorced/widowed (AOR 5.91, 95% CI: 1.31, 26.72, p value < 0.021), current drinking alcohol (AOR 2.53, 95% CI: 1.72,3.72, p value < 0.001), current smoking cigarettes (AOR 1.71, 95% CI: 1.02, 2.86, p value < 0.042), and current use of illicit substances (AOR 2.20, 95% CI: 1.26, 3.85, p value < 0.006) were independently associated with depressive symptoms. Having no religion and currently chewing Khat were statistically significantly associated with depressive symptoms in the binary logistic regression analysis but not in the final model. Conclusions. The prevalence of depressive symptoms among university students in this study is high relative to the general population. Sociodemographic factors year of study and current substance use were identified as associated factors of depressive symptoms. Recommendations. This finding suggests the need for the provision of mental health services at the university, including screening, counseling, and effective treatment. Families need to closely follow their students’ health status by having good communication with the universities, and they have to play their great role in preventing depression and providing appropriate treatment as needed. The governments and policy-makers should stand with universities by supporting and establishing matured policies which helps universities to have mental health service centers. Generally, the university and other stakeholders should consider these identified associated factors for prevention and control of mental health problems of university students.

ANALISIS HUBUNGAN SARANA, PENGETAHUAN, DAN SIKAP BIDAN PRAKTIK MANDIRI DENGAN KEPATUHAN MENJALANKAN STANDAR PELAYANAN ANTENATAL CARE DI KOTA PADANGSIDIMPUAN

2019 ◽  
Vol 2 (1) ◽  
pp. 27-33
Author(s):  
Megawati Sinambela ◽  
Evi Erianty Hasibuan
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Antenatal Care ◽  
Pregnant Women ◽  
Logistic Regression Analysis ◽  
Care Service ◽  
Multivariate Logistic Regression Analysis ◽  
Bivariate Analysis ◽  
Cross Sectional ◽  
The North

Antenatal care is a service provided to pregnant women to monitor, support maternal health and detect mothers whether normal or problematic pregnant women. According to the WHO, globally more than 70% of maternal deaths are caused by complications of pregnancy and childbirth such as hemorrhage, hypertension, sepsis, and abortion. Based on data obtained from the profile of the North Sumatra provincial health office in 2017, in the city of Padangsidimpuan in 2017 the coverage of ANC visits reached (76.58%) and had not reached the target in accordance with the 2017 Provincial Health Office strategy plan (95%). This type of research was an observational analytic study with a cross sectional design. The population in this study were independent practice midwives who were in the Padangsidimpuan, the sample in this study amounted to 102 respondents. The technique of collecting data used questionnaires and data analysis used univariate, bivariate and multivariate analysis with logistic regression analysis. Based on bivariate analysis showed that there was a relationship between facilities, knowledge and attitudes of independent midwives with compliance with the standards of antenatal care services with a value of p <0.05. The results of the study with multivariate logistic regression analysis showed that the factors associated with the compliance of independent midwives in carrying out antenatal care service standards were attitudes with values (p = 0.026).

scholarly journals Efficacy of flurbiprofen axetil for preventing postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Atsushi Kotera
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Postoperative Pain ◽  
Logistic Regression Analysis ◽  
Pain Control ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Postoperative Pain Control ◽  
Flurbiprofen Axetil ◽  
Postanesthetic Shivering

Abstract Background Postanesthetic shivering is an unpleasant adverse event in surgical patients. A nonsteroidal anti-inflammatory drug has been reported to be useful in preventing postanesthetic shivering in several previous studies. The aim of this study was to evaluate the efficacy of flurbiprofen axetil being a prodrug of a nonsteroidal anti-inflammatory drug for preventing postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries. Method This study is a retrospective observational study. I collected data from patients undergoing gynecologic laparotomy surgeries performed between October 1, 2019, and September 30, 2020, at Kumamoto City Hospital. All the patients were managed with general anesthesia with or without epidural analgesia. The administration of intravenous 50 mg flurbiprofen axetil for postoperative pain control at the end of the surgery was left to the individual anesthesiologist. The patients were divided into two groups: those who had received intravenous flurbiprofen axetil (flurbiprofen group) and those who had not received intravenous flurbiprofen axetil (non-flurbiprofen group), and I compared the frequency of postanesthetic shivering between the two groups. Additionally, the factors presumably associated with postanesthetic shivering were collected from the medical charts. Intergroup differences were assessed with the χ2 test with Yates’ correlation for continuity category variables. The Student’s t test was used to test for differences in continuous variables. Furthermore, a multivariate logistic regression analysis was performed to elucidate the relationship between the administration of flurbiprofen axetil and the incidence of PAS. Results I retrospectively examined the cases of 141 patients aged 49 ± 13 (range 21-84) years old. The overall postanesthetic shivering rate was 21.3% (30 of the 141 patients). The frequency of postanesthetic shivering in the flurbiprofen group (n = 31) was 6.5%, which was significantly lower than that in the non-flurbiprofen group (n = 110), 25.5% (p value = 0.022). A multivariate logistic regression analysis showed that administration of flurbiprofen axetil was independently associated with a reduced incidence of postanesthetic shivering (odds ratio 0.12; 95% confidence interval, 0.02-0.66, p value = 0.015). Conclusions My result suggests that intraoperative 50 mg flurbiprofen axetil administration for postoperative pain control is useful to prevent postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries.

scholarly journals Prior Admissions as a Risk Factor for Readmission in Patients Surgically Treated for Femur Fractures: Implications for a Potential Hip Fracture Bundle

2021 ◽  
Vol 12 ◽  
pp. 215145932199616
Author(s):  
Robert Erlichman ◽  
Nicholas Kolodychuk ◽  
Joseph N. Gabra ◽  
Harshitha Dudipala ◽  
Brook Maxhimer ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Hip Fracture ◽  
Logistic Regression Analysis ◽  
Hip Fractures ◽  
Surgical Procedure ◽  
Hospital Admissions ◽  
Fracture Care ◽  
Increased Risk ◽  
Payment Models

Introduction: Hip fractures are a significant economic burden to our healthcare system. As there have been efforts made to create an alternative payment model for hip fracture care, it will be imperative to risk-stratify reimbursement for these medically comorbid patients. We hypothesized that patients readmitted to the hospital within 90 days would be more likely to have a recent previous hospital admission, prior to their injury. Patients with a recent prior admission could therefore be considered higher risk for readmission and increased cost. Methods: A retrospective chart review identified 598 patients who underwent surgical fixation of a hip or femur fracture. Data on readmissions within 90 days of surgical procedure and previous admissions in the year prior to injury resulting in surgical procedure were collected. Logistic regression analysis was used to determine if recent prior admission had increased risk of 90-day readmission. A subgroup analysis of geriatric hip fractures and of readmitted patients were also performed. Results: Having a prior admission within one year was significantly associated (p < 0.0001) for 90-day readmission. Specifically, logistic regression analysis revealed that a prior admission was significantly associated with 90-day readmission with an odds ratio of 7.2 (95% CI: 4.8-10.9). Discussion: This patient population has a high rate of prior hospital admissions, and these prior admissions were predictive of 90-day readmission. Alternative payment models that include penalties for readmissions or fail to apply robust risk stratification may unjustly penalize hospital systems which care for more medically complex patients. Conclusions: Hip fracture patients with a recent prior admission to the hospital are at an increased risk for 90-day readmission. This information should be considered as alternative payment models are developed for hip fracture care.

Sign in / Sign up

Export Citation Format

Share Document