scholarly journals Problematic Internet Use, Mental Health, and Sleep Quality among Medical Students: A Path-Analytic Model

2020 ◽  
Vol 42 (2) ◽  
pp. 128-135
Author(s):  
Mohammad Reza Shadzi ◽  
Alireza Salehi ◽  
Hossein Molavi Vardanjani
Keyword(s):  
Mental Health ◽  
Medical Students ◽  
Sleep Quality ◽  
Internet Use ◽  
Problematic Internet Use ◽  
Analytic Model ◽  
Path Analytic

scholarly journals Mental Health, Sleep Quality, Drinking Motives, and Alcohol-Related Consequences: A Path-Analytic Model

2013 ◽  
Vol 74 (6) ◽  
pp. 841-851 ◽  
Author(s):  
Shannon R. Kenney ◽  
Andrew Lac ◽  
Joseph W. LaBrie ◽  
Justin F. Hummer, ◽  
Andy Pham
Keyword(s):  
Mental Health ◽  
Sleep Quality ◽  
Drinking Motives ◽  
Analytic Model ◽  
Path Analytic

scholarly journals THE EFFECT OF PROBLEMATIC INTERNET USE ON THE SLEEP QUALITY OF MEDICAL STUDENTS

2015 ◽  
Vol 9 (4) ◽  
pp. 143 ◽  
Author(s):  
Aylin Demirci ◽  
Rumeysa Dogan ◽  
Yusuf Matrak ◽  
Emel Kuruoglu ◽  
Vildan Mevsim
Keyword(s):  
Medical Students ◽  
Sleep Quality ◽  
Internet Use ◽  
Problematic Internet Use

scholarly journals Compulsive Internet Use Scale: Psychometric Properties and Associations With Sleeping Patterns, Mental Health, and Well-Being in Lithuanian Medical Students During the Coronavirus Disease 2019 Pandemic

2021 ◽  
Vol 12 ◽  
Author(s):  
Egle Milasauskiene ◽  
Julius Burkauskas ◽  
Aurelija Podlipskyte ◽  
Orsolya Király ◽  
Zsolt Demetrovics ◽  
...  
Keyword(s):  
Mental Health ◽  
Medical Students ◽  
Sleep Quality ◽  
Psychometric Properties ◽  
Internet Use ◽  
Online Survey ◽  
Well Being ◽  
Self Report ◽  
Everyday Functioning ◽  
Patient Health

Background: The increase in problematic Internet use (PIU) among medical students and resident doctors during the coronavirus disease 2019 (COVID-19) pandemic may be leading to significant impairments in everyday functioning, including sleeping patterns, anxiety, depressive symptoms, and overall well-being. The Compulsive Internet Use Scale (CIUS) has been developed to assess the severity of PIU, however, it has not been elucidated whether this scale is also applicable to medical students and resident doctors. The first aim of this study was to explore the psychometric properties of the Lithuanian version of the CIUS. The second aim was to examine associations between subjectively reported mental health symptoms and PIU during the COVID-19 pandemic.Methods: A total of 524 medical students and resident doctors (78.60% women, mean age 24 [SD 3] years old) participated in an online survey between December 2020 and February 2021. Participants completed the CIUS, the Pittsburgh Sleep Quality Index (PSQI) questionnaire, the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder Assessment-7 (GAD-7), and the WHO—Five Well-Being Index questionnaire (WHO-5).Results: The confirmatory factor analysis (CFA) suggested brief versions (CIUS-5, CIUS-7, and CIUS-9) rather than the original (CIUS-14) version of the CIUS questionnaire as reliable and structurally stable instruments that can be used to measure compulsive Internet use severity in the sample of medical students and resident doctors. The most prevalent online behaviors were social media use (90.1%), online shopping (15.6%), and online gaming/gambling (11.3%). Students with higher CIUS scores reported significantly lower academic achievements during the 6 months (r = 0.12–0.13; p < 0.006), as well as more severe depressive and anxiety symptoms, worsened sleep quality, and lower sense of well-being (r = 0.21–0.41; p's < 0.001). Both, during workdays (d = 0.87) and weekend (d = 0.33), students spent more time online than resident doctors (p's < 0.001).Conclusion: The brief, 5-, 7-, and 9-item versions of the Lithuanian CIUS are reliable and valid self-report screening instruments for evaluating the severity of PIU symptoms among the medical student population. Symptoms of PIU during the COVID-19 period were associated with worsened self-reported mental health and everyday functioning.

scholarly journals Association of sleep quality and internet addiction among the medical students

2019 ◽  
Vol 7 (7) ◽  
pp. 2703
Author(s):  
Nidhi Nagori ◽  
Kinjal Vasava ◽  
Ashok U. Vala U. Vala ◽  
Imran J. Ratnani
Keyword(s):  
Medical Students ◽  
Sleep Quality ◽  
Internet Addiction ◽  
Internet Use ◽  
Poor Quality ◽  
Problematic Internet Use ◽  
Poor Sleep ◽  
Quality Of Sleep ◽  
Poor Sleep Quality

Background: The side effects of Internet overuse have been emerging progressively causing the emergence of a problem that is defined as internet addiction or problematic internet use. It also disrupts the sleep wake cycle so adversely affecting quality of sleep. This study is a preliminary step toward understanding the effect of internet addiction on sleep quality among medical college students in India.Methods: This was an observational, cross-sectional, single-centred, and self-assessable. Questionnaire based study administrated among 525 consenting medical students. The participants were assessed by proforma containing demographic details, variables related with internet use, questionnaires of IAT (Internet Addiction Test for Internet Use) and PSQI (Pittsburgh Sleep Quality Index for Sleep quality. Statistical data were analysed by Graph Pad InStat version 3.06 using Chi–square test and Mann-Whitney test.Results: There were 9.3% of all participants were considered problematic internet users with frequency of internet addiction 0.9%. Participants with problematic internet use are likely to have poor sleep quality (p<0.0001). 23.8% of all participants had poor sleep quality and 76.2% of the students had good quality of sleep. Participants with poor quality of sleep were having high IAT scores in comparison to participants with good quality of sleep. Severity of poor sleep quality is positively correlated with internet addiction (r2=0.233, p<0.0001).Conclusions: Participants with problematic internet use were more likely to have poor quality of sleep and vice a versa.

scholarly journals Problematic internet use among students of mental health: Preliminary findings from eastern India

2015 ◽  
Vol 6 (03) ◽  
pp. 452-454
Author(s):  
Sayantanava Mitra ◽  
Tathagata Mahintamani ◽  
Vipin Kumar ◽  
Shuvabrata Poddar ◽  
Urbi Mukherjee ◽  
...  
Keyword(s):  
Mental Health ◽  
Internet Use ◽  
Problematic Internet Use ◽  
Eastern India

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.

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