Danial Chaleshi, Fatemeh Badrabadi, Fatemeh Ghadiri Anari, Sepehr Sorkhizadeh, Z. Nematollahi, Mohammad Hosein Shirdareh Haghighi, M. Aghabagheri
{"title":"Depressive Symptom Level, Sleep Quality, and Internet Addiction among Medical Students in Home Quarantine during the COVID-19 Pandemic","authors":"Danial Chaleshi, Fatemeh Badrabadi, Fatemeh Ghadiri Anari, Sepehr Sorkhizadeh, Z. Nematollahi, Mohammad Hosein Shirdareh Haghighi, M. Aghabagheri","doi":"10.1155/2023/1787947","DOIUrl":null,"url":null,"abstract":"The COVID-19 pandemic has a major impact on the mental health of people around the world. Due to the possible impact of quarantine conditions on mental health, we decided to assess internet addiction, depressive symptom level (DSL), and sleep disorders among medical students during the quarantine of COVID-19. This cross-sectional study was performed among medical students during the COVID-19 quarantine in Iran. Participants were selected using the available sampling method. Sleep quality, internet addiction, and depression were assessed using an online survey of the Pittsburgh Sleep Quality Index (PSQI), Internet Addiction Test (IAT), and Patient Health Questionnaire-9 (PHQ-9), respectively. Also, sociodemographic data including age, gender, marital status, smoking status, living circumstances, and educational status were asked. Participants were asked to share the link in their class social media groups. SPSS (version 16) was used for statistical analysis. Students participated; 64.9% of whom were female (\n \n n\n =\n 564\n \n ), and the mean age of participants was 21.3 years. 74.1% of students’ educational status was not mainly clinical. 48.2%, 28.6%, and 27.1% had poor sleep quality, DSL, and internet addiction, respectively. Smoking (AOR: 3.49, 95% CI: 1.56-7.76), living with family (AOR: 1.75, 95% CI: 1.16-2.66), and using social media for more than 2 hours were defined as predictive factors for depression. 165 participants (19%) were diagnosed with both poor sleep quality and DSL. There was a positive correlation between PSQI and PHQ-9 (\n \n r\n \n : 0.51, \n \n P\n \n value <0.001). A positive correlation was observed between IAT and PHQ-9 (\n \n r\n \n : 0.56, \n \n P\n \n value <0.001). The rate of DSL, internet addiction, and poor sleep quality were increased and strong correlations between them were concluded. Variables of gender, GPA, and smoking status were the most important associated variables.","PeriodicalId":44029,"journal":{"name":"Mental Illness","volume":"40 1","pages":""},"PeriodicalIF":9.0000,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mental Illness","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2023/1787947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0
Abstract
The COVID-19 pandemic has a major impact on the mental health of people around the world. Due to the possible impact of quarantine conditions on mental health, we decided to assess internet addiction, depressive symptom level (DSL), and sleep disorders among medical students during the quarantine of COVID-19. This cross-sectional study was performed among medical students during the COVID-19 quarantine in Iran. Participants were selected using the available sampling method. Sleep quality, internet addiction, and depression were assessed using an online survey of the Pittsburgh Sleep Quality Index (PSQI), Internet Addiction Test (IAT), and Patient Health Questionnaire-9 (PHQ-9), respectively. Also, sociodemographic data including age, gender, marital status, smoking status, living circumstances, and educational status were asked. Participants were asked to share the link in their class social media groups. SPSS (version 16) was used for statistical analysis. Students participated; 64.9% of whom were female (
n
=
564
), and the mean age of participants was 21.3 years. 74.1% of students’ educational status was not mainly clinical. 48.2%, 28.6%, and 27.1% had poor sleep quality, DSL, and internet addiction, respectively. Smoking (AOR: 3.49, 95% CI: 1.56-7.76), living with family (AOR: 1.75, 95% CI: 1.16-2.66), and using social media for more than 2 hours were defined as predictive factors for depression. 165 participants (19%) were diagnosed with both poor sleep quality and DSL. There was a positive correlation between PSQI and PHQ-9 (
r
: 0.51,
P
value <0.001). A positive correlation was observed between IAT and PHQ-9 (
r
: 0.56,
P
value <0.001). The rate of DSL, internet addiction, and poor sleep quality were increased and strong correlations between them were concluded. Variables of gender, GPA, and smoking status were the most important associated variables.