key: cord-0893102-olaybyme authors: Hoque, Md. Najmol; Hannan, Afsana; Imran, Shahin; Alam, Muhammad Ashiqul; Matubber, Bidyut; Saha, Sourav Mohan title: Anxiety and Its Determinants among Undergraduate Students during E-learning in Bangladesh Amid Covid-19 date: 2021-09-22 journal: J Affect Disord Rep DOI: 10.1016/j.jadr.2021.100241 sha: d170f6e079bdcaea527ce7ff3ef8ae895bd17285 doc_id: 893102 cord_uid: olaybyme BACKGROUND: The universities of Bangladesh are closed for more than seventeen months due to the covid-19 pandemic. This prolonged detachment has psychological consequences among the students. This study assessed the anxiety level and its determinants among the undergraduate students of Bangladesh, along with constraints faced by them during e-learning. METHODS: A web-based cross-sectional survey among 206 undergraduate students was conducted using a well-structured questionnaire. Their anxiety level was estimated using Zung's self-rating anxiety scale (SAS) and determinates were identified by employing a Tobit model. The problem confrontation index (PCI) was used to rank the constraints. RESULTS: About 82.5% of the undergraduate students in Bangladesh are experiencing mild to extreme anxiety, while 14.08% are experiencing extreme anxiety. Students' gender, father's year of schooling, family size, residential area, academic year, current accommodation, and access to high-speed internet affect their level of anxiety. Learning alone at home, lacking access to learning resources and inaccessibility to other e-learning platforms are the top three constraints students faced during e-learning. LIMITATIONS: Self-reported data, socio-demographic variables and online survey. CONCLUSION: Covid-19 has been causing anxiety among the students. This study recommends providing better internet services for facilitating e-learning along with access to different e-learning platforms. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a highly contagious virus responsible for coronavirus disease 2019 or COVID-19. The first known case was identified at the end of December 2019 in Wuhan city of China (Page et al., 2021; Chahrour et al., 2020) . The initial outbreak of COVID-19 in Wuhan spread rapidly in the other parts of China. The central government of China imposed a lockdown in Wuhan and other cities in Hubei on 23 January 2020 to lower the risk of further disease transmission (Xiang et al., 2020; Sahu, 2020) . The World Health Organization (WHO) declared a Public Health Emergency of International Concern on 30 January 2020 and later declared a pandemic on 11 March 2020 (WHO, 2020). As of 21 August, COVID-19 affects 223 countries and infected more than 211 million people worldwide, resulting in more than 4429425 deaths (Worldometer, 2021) . Bangladesh is one of the worst-affected countries in this pandemic because of its dense population and other factors (Johns Hopkins Coronavirus Resource Center, 2020; Mamun & Griffiths, 2020; Shammi et al., 2020; WHO, 2020) . On 08 March 2020, Bangladesh identified its foremost COVID-19 patient (Reuters, 2020) . Like other countries, the COVID-19 positive cases and deaths continuously surged in Bangladesh (Worldometer, 2021) . To protect the people of Bangladesh, the government declared a lockdown throughout the nation from 26 March to reduce the spread and risk of infection (Anwar et al., 2020) . From March 2020, Bangladesh announced to close all educational institutions, and approximately 40 million students are affected so far due to this pandemic (The Business Standard, 2020). Ìt has been 17 months since these educational institutions, including all the universities, are closed. Several reports showed that university students are at high risk during such pandemics for depression and anxiety (Zivin et al., 2009; American College Health Association, 2018) . Early literature has reported the impact of such pandemics on students' psychology, acute depression, and anxiety (Mosley et al., 1994; Aktekin et al., 2001) . A study in China reported that among 7143 students, 0.9% had severe anxiety, 2.7% had moderate anxiety, and 21.3% had mild anxiety during the COVID-19 pandemic (Cao et al., 2020) . Another report on 1210 students from 194 cities in China reported that 53.8% of students having severe to moderate psychological impact . Odriozola-González et al. (2020) reported the psychological impacts on Spanish university students, which showed that 34.19% of students have depression symptoms; 21.34% have anxiety symptoms. However, in Bangladesh, very little research has been found on the impact of COVID-19 on the education and anxiety of Bangladeshi university students. Hence, this study aims to determine the learning challenges and the level of anxiety among university students in Bangladesh during extended lockdown at the COVID-19 pandemic. A cross-sectional online survey was conducted among undergraduate students from different public universities in Bangladesh to evaluate their anxiety and challenges of e-learning. 'Google Form' (an online self-administered data collection tool by 'Google LLC') was used as a survey tool, and the link of the questionnaire was sent to participants via emails and social media platforms. An invitation to complete the survey was sent to a total of 2163 undergraduate students of public universities. Two hundred six students consented to participate in the online survey by giving their information where response rate was 9.52 percent. The data collection was launched on 13 March 2021 and continued to 05 April 2021. Before the final survey, the questionnaire was tested in a pilot study with ten random students. Based on the pilot study findings, the questionnaire was revised and finalized where needed according to the objectives. Besides, the purposes of the study were briefly explained to the respondents, and their consent was ensured prior to the data collection. The questionnaire included information about the student's socioeconomic characteristics and questions regarding their emotional, physical and mental symptoms during university lockdown to estimate their anxiety and challenges faced in e-learning. This study analyzed the anxiety level of the students during the COVID-19 pandemic using Zung's self-rating anxiety scale (SAS). SAS, developed by Zung (1971) , has affective psychometric properties found in several recent studies Dunstan et al., 2017) . This scale focuses on the most common general anxiety disorders; coping with stress typically causes anxiety. SAS is self-administered, and questions usually have a response of a 4-point scale (Ramirez & Lukenbill, 2008) . It works as a Likert-type scale of 1 to 4 where 1 = 'a little of the time', 2 = 'some of the time', 3 = 'good part of the time', and 4 = 'most of the time'. Questions 1-5 illustrate the emotional pointers of anxiety, while questions 6-20 imply the physical symptoms of anxiety. For each respondent, the totality of the scores from 20 items ranges from 20 to 80. The entirety of the scores is then converted to an "Anxiety Index," with scores ranging from 25 to 100. According to Zung (1971) , an Anxiety Index less than 45 specifies 'Normal anxiety,' a value in the range of 45-59 specifies 'Mild to moderate anxiety,' a value in the range of 60-74 designates 'Moderate to severe anxiety', and values ≥ 75 indicates 'Extreme anxiety.' The regression analysis has been employed to identify the determinants affecting students' level of anxiety. In this study, students' anxiety is an important kind of limited dependent variable that has a corner solution response. It is a continuous variable, but it has a boundary i.e., from zero to eighty. In this situation, the Tobit model can estimate the determinants (Wooldridge, 2002) . This model is widely used in various studies with such type of limited dependent variable (Nazu et al., 2021; Prodhan & Khan, 2018; Tansel & Bircan, 2006) . The model can be specified as follows: The latent variable y* satisfies the classical linear model assumptions; in particular, it has a normal, homoscedastic distribution with a linear conditional mean. Equation (4) implies that the observed variable, y, equals y* when y* >= 0, but y = 0 when y*<0. Because y* is normally distributed, the density of y given x is the same as the density of y* given x for positive values. The model was employed in this study as follows: ( Here, Y i = SAS Score; X 1 = Gender; X 2 = Academic year; X 3 = Father's year of schooling; X 4 = Mother's year of schooling; X 5 = Family size; X 6 = Family income; X 7 = Residential area; X 8 = Current accommodation; X 9 = Access to high-speed internet; β o = Intercept; β 1 to β 9 = Coefficient to be estimated. Constraints faced by students in this study were analyzed using Problem Confrontation Index (PCI). A four-point rating scale was used for measuring the problem confrontation score. The respondents were asked to respond against 11 major constraints which they faced in elearning during university lockdown. The weights assigned for each response were: 3 for high confrontation, 2 for medium confrontation, 1 for low confrontation, and 0 for not at all. The demographic characteristics of the students in this study are shown in all the students were sent back from the hostels to their homes which were mainly in rural and sub-urban areas. However, some students were living in the rented messes with other students mainly for continuing online classes as internet facilities in their localities were very poor. In this study, about 95.15% of the respondents stayed with their families, and the rest stayed in rental messes or apartments with their friends or alone. The average monthly family income of the respondents was 32557.5 BDT. The anxiety level among students was estimated based on Zung's anxiety index. Internal consistency of the 20 items in the self-rating anxiety scale (SAS) was high (Cronbach's alpha = 0.8726). Anxiety levels of the agricultural university students in this study is presented in The determinants of university students' anxiety were identified by employing the Tobit regression model. The results were presented in Table 3 . It reveals that the gender of the students has a significant positive effect on their anxiety level. Female students are more likely to suffer from anxiety than their counterparts. In this study, respondents do not much differ from each other in terms of their age. Besides, age is associated with their academic year. That's why the students' academic years are considered in the model, and it shows significant effects on their anxiety level. Students currently in 4 th and 5 th year are more likely to feel anxiety. The year of schooling of the students' father showed a negative impact on their anxiety, indicating that students whose father is educated are less likely to feel anxiety. The family size of the student has a significant negative influence on their anxiety. Note: ***, ** and * denotes significant at 1%, 5% an 10% level. The residential area also affected the student's anxiety levels. Students from urban areas are more prone to feel anxiety than those from rural and sub-urban areas. Current accommodation has a significant and positive effect on the students' anxiety. It implies that students who are not staying with their families are more affected by anxiety than those staying with their families. Lastly, students' access to high-speed internet influences their anxiety levels negatively. That means students with low-speed internet are more likely to feel anxiety than their counterparts. This study identified the constraints faced by university students in e-learning during lockdown using the problem confrontation index (PCI). The results of PCI are presented in Table 4 . It shows that learning alone is the most severe constraint for students during the lockdown. It obtained a score of 479 out of 618. The second most constraint was the lack of adequate learning resources at home. The third constraint found in this study was low access to other online learning platforms. The poor internet service in their locality ranked fourth. Other constraints are parents not being able to help much in study, e-learning not being effective for higher education, unable to study effectively from home, lack of enough internet data to facilitate e-learning, parents having low ICT knowledge to help in e-learning, and lack of proper training in e-learning from university, respectively. The whole world is going through inexpressible hardship due to the Covid-19 pandemic. It has been affecting every aspect of life ever since its inception. Education is one of the worst affected sectors, especially in developing countries like Bangladesh. All the educational institutions in the are closed since March 2020. This prolonged shutdown affects the psychological health of the students, especially those of higher studies. Hence, this study assessed the anxiety level of university students along with its determinants and constraints faced by them during e-learning. Findings from the online cross-sectional survey reveal that about 82.5% of the undergraduate students in Bangladesh is experiencing mild to extreme level of anxiety. Previous studies also reported a high presence of anxiety among the students. reported that 87.7% of students suffer from anxiety, whereas Shamsuddin et al. (2013) found that 64.8% of medical students have different anxiety levels. Anxiety among students is mainly due to the sense of uncertainty about an academic and professional career. Results reveal that female students exhibited higher anxiety than male students, which is in line with Di Marco et al. (2006) . Previous literature reported that stress exposure increases rates of mental problems in females . Students of last year are experiencing more anxiety than others. These students are very close to their graduation, but they have yet to complete it due to the lockdown, which could explain the results. Father's education affected the students' anxiety levels negatively. Educated persons are more aware of mental health issues. That's why they are more concerned about their children's mental health. This study also reveals that students from large families are less affected by anxiety. Ozer et al. (2008) also found similar results among Mexican adolescents. People from large families usually have fewer mental problems due to the favorable environment (Grinde & Tambs, 2016) . Urban students are feeling more anxiety which conforms with the findings of Özdin & Özdin (2020) . This is because urban areas in Bangladesh are more affected by covid 19 due to dense population . Besides, there are limited recreational options in cities during the pandemic. The findings also indicate that students living without their families are experiencing more anxiety due to the stress of living alone and inadequate nutrient intake. This result is in line with the findings of Arusha & Biswas (2020) . The necessity of high-speed internet during this pandemic is immense, and it is compulsory for participating in e-learning. This study found that students who do not have high-speed internet connections feel more anxiety. Students often cannot connect or gets interrupted during a class because of a poor internet connection. The problem confrontation index reveals that the biggest constraint in e-learning is to learn alone. In universities, they can discuss their study topic with their classmates, seniors, and teachers, facilitating easy and better learning. Besides, students have access to books, journals, datasets, and other learning resources from the university library, which is not possible during the lockdown. That's why the second-ranked problem was the lack of adequate learning resources at home. The third most constraint was low access to other online learning platforms. Many online platforms such as Udemy, Coursera, Edx, Skillshare, etc., provide different academic and skill development courses conducted by worldwide popular teachers and personnel. Since most of the courses are paid for, many students cannot access these courses. Poor internet connection ranked fourth since most regions in Bangladesh do have good internet connectivity, which hinders students in e-learning. Similar findings were reported by Almaiah et al. (2020) . Some limitations of this study should be acknowledged. Firstly, it relied on self-reported data, and the respondents may not have provided stable responses to questions identifying their anxiety. Secondly, this study did not consider the physiological data of the respondents. Students' physical factors may influence their anxiety level, which needs future longitudinal or experimental studies. Thirdly, this study was conducted based on an online survey, and only virtually available students participated. Universities in Bangladesh are closed due to Covid-19 for more than a year. This extended university lockdown has adverse effects on the mental health of the students. Therefore, this study assessed the anxiety level of university students and identified the determinants of their anxiety. Additionally, constraints faced by them in e-learning during this lockdown were examined. A primary dataset collected from an online survey was used where different information of the students was gathered. Zung Self-Rating Anxiety Scale (SAS) is used to assess the anxiety level, and the Tobit model was employed to identify the determinants. Results reveal that 29.1% and 14.08% of the students were experienced moderate to severe and extreme anxiety, respectively. Various factors influenced their anxiety level. Female students, students from urban areas, last academic year students, and students living without family are more likely to feel anxiety. On the other hand, students with educated fathers, students from large families, and students who have access to high-speed internet are less prone to feel anxiety. Moreover, students face problems in learning alone at home and lack access to learning resources and other e-learning platforms. This study suggested providing better internet services for facilitating e-learning. Universities should provide students institutional access to different e-learning platforms. This study would play a vital role in policy making to understand students' mental health and facilitate better e-learning at home and abroad. All the authors listed in the manuscript contributed substantially to the study. Md. Najmol Hoque designed the study and collected data. Afsana Hannan and Md. 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