Impact of COVID-19 Pandemic on Academic Activities of Academicians in Nepal

Abstract

This study explored the academic activities of academicians during the COVID-19 pandemic in Nepal. An online questionnaire was used to collect quantitative data from 361 academicians about changes in academic and extracurricular activities. The findings showed that the majority of participants (69% and 72%) agreed that both academic and extracurricular activities, respectively, were adversely affected by the lockdown during the pandemic. The results also showed that the study hours, sleeping hours, and social networking increased while concentration on academic activities decreased during the lockdown due to the COVID-19 pandemic.

Introduction

The first case of COVID-19 in Nepal was recorded on January 13, 2020, when a student from Wuhan returned to Nepal (Bastola et al., 2020). The World Health Organization (WHO) declared COVID-19 a pandemic on 11 March 2020, when the virus infection reached over 118,000 in 110 countries, while Nepal recorded only one case by that date. When there was a fast spread of the COVID-19 in different countries across the world, Nepal was still waiting to take measures to contain the spread of the virus in the country. On March 24^th, 2020, the Government of Nepal announced a nationwide lockdown after a second recorded case of coronavirus infection (Pradhan, 2020). The Government of Nepal Ministry of Health reported the first fatality in the country due to COVID-19 on March 16^th, 2020 (Poudel, 2020). After 4 months on July 28th, 2020, Nepal recorded 19,374 confirmed cases, 13,875 recovered, and 50 deaths, with a 0.26% fatality rate and a 71.62% recovery rate out of the total cases (CoronaTracker 2020). The rapid increase in the COVID-19 spread can be seen after the third week of May 2020 (Figure 1).

Figure 1.

Daily COVID-19 cases and deaths in Nepal [Source: https://ourworldindata.org/].

The nationwide lockdown was lifted by the government on July 21st, 2020, when the infection rate went down (Nepalitimes, 2020). Nonetheless, the second wave of the virus infection increased again rapidly in the months of April, May, and June 2021, reaching a record high daily case of 9,317 on May 11th, 2021. The fatality of 246 patients in a day was recorded in Nepal on May 19th, 2021 (https://github.com/CSSEGISandData/COVID-19). Then, the government imposed the second lockdown on April 29th, 2021, to contain the spread of the virus in the second wave (Prasai, 2021).

Again, Nepal experienced the third wave of COVID-19 with the serge of new variant Omicron on January 19th, 2022, pushing the infection bar as high as 9502 new cases; the highest number of fatalities due to the virus reached 32 on January 30th, 2022 (Figure 2). The introduction of the vaccine to 49.4% of the total population seemed a good effort to control the epidemic to some extent by the end of January 2022 (Figure 2c). Of the 17,186 tests, about 50% (8,524 tests) were reported positive on January 25th, 2022, showing that the infection might have widely spread to a large population in the country (Figure 2d). The infection rate then decreased and reached 33 new cases with no fatality record on June 23rd, 2022 (JHU CSSE, 2022). By this time, the Government of Nepal provided COVID-19 vaccines to 77.7% people at least a single dose and 69.3% full (Our World Data, 2022).

Figure 2.

Daily new cases, deaths, and vaccination rate in Nepal, (a) New COVID-19 cases daily, (b) Death rate per day, and (c) total vaccination percent. (d) Number of tests conducted each day. [Source: https://github.com/CSSEGISandData/COVID-19].

The coronavirus pandemic and the protracted lockdown affected education, economy, social behavior (Asian Development Bank, 2020), and other activities (WHO, 2020). Most governments in the world temporarily closed all the educational institutions to contain the spread of the COVID-19 pandemic. Universities had to shut down research and academic activities due to the coronavirus pandemic (Vagal et al., 2020). The pandemic had a negative effect on higher education (Gallo & Trompetto, 2020; Langella, 2020). These nationwide closures impacted over 60% of the world’s student population (UNESCO IESALC, 2020). Several other countries implemented localized closures that impacted millions of additional learners (Aydemir & Ulusu, 2020).

The transmission rate of the virus was very high (Kim & Bostwick, 2020) which made difficult managing and running the educational institutions even by implementing major safety protocols, such as social distancing, public transport reduction, and social isolation (De Vos, 2020; Xafis, 2020). Hence, a significant short-term and long-term consequences appeared in the higher education with more complexity and uncertainty (MoHP, 2020). In that context, Nepal’s education system had also been entirely affected by the pandemic (Dawadi et al., 2020). About 91% of the students enrolled in the formal education system were affected by the pandemic. However, distance learning through television and radio, online learning (CCSA, 2020), and virtual conferencing targeting university and school level students had been launched nationwide as alternative ways to continue teaching-learning activities (Rosen et al., 2020). Remote learning and tele-education had been applied during the pandemic period (UNESCAP, 2020). Still, the effectiveness of such virtual classes had been questioned because of the lack of access to resources by the rural and marginal learners (UNDP, 2020).

The educational institutions of Nepal were closed for around 1 year during the first and second phases of the pandemic situation (Asian Development Bank, 2021). Organization of Economic Cooperation and Development (OECD, 2020) showed that the academic activities of several countries were also affected by the pandemic (Farnell et al., 2021). The physical and mental activities of individuals were negatively affected by the pandemic (Lizana et al., 2021; Poudel & Subedi, 2020). Finnerty et al. (2021) reported that university students engaged in different musical activities through social media and virtual modes during the pandemic period. However, Koç and Koç (2021) found a negative effect of the pandemic on learners' extracurricular activities (ECA) and socialization. Some studies reported increased sleeping duration of students during the lockdown (Biswas et al., 2021; Joshi et al., 2020; Marelli et al., 2021), whereas variations were found in sleeping and waking up time in the pandemic period (Genta et al., 2021; Silva & Sobral, 2021). Yoga was found to be a major ECA activity among the medical students (Joshi et al., 2020). There was an increase students’ study hours by 5 hours/week (Aucejo et al., 2020). Most studies reported that the learners had psychological disturbances on academic activities during the pandemic (Son et al., 2020; Villani et al., 2021).

The continuous spread of disease, conspiracy theories, myths, sensational media reporting of COVID-19, and the implementation of lockdown were some of the risk factors that significantly impacted academic activities. Several students faced psychological distress (Grubic et al., 2020), which affected their mental health (Liang et al., 2020). Also, there had been psychological impacts of the epidemic on the general public, healthcare workers, teachers, and college students (Cao et al., 2020; Wang & Zhao, 2020). There was a substantial number of studies on Nepalese residents and their knowledge, attitudes, and practices regarding coronavirus (Hussain et al., 2020). However, very few studies assessed the issues related academic performance, extracurricular activities, psychological distress, and sleeping habits of Nepalese academics (i.e., students and teachers) during the COVID-19 pandemic. A number of factors the influenced educational experiences of individuals, such as institutional environment, curriculum, technological integration, assessment systems (Ginsburg & Smith, 2014), instructional language (European Commission/EACEA/Eurydice, 2018), institutional quality, learners’ background, learner participation, attitude, and aspirations (Bramley, 1995; Ogawa & Collom, 1998).

Schools made the use of face masks and sanitizer essential to continue face-to-face classes with frequent hand washing and social distancing (UNICEF, 2021a). However, the third wave of the new variants (Omicron) disturbed education again in Nepal in 2021. Schools and higher education institutions ran classes online or through virtual means such as phones, app-based videos, and online virtual sessions (UNICEF, 2021a). Despite these attempts, the quality of education, in general, was severely impacted by the pandemic throughout the years 2021 and the beginning of 2022. It impacted access to resources and student participation in the online classes despite the efforts that included Zoom meetings, Nepal Telecom’s happy learning program, and alternative methods applied by schools (UNICEF, 2021b). Therefore, teaching and learning were severely disrupted by the COVID-19 pandemic in all schools and higher education institutions in Nepal during the first, second, and third waves of the COVID-19. In this context, the present study aimed to assess the academic and extracurricular activities of academicians during a prolonged period of lockdown and its psychological effects on students and teachers in Nepal. This research attempted to answer the question: What is the effect of the COVID-19 pandemic on study-related activities, such as mental concentration, study and sleeping hours each day, and social networking along with academic and extracurricular activities among academicians in Nepal?

We considered the research question as a guiding tool for this study, focusing on school teachers, faculty members, and graduate students of higher education institutions. They were considered academicians in the study because of their active role in teaching, learning, and other academic activities, such as research and training. We kept this definition broad because there was a widespread impact of COVID-19 in almost all education sectors, and we wanted to gather data from a diverse sample.

Literature Review

Different impacts of the COVID-19 have been documented in the literature. These impacts are multi-dimensional. For example, Golestaneh et al. (2020) discussed how the mortality due to COVID-19 is associated with race. De Oliveira et al. (2020), Wang and Zhao (2020), Varalakshmi and Swetha (2020), and Rizwan et al. (2020) reported the psychological, social, and financial issues during the COVID-19 lockdown. We reviewed some literature to examine how COVID-19 affected life in general and education in particular at the beginning of the outbreak of the pandemic in 2020.

The COVID-19 had a differential impact on people. In this context, different studies reported various kinds of impacts of COVID-19 on their day-to-day life and professions. For example, mortality due to COVID-19 was associated with race (De Oliveira et al., 2020; Golestaneh et al., 2020), COVID-19 increased student anxiety (Wang & Zhao, 2020), the pandemic caused psychological disturbance and stress among the citizens (Hiremath et al., 2020; Varalakshmi and Swetha (2020), and it destabilized financial institutions (Rizwan et al., 2020).

Banerjee (2020), Dickerson (2020), Zandifar and Badrfam (2020) reported multi-dimensional impacts of COVID-19 on public in terms of increased anxiety, loneliness, difficulty in concentrating and distraction, stress threshold, and negative emotion spiral. They also highlighted public desperation, panic and fear, financial strain, and apprehension about the future as the significant psychological effects caused by the pandemic. Hiremath et al. (2020) mentioned stressful situations spreading everywhere, such as in the health sector, financial sector, educational institutions, social organizations, and even individuals.

As the entire world was severely affected the by the surge of the COVID-19 pandemic, it also negatively impacted education sector in Nepal. The Federal Government of Nepal introduced several measures to combat the pandemic and support the educational sector to continue teaching, learning, and other academic activities. The government provided the related institutions and local government bodies with guidelines and protocols to conduct educational activities during the pandemic (UNICEF, 2021b). The government approved COVID-19 Education Cluster Contingency Plan 2020, Alternative Learning Facilitation Guidelines, Emergency Action Plan for School Education, and School Reopening Framework (UNICEF, 2021b). Despite these efforts, more than 90% of the families needed additional financial support to continue their children’s education (UNICEF, 2021b).

Theoretical Framework

We developed a theoretical framework to study the effects of lockdown on students’ and teachers’ experiences due to COVID-19 in Nepal. The framework utilized the social, psychological, and educational aspects of COVID-19 to observe the perceptions of Nepalese academics (Figure 3).

Figure 3.

Theoretical framework for analyzing impacts of COVID-19 on the academicians’ perception of lockdown in Nepal.

The outbreak of the COVID-19 pandemic had a profound social impact across the globe with severe implications on economic policies, actions, and the management of resources (United Nations, 2020). The United Nations (2020) claimed that the pandemic had been “detrimental to members of those social groups in the most vulnerable situations and continues to affect populations, including people living in poverty situations, older people, people with disabilities, youth, and indigenous people” (para. 3). This issue has been further gravitated in the developing and least developed countries due to strict measures by their governments to ban public gatherings, businesses, and all economic activities, deteriorating family and community lives. It increased the possibility of “fracturing family and community relationships and undermining long-held trust between states and their citizens, with long-term implications for cohesion and social harmony” (UNESCO, 2020, p. 6). The social and economic consequences of COVID-19 have been further reflected in the severe decline in employment and other economic activities such as business, tourism, and education (World Bank Group, 2020). The COVID-19 pandemic has affected people’s mental health at all levels. This effect is more severe with the feeling of “loneliness, depression, harmful alcohol and drug use, and self-harm or suicidal behavior” (WHO, 2020, p. 1). The other psychological impacts of COVID-19 are—the stigma of being coronavirus positive, the burden of isolation and quarantine, and false information causing “coronavirus infodemic” (Dubey et al., 2020, p. 781). Besides socio-economic and psychological impacts, the outbreak of COVID-19 has severely impacted education at all levels due to lockdowns as a measure to protect students, teachers, and other community members from the virus (Rajhans et al., 2020). However, it has been considered a “constructive disruptor, allowing restructuring of the present conventional, classroom-based educational system” (Rajhans et al., 2020, p. 1).

Methodology

Study Instrument and Sample

The study was based on a cross-sectional survey with an online questionnaire constructed by the researchers. The questionnaire was constructed in Google Forms with seven items related to mental concentration, study and sleeping hours per day, social networking, resources for awareness, and academic and extracurricular activities. The questionnaire link from the Google Forms was shared with the potential participants through emails, Facebook walls, and Messenger. Age group, qualifications, and geographical locations were not limited to the respondents; the target was to reach at least 50 participants from each of the seven provinces in Nepal.

We collected data from April 15 to July 25, 2020 through the online questionnaire in the Google Forms. Three hundred sixty-one participants from different categories (school teachers, faculty members, and graduate students of higher education institutions) responded the questionnaire. This way, a self-constructed ‘Academic Activities during the COVID-19′ tool was implemented to assess the academic performance of the academicians in Nepal during the study period.

The validity of the tool was ensured through a pre-test in a sample of 20 participants and reviews of the instrument by three education, technology, and health-related experts. The reliability coefficient of Cronbach’s alpha was found to be 0.92, which showed a strong internal consistency among the items in the questionnaire (Patten & Newhart, 2018). Data collection through physical presence was not possible because of the lockdown during the COVID-19 pandemic. Hence, the samples were chosen by Facebook friends of the researchers, and they also requested that they share the link with their friends. Hence, the snowball sampling technique was applied in the data collection (Gallegati et al., 2021). The final survey with the online questionnaire was closed on July 25th, 2020.

Definition of Variables

The questionnaire included seven items related to participants’ mental concentration, study and sleeping hours per day, social networking, best resources for awareness, and academic and extracurricular activities as the variables for the study. The items of study-related activities were measured in three-point rating scales: decreased, as usual, and increased in comparison to before the COVID-19 pandemic. The items for academic and extracurricular activities included responses in the forms of yes and no. The best resources for awareness were measured as newspaper, television, and awareness programs. The study-related activities represented those activities that were, directly and indirectly, related to the study habits of the participants during the COVID-19 pandemic. Details of the variables are given in Figure 4.

Figure 4.

Conceptual framework of the variables in the study.

Six sociodemographic variables assessing age, gender, qualification, educational background, job role, location of residence, and time of using social media per day were used in the research. The age was divided into three categories as ≤ 30 years (36%), 31–40 years (39.6%), and ≥41 years (24.1%). Gender was divided into two categories as male (81.7%) and female (18.3%), and qualifications had four categories as high school level (4.2%), bachelor (22.4%), master (55.1%), and M.Phil./Ph.D. (18.3%). The educational background was divided into five categories; education (49.9%), science and technology (19.9%), humanities (17.2%), management (6.9%), and medical (6.1%), in which science and technology represented engineering, science, and computer science. Job roles were divided into four categories as teaching at the university level (28%), students (15.5%), school teachers (44.9%), and others job (11.6%), whereas the other job represented governmental and non-governmental job holders except teaching. The location of permanent residence was divided into seven categories as per decentralized units of the government of Nepal as province 1 (10.5%), Province 2 (13.9%), Bagmati Province (18.6%), Gandaki Province (14.4%), Lumbini Province (16.6%), Karnali Province (9.4%), and Sudur-Paschim Province (16.6%). The time spent on using social media was divided into four categories as less than 3 hours (39.3%), 3–6 hours (42.7%), 6–9 hours (12.2%), and more than 9 hours (5.8%) with reference to Table 1 and Table 2.

Table 1.

Status of study-related activities during COVID-19 pandemic based on sociodemographic characteristics (n = 361).

Categories	Frequency (%)	Study hours/day		Sleeping hours/day		Social Networking		Concentration
		Mean Rank	p-value	Mean Rank	p-value	Mean Rank	p-value	Mean Rank	p-value
Age
≤30 years	130 (36.0)	162.5	0.01*	188.2	0.11	179.8	0.11	167.1	0.07
31–40 years	144 (39.9)	183.9		185.5		174.2		193.9
≥41 years	87 (24.1)	204.0		162.9		194.1		180.5
Gender
Female	66 (18.3)	149.7	0.00*	201.2	0.05*	173.6	0.34	166.1	0.16
Male	295 (81.7)	188.0		176.5		182.7		184.3
Qualification
School level	15 (4.2)	141.8	0.00*	181.7	0.63	163.9	0.04*	181.8	0.34
Bachelor	81 (22.4)	133.5		187.4		165.3		168.1
Master	199 (55.1)	197.9		175.4		189.8		180.9
MPhil/Ph. D.	66 (18.3)	197.3		189.9		177.6		197.1
Stream
Education	180 (49.9)	195.5	0.00*	174.3	0.04*	181.4	0.62	186.2	0.22
Science & technology	72 (19.9)	141.0		182.8		183.4		178.0
Humanities	62 (17.2)	206.3		172.2		172.0		191.4
Management	25 (6.9)	173.4		196.8		177.6		158.0
Medical	22 (6.1)	130.9		236.6		199.6		145.4
Job type
University teachers	101 (28.0)	197.9	0.00*	180.4	0.09	189.4	0.28	189.4	0.62
Students	56 (15.5)	138.5		208.7		166.9		168.4
School teachers	162 (44.9)	193.7		175.4		179.7		181.0
Others	42 (11.6)	148.0		167.4		184.7		177.6
Location of residence
Province 1	38 (10.5)	184.6	0.32	160.1	0.05*	170.3	0.54	182.5	0.94
Province 2	50 (13.9)	157.6		168.2		186.2		180.8
Bagmati Province	67 (18.6)	180.5		205.4		193.4		174.6
Gandaki Province	52 (14.4)	203.4		171.8		175.8		178.7
Province 5	60 (16.6)	172.6		200.7		181.0		174.2
Karnali Province	34 (9.4)	191.9		184.0		166.0		184.3
Sudur-Paschim Province	60 (16.6)	181.5		164.3		182.7		194.3
Time of using social media
Less than 3 hours	142 (39.3)	183.5	0.89	171.2	0.37	169.3	0.07	187.3	0.65
3–6 hours	154 (42.7)	179.2		190.2		190.7		173.8
6–9 hours	44 (12.2)	174.3		181.8		185.3		182.0
More than 9 hours	21 (5.8)	191.2		178.1		180.0		188.9

*p-value ≤0.05 (i.e., Significant).

Table 2.

Associations of effect on academic and extracurricular activities by COVID-19 with sociodemographic characteristics (n = 361).

Sociodemographic Characteristics	Deteriorate Academic Activities			Deteriorate Extracurricular Activities
	Frequency (%)	Yes (%)	p-value	Yes (%)	p-value
Age					0.55
≤30 years	130 (36.0)	100 (76.9)	0.01*	97 (74.6)
31–40 years	144 (39.9)	99 (68.9)		104 (72.2)
≥41 years	87 (24.1)	50 (57.5)		59 (67.8)
Gender
Female	66 (18.3)	53 (80.3)	0.03*	49 (74.2)	0.66
Male	295 (81.7)	196 (66.4)		211 (71.5)
Qualification
School level	15 (4.2)	14 (93.3)	0.00*	10 (66.7)	0.27
Bachelor	81 (22.4)	70 (86.4)		63 (77.8)
Master	199 (55.1)	124 (62.3)		136 (68.3)
MPhil/Ph. D.	66 (18.3)	41 (62.1)		51 (77.3)
Stream
Education	180 (49.9)	115 (63.9)	0.12	125 (69.4)	0.10
Science & technology	72 (19.9)	55 (76.4)		50 (69.4)
Humanities	62 (17.2)	41 (66.1)		52 (83.9)
Management	25 (6.9)	20 (80.0)		20 (80.0)
Medical	22 (6.1)	18 (81.8)		13 (59/1)
Job type
University teachers	101 (28.0)	59 (58.4)	0.01*	71 (70.3)	0.03*
Students	56 (15.5)	46 (82.1)		41 (73.2)
School teachers	162 (44.9)	112 (69.1)		110 (67.9)
Others	42 (11.6)	32 (76.2)		38 (90.5)
Location of residence
Province 1	38 (10.5)	25 (65.8)	0.82	26 (68.4)	0.88
Province 2	50 (13.9)	36 (72.0)		36 (72.0)
Bagmati Province	67 (18.6)	44 (65.4)		48 (71.6)
Gandaki Province	52 (14.4)	34 (65.4)		36 (69.2)
Province 5	60 (16.6)	40 (66.7)		41 (68.3)
Karnali Province	34 (9.4)	24 (70.6)		27 (79.4)
Sudur-Paschim Province	60 (16.6)	46 (76.7)		46 (76.7)
Time of using social media
Less than 3 hours	142 (39.3)	99 (69.7)	0.96	103 (72.5)	0.24
3–6 hours	154 (42.7)	104 (67.5)		108 (70.1)
6–9 hours	44 (12.2)	31 (70.5)		30 (68.2)
More than 9 hours	21 (5.8)	15 (71.4)		19 (90.5)

*p-value ≤0.05 (i.e., Significant).

Statistical Analysis

Frequency and percentage as well as histogram and pie-chart were used as descriptive statistics to show the status of sociodemographic variables, duration of study and sleeping (hours per day), social networking, concentration, academic and extracurricular activities, and best resources for awareness. Since the dependent variables under study-related activities were measured on an ordinal scale, the Mann–Whitney U and Kruskal–Wallis H tests (Cohen et al., 2007) were adopted for sociodemographic variables having two and more than two categories, respectively. Additionally, academic and extracurricular activities were measured on a nominal scale (yes or no).Therefore, the Chi-square test (Stolp et al., 2004) was adopted to find the association between variables. An Ordinal Logistic Regression was utilized to estimate the effect of sociodemographic categories on study-related activities during the COVID pandemic. Additionally, a Binary Logistic Regression model was used to estimate the odds ratios for the deterioration of academic and extracurricular activities based on different sociodemographic categories.

Results

The results showed that one-third (32.4%) of the participants described their study time as decreasing due to the lockdown during the COVID-19 pandemic. More than half of the respondents (57.9%) reported having worse sleeping habits than usual because of the COVID-19-related lockdowns. Likewise, four-fifths (81.4%) of the respondents reported using social media for a more extended period than they used as usual during the lockdown period. Additionally, about two-fifths (38.8%) of the respondents felt a disturbance in their concentration on academic activities during the lockdown period (Figure 5). Similarly, more than two-thirds (69%, 72%) of the participants agreed that both academic and extracurricular activities, respectively, deteriorated during the lockdown (Figure 6), 42% of the participants used Facebook, and 24% of them watched television programs to get resources about COVID-19 (Figure 7).

Figure 5.

Status of study-related activities during COVID-19 pandemic.

Figure 6.

Status effect on academic and extracurricular activities by COVID-19.

Figure 7.

Best resources for awareness about COVID-19.

Results indicated significant differences in study hours/day with respect to age, gender, educational stream (i.e., educational background), and academic qualification. There were also differences in change of sleeping hours/day with respect to gender, educational stream, and location of their residences. Respondents reported changes in social networking associated with academic qualification. In the remaining cases of study hours/day, sleeping hours/day, social networking, and concentration, the results were found to be statistically insignificant with respect to measured sociodemographic characteristics at 95% of the confidence interval (Table 1). Additionally, Table 2 showed that the significant association was measured in deteriorating academic activities with respect to age, gender, academic qualification, and job type. Respondents indicated deteriorating extracurricular activities with respect to job type, whereas the associations were statistically insignificant in the remaining cases.

The results from ordinal logistic regression showed likelihood ratio between the effect of lockdown (in terms of odds ratio) during COVID-19 pandemic on study hours/day (χ2 (21, N = 361) = 53.93, p = 0.00 ≤ 0.05), sleeping hours/day (Likelihood ratio χ2 (21, N = 361) = 33.91, p = 0.04 ≤ 0.05), and social networking (Likelihood ratio χ2 (21, N = 361) = 35, p = 0.03 ≤ 0.05) which were found to be statistically significant at 95% confidence level. However, the result was statistically insignificant in the case of concentration (Likelihood ratio χ2 (21, N = 361) = 11, p = 0.96 > 0.05). The results from ordinal logistic regression showed that females were more likely to report an impact on sleeping hours/day than in males with adjusted odds ratio (AOR) = 1.29 ((0.70–2.38), but it was statistically not significant. However, the impact was statistically significant in the case of study hours/day with respect to genders. In the case of academic qualification, participants with a master’s degree qualification reported that pandemic impacted their study hours/day 1.03 (0.55–1.92) times more than those with an M.Phil/Ph.D. Further those with a master’s qualification reported more engaged in social networking than those with an M.Phil./Ph.D. Those having a school education qualification were 0.28 (0.07–1.13) times more likely to be affected compared to those having an M.Phil./Ph.D degree, and the result was statistically significant sleeping hours/day with respect to bachelor qualification only. With reference to medical background participants, the participants having education, humanities, and management background were affected 1.62(0.57–4.62), 2.02(0.65–6.24), and 1.81 (0.54–6.08) times higher in study hours/day, respectively. A significant association existed between sleeping hours/day among the education majors, and social networking among the humanities and education backgrounds as compared to participants of medical background. Whereas the management backgrounded participants were affected 0.46 (0.10–2.21) times higher in sleeping hours/day as compared to medical background.

The effect on sleeping hours per day was found to be 2.3 (1.09–4.86) times greater among the participants from Bagmati Province than from Sudur-Paschim Province. The effect of study hours/day was found to be high among university teachers with AOR = 2.18 (0.97–4.92) and school teachers with AOR = 2.37 (1.13–4.97) as compared to other job holders. However, the AOR was found to be low in social networking among students with AOR = 0.59 (0.18–1.99) and school teachers AOR = 0.91 (0.34–2.45). The social media use time rate (hours/day) was found to be higher as compared to sleeping hours/day with AOR = 1.64 (0.60–4.51) and social networking with AOR = 1.55 (0.43–5.63) among 3–6-hour users with reference to more or equal to 9-hour users (Table 3).

Table 3.

Results of ordinal logistic regression for association of sociodemographic factors with study-related activities in lockdown during COVID-19 pandemic (n = 361).

	Study hours/day	Sleeping hours/day	Social Networking	Concentration
	Odds Ratio (95%CI)	Odds Ratio (95%CI)	Odds Ratio (95%CI)	Odds Ratio (95%CI)
Decrease	0.47 (0.07–3.27)	0.03 (0.01–0.31)*	0.02 (0.00–0.32)*	0.33 (0.05–2.12)
As usual	0.95 (0.14–6.63)	0.13 (0.02–1.17)	0.05 (0.00–0.79)*	0.65 (0.10–4.18)
Gender
Female	0.55 (0.31–0.99)*	1.29 (0.70–2.38)	0.75 (0.35–1.61)	0.84 (0.48–1.47)
Male	Reference	Reference	Reference	Reference
Qualification
School level	0.68 (0.18–2.61)	0.28 (0.07–1.13)	0.42 (0.08–2.24)	0.96 (0.28–3.35)
Bachelor	0.42 (0.18–0.99)*	0.39 (0.16–0.93)*	0.64 (0.22–1.88)	0.65 (0.29–1.48)
Master	1.03 (0.55–1.92)	0.60 (0.33–1.11)	1.94 (0.87–4.35)	0.73 (0.40–1.33)
MPhil/Ph. D.	Reference	Reference	Reference	Reference
Stream
Education	1.62 (0.57–4.62)	0.22 (0.05–0.91)*	0.16 (0.03–0.91)*	1.85 (0.68–5.06)
Science & technology	0.74 (0.27–2.06)	0.27 (0.07–1.09)	0.26 (0.05–1.42)	1.55 (0.59–4.12)
Humanities	2.02 (0.65–6.24)	0.24 (0.06–1.03)	0.10 (0.02–0.64)*	2.02 (0.69–5.91)
Management	1.81 (0.54–6.08)	0.46 (0.10–2.21)	0.23 (0.04–1.57)	0.99 (0.31–3.19)
Medical	Reference	Reference	Reference	Reference
Location of residence
Province 1	0.80 (0.35–1.82)	0.88 (0.40–1.93)	0.64 (0.23–1.82)	0.75 (0.34–1.64)
Province 2	0.76 (0.34–1.69)	1.15 (0.52–2.53)	1.36 (0.47–3.97)	0.74 (0.35–1.58)
Bagmati Province	1.02 (0.50–2.07)	2.30 (1.09–4.86)*	1.69 (0.60–4.78)	0.67 (0.33–1.35)
Gandaki Province	1.36 (0.62–2.97)	1.12 (0.54–2.34)	0.63 (0.24–1.69)	0.73 (0.35–1.52)
Province 5	1.16 (0.55–2.46)	1.76 (0.83–3.74)	0.87 (0.31–2.44)	0.76 (0.37–1.56)
Karnali Province	0.99 (0.40–2.41)	1.75 (0.73–4.19)	0.47 (0.16–1.39)	0.78 (0.33–1.84)
Sudur-Paschim Province	Reference	Reference	Reference	Reference
Job type
University teachers	2.18 (0.97–4.92)	1.54 (0.67–3.54)	1.43 (0.46–4.42)	1.10 (0.50–2.45)
Students	1.67 (0.67–4.17)	1.94 (0.73–5.18)	0.59 (0.18–1.99)	1.00 (0.41–2.43)
School teachers	2.37 (1.13–4.97)*	1.58 (0.74–3.38)	0.91 (0.34–2.45)	1.01 (0.49–2.07)
Others	Reference	Reference	Reference	Reference
Time of using social media
Less than 3 hours	0.70 (0.25–1.95)	1.16 (0.42–3.20)	0.62 (0.17–2.18)	0.87 (0.35–2.12)
3–6 hours	0.67 (0.24–1.84)	1.64 (0.60–4.51)	1.55 (0.43–5.63)	0.72 (0.30–1.73)
6–9 hours	0.60 (0.20–1.84)	1.45 (0.47–4.50)	1.08 (0.26–4.56)	0.80 (0.29–2.18)
More than 9 hours	Reference	Reference	Reference	Reference
Age in years	0.99 (0.96–1.03)	0.97 (0.94–1.01)	1.01 (0.96–1.05)	0.99 (0.96–1.02)
(Scale)	Reference	Reference	Reference	Reference
Model summary	Likelihood Ratio χ2 = 53.93, df = 21, p = 0.00	Likelihood ratio χ2 = 33.91, df = 21, p = 0.04	Likelihood ratio χ2 = 35, df = 21, p = 0.03	Likelihood ratio χ2 = 11, df = 21, p = 0.96

*p-value ≤0.05 (i.e., Significant), CI-confidence interval.

Information on deteriorating academic and extracurricular activities by COVID-19 was measured as binary variables with yes and no categories, and hence, the binary logistic regression analysis was performed. A binary logistic regression was performed on the association of different sociodemographic factors with whether respondents reported a decline in their academic and extracurricular activities. The model consisted of six independent factors: gender, qualification, educational background, location of permanent residence, job type, and hours of using social media. Concerning the effect of these variables on extracurricular activities during the COVID-19 pandemic, the full model containing all predictors was statistically significant, χ² (21, N = 361) = 37.7, p = 0.01 ≤ 0.05 indicating that the model was able to distinguish between the respondents those who reported having an effect and having no effect of COVID-19 on their extracurricular activities. The model as a whole explained between 9.9% (Cox and Snell R²) and 14.3% (Nagelkerke R²) of the variances with effect on extracurricular activities, and it correctly classified 72% of the cases. As shown in Table 4, eleven independent variables made a statistically significant contribution to the model.

Table 4.

Results of binary logistic regression for association of sociodemographic factors with reported deterioration in academic and extracurricular activities during COVID-19 (n = 361).

Sociodemographic Variables	Deterioration in Extracurricular Activities			Deterioration in Academic Activities
	B	Sig.	Odds Ratio (95%CI)	B	Sig.	Odds Ratio (95%CI)
Age in years	−.03	.19	0.98 (0.94–1.01)	−.03	.12	0.97 (0.93–1.01)
Gender	−.26	.48	0.77 (0.38–1.57)	−.33	.37	0.72 (0.35–1.49)
Qualification
MPhil/Ph. D.		.09	Reference		.04*	Reference
School level	−1.26	.11	.29 (0.61–1.33)	1.72	.13	5.56 (0.60–51.51)
Bachelor	−.01	.99	.99 (.34–2.91)	0.86	.11	2.36 (0.83–6.68)
Master	−0.61	.11	.54 (0.26–1.14)	−.24	.48	0.79 (0.41–1.53)
Stream
Medical		.01*	Reference		.90	Reference
Education	1.52	.02*	4.58 (1.30–16.14)	−.17	.81	0.85 (0.22–3.35)
Science & technology	1.19	.05*	3.29 (1.03–10.55)	.10	.89	1.10 (0.29–4.23)
Humanities	2.43	.00*	11.32 (2.79–45.94)	.11	.88	1.12 (0.26–4.74)
Management	1.49	.05*	4.42 (0.99–19.64)	.18	.83	1.20 (0.24–6.09)
Location of residence
Sudur-Paschim Province		.88	Reference		.70	Reference
Province 1	−0.41	.42	0.67 (0.25–1.80)	−.51	.29	0.60 (0.23–1.55)
Province 2	−.31	.53	0.74 (0.28–1.92)	−.64	.18	0.53 (0.21–1.34)
Bagmati Province	−.11	.81	.90 (0.37–2.15)	−.56	.19	0.57 (0.25–1.32)
Gandaki Province	−.31	.50	.73 (0.29–1.82)	−.38	.39	0.68 (0.28–1.64)
Province 5	−.15	.74	.86 (0.35–2.12)	−.76	.09	0.47 (0.19–1.14)
Karnali Province	.35	.53	1.42 (0.47–4.25)	−.16	.76	0.86 (0.31–2.35)
Job type
Others		.03*	Reference		.76	Reference
University teachers	−1.88	.01*	.15 (0.04–0.59)	−.17	.73	0.85 (0.33–2.16)
Students	−1.75	.02*	.17 (0.04–0.71)	−.22	.71	0.80 (0.25–2.59)
School teachers	−1.94	.00*	.14 (0.04–0.53)	.12	.79	1.13 (0.46–2.73)
Time of using social media
≤9 hours/day		.27	Reference		.94	Reference
>3 hours	−1.48	.06	.23 (0.05–1.09)	.10	.86	1.11 (0.36–3.40)
3–6 hours	−.1.52	.05*	.22 (0.05–1.03)	−.07	.90	0.93 (0.31–2.85)
6–9 hours	−1.16	.06	.20 (0.04–1.05)	−.01	.99	1.00 (0.28–3.54)

*p-value ≤0.05 (i.e., Significant), CI-confidence interval.

The participants from a humanity background reported deterioration in their academic activities 11.32 times more OR (95% CI) = 11.32 (2.79–45.94) than participants from a medical background. Additionally, the model was statistically significant (χ² (21, N = 361) = 35.21, p = 0.03 ≤ 0.05), indicating that the model could distinguish between the respondents who reported an effect and no effect of COVID-19 on academic activities. The model explained between 9.3% (Cox and Snell R²) and 13.1% (Nagelkerke R²) of the variances of 71.5% of the cases. The model was significant in only one case. Academic activities deteriorated 5.56 times more among participants with a qualification of school level (i.e., high school diploma), with OR (95% CI) = 5.56 (0.60–51.51) compared to the participants having a qualification of M.Phil./Ph.D. (Table 4).

Discussion

This study aimed to evaluate the academic activities, extracurricular activities, and study-related activities (sleeping hours/day, study hours/day, social networking, and concentration) of academicians during the COVID-19 pandemic and the subsequent nationwide lockdown in Nepal in 2020. Respondents described the prolonged lockdown having a negative impact on their social media usage, as well as academic and extracurricular activities in Nepal. These results are consistent with reports in other countries (OECD, 2020; Farnell et al., 2021). The participants reported an increased level of study-related problems during the lockdown. The strict provisions of lockdown increased sleeping hours and social media networking time. These findings were found consistent with Joshi et al. (2020), Biswas et al. (2021), and Marelli et al. (2021) in the case of sleeping habits. This issue might be a positive consequence of the lockdown because living in a room or home and using social media could be an excellent option to utilize the leisure time for sharing and updating the information. However, respondents also described academic and extracurricular activities as negatively affected by COVID-19. These results were resonated the findings of Koç and Koç (2021), Villani et al. (2021), and Son et al. (2020). Therefore, respondents described the lockdown and COVID-19 as major factors for the deterioration in academic and extracurricular activities in 2020 in Nepal.

The majority of the participants reported that Facebook was the best option for increasing awareness about COVID-19. The reason behind this information could be that the sample was taken from social media users, and Facebook was the most commonly used tool during the pandemic in Nepal. The results showed that the newspaper was less effective in spreading awareness about COVID-19, and it might be the case that several news links and posts could be shared on Facebook. Most social media users followed the links of the newspaper portals through which major news and information from the newspapers were readily available on Facebook pages with the likes and shares of other users.

The decline in academic activities with the age of the respondents was associated with their job roles. This could be linked to the nature of participants’ roles as students or teachers. The participants below 25 years of age, were mostly students, whereas those between 26 and 35 years, were either school or university teachers. Schools and universities were closed during the lockdown period, thus curtailing their academic and extracurricular activities. However, the rate of declination in educational activities was perhaps lower than that predicted by UNESCO (UNESCO IESALC, 2020), where more than 98% of the teachers and students were predicted to be affected by the pandemic.

There were mixed results about the academician’s perception of lockdown and COVID-19 in this study. The results of an independent sample Man Whitney U test revealed that there was a statistically significant difference in the perception of study hours, extracurricular activities, and sleeping hours by gender, but the difference was not statistically significant in the perception of social networking and mental concentration during the lockdown. There were no statistically significant differences by age, qualification, academic stream, job types, location, and duration of using social media with respect to participants’ perception of extracurricular activities. That means people of all age groups, qualifications, and other characteristics responded similarly to questions about the effects of the pandemic and the lockdowns on extracurricular activities due to restrictions on moving and gathering socially.

Researchers and scholars have studied students’ and teachers’ perceptions of COVID-19. For example, Watson (2020) reported that online learning made it harder for students in an Australian school. The students had anxiety that their grades would be impacted, and some students did not have Internet connectivity from their homes. The students felt that they wouldn’t be able to complete their schooling due to the lockdown (Watson, 2020). The findings also revealed that students at higher grade levels were more concerned with the quality of their education during the COVID-19 pandemic (Watson, 2020). However, the teachers reported that COVID-19 taught them the skills to use technology for education in a variety of ways (Watson, 2020).

In another study, Giovannella (2020) found that students had a sense of missing the physical setting of the educational environment and face-to-face pedagogical activities. However, the university students were ready to cope with the situation while adapting to the virtual learning environment in Italy. The students still felt that face-to-face sessions were critical and relevant for many educational activities, and most importantly, for quality interactions and assessments (Giovannella, 2020). However, a majority (56%) of the students in this study preferred a blended learning approach instead of face-to-face instruction (32%) (Giovannella, 2020).

According to the World Bank (2020), the closures of educational institutions (e.g., schools and universities) were “critical pillar of the social distancing tools to mitigate the spread of the disease” (p. 1). The World Bank also reported that the longer lockdown might have an adverse impact on students’ engagement in the learning process. It also might have other social implications, such as a lack of school feeding affect some children, and longer school closures might increase the risk of student dropouts. In this context, the University and College Union (UCU) of the UK also conducted a survey on students’ perception of the COVID-19 pandemic and found that 23% of students were worried about disturbance of pandemic in their learning activities, whereas 49% were worried about its negative impact on their academic activities. A vast majority (71%) of the students were supportive of the view that they preferred to start their university education at a later date so that they would be able to attend face-to-face classes instead of just online teaching-learning (UCU, 2020). In another study, Kurtz and Bushweller (2020) reported that a majority (65%) of academicians agreed to keep educational institutions closed to prevent the spread of the coronavirus, although 35% admitted to resuming the schools. The Kurtz and Bushweller (2020) report also indicated that almost 2/3 of the sample participants were concerned about the adverse impact of COVID-19 on their health implications upon reopening schools and institutions.

The government of Nepal provided a range of support to the schools, universities, and students to continue education despite the lockdowns and closures of face-to-face classes. These included radio and television programs, self-learning packages, and financial assistance (UNICEF, 2021b). However, these efforts were not examined properly to monitor their impacts on actual learning and access to educational resources by the students and teachers (UNICEF, 2021a, b). Both the lockdown and a fear of COVID-19 had severe implications for mental health due to increased anxiety in different parts of the world, including Nepal. The Office of National Statistics in the UK reported increased anxiety levels among married people or people in civil partnerships (The Guardian, 2020). The Guardian further reported that schoolchildren were much affected and troubled by the lockdown, and parents were found worried about their children’s behavioral and emotional problems during the lockdown. Such problems are not unique, but pervasive during the lockdown period in other parts of the world as well (Pate, 2020; Walter, 2020). Although we did not have concomitant results, the findings suggest the students and teachers were highly concerned with the deterioration of academic and extracurricular activities during the COVID-related lockdown in Nepal.

Conclusion

From the results, we have concluded that students and teachers described their academic and extracurricular activities and concentration as negatively affected by COVID-19. However, sleeping time and social media use habits were described as increased by lockdown during the pandemic. Gender, age group, academic qualifications, disciplinary streams, and job types were associated with study hours per day. Gender, academic background, and location of permanent residence were associated with the increased sleeping hours/day during the lockdown period. Additionally, age, gender, qualification, and job type were associated with reported disturbances in academic activities during COVID-19. Study hours/day of university and school teachers were more likely disturbed compared to non-teaching job holders and students Sleeping hours and social networking habits of social media users of less than 4 hours/day were more likely to be affected compared to those using social media for more than 9 hours. The most substantial predictor variable on academic activities was qualification level with reference to the participants' having an M.Phil. or Ph.D. degree.

The study has its own limitations, especially with regards to snowball sampling technique, limited sample size (361), response rate, and self-reported responses of respondents. The snowball sampling was the tool that affected the distribution of online questionnaire to the potential respondents with a chain effect. When a particular academician received the link through social media, such as Facebook, he/she was requested to share the link with their friends. That way there was no control of researchers over the distribution of the questionnaire link among the potential participants. This might have caused a disproportionate sampling of different age groups, qualifications, experiences, and other different demographic characteristics. Additionally, study-related variables are limited to concentration, study and sleeping hours/day, and social networking with a measurement of a three-point rating scale, whereas the effects of academic and extracurricular activities were measured in binary form as yes or no. Due to these limitations, the findings of the study have limited generalizability and transferability to other settings. The data collection took place in April–July 2020. Therefore, the findings could be different in other time. Hence, further study can be carried out considering these limitations. The study currently considered only the people of Nepal; therefore, a further investigation is needed in large samples among different countries. The finding of this may have pedagogical and health-related implications to guide policies and awareness programs to better prepare to deal with crisis in the future to reduce the deleterious effects of lockdown on academic and extracurricular activities.

ORCID iDs

Dirgha R. Joshi https://orcid.org/0000-0002-1437-6661

Jitendra K. Singh https://orcid.org/0000-0002-1387-4642

Bishnu Khanal https://orcid.org/0000-0002-3304-7695

Shashidhar Belbase https://orcid.org/0000-0003-3722-756X