Lockdown Period Of COVID-19 Pandemic Research Articles

Response of PM2.5 chemical composition to the emission reduction and meteorological variation during the COVID-19 lockdown

PM2.5 is a main atmospheric pollutant with various sources and complex chemical compositions, which are influenced by various factors, such as anthropogenic emissions (AE) and meteorological conditions (MC). MC have a significant impacts on variations in atmospheric pollutant; therefore, emission reduction policies and ambient air quality are non-linearly correlated, which hinders the accurate assessment of the effectiveness of control measures. In this study, we conducted online observations of PM2.5 and its chemical composition in Hohhot, China, from December 1, 2019, to February 29, 2020, to investigate how the chemical compositions of PM2.5 respond to the variations in AE and MC. Moreover, the random forest (RF) model was used to quantify the contributions of AE and MC to PM2.5 and its chemical composition during severe hazes and the COVID-19 pandemic lockdown period. During the clean period, MC reduced PM2.5 concentrations by 124%, while MC incresed PM2.5 concentrations by 49% during severe pollution episode. Inorganic aerosols (SO42-, NO3-, and NH4+) showed the strongest response to MC. MC significantly contributed to PM2.5 (36%), SO42- (32%), NO3- (29%), NH4+ (28%), OC (22%), and SOC (17%) levels during pollution episodes. From the pre-lockdown to lockdown period, AE (MC) contributed 52% (48%), 81% (19%), 48% (52%), 68% (32%), 59% (41%), and 288% (-188%) to the PM2.5, SO42-, NO3-, NH4+, OC, and SOC reductions, respectively. The variations in MC (especially the increase in relative humidity) rapidly generated meteorologically sensitive species (SO42-, NO3-, and NH4+), which led to severe winter pollution. This study provides a reference for assessing the net benefits of emission reduction measures for PM2.5 and its chemical compositions.

Profiling Social Sentiment in Times of Health Emergencies with Information from Social Networks and Official Statistics

Social networks and official statistics have become vital sources of information in times of health emergencies. The ability to monitor and profile social sentiment is essential for understanding public perception and response in the context of public health crises, such as the one resulting from the COVID-19 pandemic. This study will explore how social sentiment monitoring and profiling can be conducted using information from social networks and official statistics, and how this combination of data can offer a more complete picture of social dynamics in times of emergency, providing a valuable tool for understanding public perception and guiding a public health response. To this end, a three-layer architecture based on Big Data and Artificial Intelligence is presented: the first layer focuses mainly on collecting, storing, and governing the necessary data such as social media and official statistics; in the second layer, the representation models and machine learning necessary for knowledge generation are built, and in the third layer the previously generated knowledge is adapted for better understanding by crisis managers through visualization techniques among others. Based on this architecture, a KDD (Knowledge Discovery in Databases) framework is implemented using methodological tools such as sentiment analysis, fuzzy 2-tuple linguistic models and time series prediction with the Prophet model. As a practical demonstration of the proposed model, we use tweets as data source (from the social network X, formerly known as Twitter) generated during the COVID-19 pandemic lockdown period in Spain, which are processed to identify the overall sentiment using sentiment analysis techniques and fuzzy linguistic variables, and combined with official statistical indicators for prediction, visualizing the results through dashboards.

COVID-19 pandemic: transformation from physical to virtual classrooms (mediation analysis using PLS-SEM)

PurposeThe purpose of this paper is threefold: first, to examine the influence of the quality of online classes on student satisfaction and student loyalty; second, to explore the mediating role of student participation between online classes and student satisfaction; third, to examine the mediating role of student satisfaction between online classes and student loyalty.Design/methodology/approachThe primary data is collected from the postgraduate students in Jammu and Kashmir, India. A descriptive research design was applied to collect the primary data via Google questionnaire with the COVID-19 pandemic in mind to maintain social distance.FindingsThe result reveals that online classes and student participation positively affect student satisfaction. Student participation is a partial mediator between online classes and student satisfaction, with 0.393 Variance Accounted For (VAF). In comparison, it is a full mediator between online classes and student loyalty with 0.96 VAF.Research limitations/implicationsThe current study was restricted to postgraduate students, while future research could include research scholars, graduate students, and others. Only government institutions in Jammu and Kashmir were employed for the present study. The study may eventually be expanded to include private universities and more states.Practical implicationsThe suggested approach can help teachers, students, policymakers and administrators. The study emphasizes the crucial elements of student engagement and happiness, which must be prioritized to improve online teaching and learning effectiveness and win over students' loyalty.Originality/valueThe study tested the conceptual framework of an integrated approach connecting online classes, student participation, student satisfaction and student loyalty. The study was conducted during the COVID-19 pandemic lockdown period, as it was the need of the hour to come out of such a crisis in the future. The present study can also provide a roadmap for transformation from physical to virtual classrooms.

Effects of parenting style on depressive symptoms, anxiety symptoms, and their comorbidity during the COVID-19 pandemic lockdown among 3117 Chinese junior high school students

IntroductionDepressive symptoms, anxiety symptoms, and comorbidity increased in junior high school students due to the outbreak of COVID-19. The objective of this study was to measure the impacts of parenting style on depressive symptoms, anxiety symptoms, and their comorbidity in Chinese junior high school students during the COVID-19 pandemic lockdown period. MethodsAn online survey was conducted in June 2020 among 3117 junior high school students from Shandong Province, China. The Egna Minnen av Barndoms Uppfostran scale was used to measure parenting styles. The 9-item Patient Health Questionnaire scale and the 7-item Generalized Anxiety Disorder scale were used to measure depressive symptoms and anxiety symptoms, respectively. Multinomial logistic regression was conducted with SPSS 25.0 Version. Results3117 junior school students enrolled in this study. The prevalence of depressive symptoms only, anxiety symptoms only, and comorbidity among junior high school students was 11.55 %, 5.29 %, and 22.97 %. Paternal over-protection was a risk factor not only for depressive symptoms only (OR = 1.075, 95 % CI = 1.020–1.134) but for anxiety symptoms only (OR = 1.090, 95 % CI = 1.016–1.170) and comorbidity (OR = 1.098, 95 % CI = 1.050–1.148). Paternal over-interference was a protective factor for depressive symptoms only (OR = 0.947, 95 % CI = 0.908–0.987) and comorbidity (OR = 0.953, 95 % CI = 0.921–0.986). However, maternal over-interference and over-protection were risk factors for depressive symptoms only (OR = 1.039, 95 % CI = 1.011–1.068). LimitationsThis was a cross-sectional study and the causal inferences could not be conducted. ConclusionsJunior high school students with poorer family environmental factors were more likely to suffer from the comorbidity of anxiety symptoms and depressive symptoms during the COVID-19 pandemic lockdown. Decision-makers from the government, educational, and healthcare institutions should pay more attention to junior high school students at higher risk of mental disorders due to poor parenting styles. We should discuss family interventions in the future to prevent mental disorders in junior high school students.

Hyperparameter Optimization of Regression Model for Electrical Load Forecasting During the COVID-19 Pandemic Lockdown Period

Hyperparameter Optimization of Regression Model for Electrical Load Forecasting During the COVID-19 Pandemic Lockdown Period

Assessment of Land Surface Temperature from the Indian Cities of Ranchi and Dhanbad during COVID-19 Lockdown: Implications on the Urban Climatology

An apparent increase in average global temperature is evident globally, and India is no exception. With the recent decade (2011–2020) arguably being the warmest, significant challenges due to rapid climate change have gained attention. However, notable spatial-temporal changes, especially with regard to land surface temperature (LST), were observed during the COVID-19 pandemic lockdown period, when a comparatively cooler climate was experienced in many urban centers. Assessment of LST, crucial in many heat-balance, land use, and climate change models research studies, depicts the near-surface hotness of the Earth’s temperature at a given location. Thus, this study utilizes satellite remote-sensing data to investigate the spatial-temporal variations of LST pre and post-lockdown imposed during the COVID-19 outbreak. Unlike many existing research studies on the metropolitans of India, the study considers developing Indian cities, Ranchi and Dhanbad, as its study area. Accurate LST computation was performed using existing LANDSAT-8 OLI/TIRS images and judged using other parameters (NDVI, LSE) obtained directly from the thermal infrared bands. The LST assessment successfully estimated temperature variations in Ranchi and Dhanbad, depicting a significant drop in temperature coinciding with the lockdown period and subsequent increase in urban temperature post-pandemic, indicating a meaningful relationship between human activities and urban surface temperature.

Web-based digital applications for training of senior citizens and their caregivers before and after pandemics: A Swot analysis

This would be the first instance where we would be using the online web-based training session for senior citizens and the caregivers to address the commonest health issues like depression, as a result of loneliness arising among the senior citizens during the lockdown period of CoVID-19 pandemic in India and the other issue is caregiver burden, stress and strain due to burnout because of continued caretaking. The article focusses on addressing the mental health issues arising in situations like the global pandemic, of CoVID-19 outbreak, among the senior residents and their caregivers. The lockdown period in India came along with mental health issues, which included depression in elderly with caregiver burnout and strain among the caregiver’s, due to excess caregiving. The above-mentioned health issues could have been addressed during the online training session. The tools involved here, would be web-based applications, conveyed through cell phones using this as a mode of delivery of the online training content, to the participants.

Triage policy to postpone endoscopy for patients with low-risk varices is safe during the lockdown period of COVID-19 pandemic

Background & aimsDuring the COVID-19 pandemic, most of the endoscopic services were electively postponed or suspended. We aimed to assess the safety of a triage policy in patients receiving esophageal variceal ligation during the COVID-19 pandemic.MethodsTriage policy of endoscopic variceal ligation (EVL) was implemented in our hospital during the lockdown period from 15th May 2021 to 26th July 2021. One experienced gastroenterologist reviewed the prior-scheduled list of patients for the EVL prophylaxisprogram. We compared the clinical characteristics and outcomes with those receiving endoscopy due to esophageal varices from 17th May 2020 to 28th July 2020.ResultsOf the 124 patients receiving EVL, a higher percentage of esophageal variceal bleeding (EVB) was noted (9/32, 28.1% vs. 8/92, 8.7%, p = 0.006) during the lockdown period, with a higher percentage of EVB in the referrals (7/9, 77.8% vs. 2/14, 14.2%, p = 0.007). Among patients who received prophylactic EVL, 6 of 78 (7.7%) experienced EVB during the normal period, which is no different to 2 of 23 (8.7%) during the lockdown period. Twenty-three patients whose endoscopies were postponed by triage policy due to low-risk or eradicated varices did not experience EVB during the lockdown period. Child-Turcotte-Pugh (CTP) class C was predictive of EVB (relative risk 8.400, P = 0.033), entering the program of prophylactic EVL was the protective factor of EVB (relative risk 0.016, P = 0.002).ConclusionEntrance into the prophylaxis program does not only decreases risk of EVB but also fosters comprehensive triage to postpone endoscopy during the lockdown period.

Towards a Dignified Death: A New Approach to Care for People Using Substances Who Are at, or Near, the End of Their Lives.

There are no effective intervention studies for people using substances who are at, or near, the end of their lives. The needs of this group of people have been consistently overlooked even within the literature that identifies marginalised groups of people in need of greater recognition in palliative and end-of-life care. The aims of the project were to: (i) determine what a new, co-produced, model of care should look like for people using substances needing palliative and end-of-life care, and (ii) establish whether the new model had the potential to improve people's access to, and experience of, end-of-life care. This paper presents the development of the new approach to care. It was developed using participatory action research principles over a course of online workshops during the COVID-19 pandemic lockdown period in the UK. A theory of change that aims to inform future policy and practice development is presented. While the ambition of the research was stunted by the pandemic, the process of its development and dissemination of the model and its resources has continued. Response from participants highlighted the importance of this work, however, in this new field of policy and practice, preparatory work that engages a wide range of stakeholders is crucial to its success. This relationship building and topic engagement are major parts of implementation before more substantial and sustainable development goals can be met.

Machine Learning-Based Hybrid Ensemble Model Achieving Precision Education for Online Education Amid the Lockdown Period of COVID-19 Pandemic in Pakistan

Institutions of higher learning have made persistent efforts to provide students with a high-quality education. Educational data mining (EDM) enables academic institutions to gain insight into student data in order to extract information for making predictions. COVID-19 represents the most catastrophic pandemic in human history. As a result of the global pandemic, all educational systems were shifted to online learning (OL). Due to issues with accessing the internet, disinterest, and a lack of available tools, online education has proven challenging for many students. Acquiring accurate education has emerged as a major goal for the future of this popular medium of education. Therefore, the focus of this research was to identifying attributes that could help in students’ performance prediction through a generalizable model achieving precision education in online education. The dataset used in this research was compiled from a survey taken primarily during the academic year of COVID-19, which was taken from the perspective of Pakistani university students. Five machine learning (ML) regressors were used in order to train the model, and its results were then analyzed. Comparatively, SVM has outperformed the other methods, yielding 87.5% accuracy, which was the highest of all the models tested. After that, an efficient hybrid ensemble model of machine learning was used to predict student performance using NB, KNN, SVM, decision tree, and logical regression during the COVID-19 period, yielding outclass results. Finally, the accuracy obtained through the hybrid ensemble model was obtained as 98.6%, which demonstrated that the hybrid ensemble learning model has performed better than any other model for predicting the performance of students.

Assessment of Self-Care Methods for Acute Dental Pain Among Adults During COVID-19 Dissemination and the Implementation of Teledentistry in Makkah, Saudi Arabia: A Cross-Sectional Study.

This cross-sectional study aims to explore the prevalence ofacute dental pain, different self-care methods done by adults to manage this pain, and the utilization of teledental platformsduring the COVID-19 pandemic lockdown period. The study was conducted in Makkah, Saudi Arabia. A total of 727 participants answered the study questionnaire, which was distributed as an online survey on different social media platforms. The modified dental pain screening questionnaire (M-DePaQ) was used to obtain dental pain-related characteristics of subjects. Also, self-care and formal-care strategies for pain relief questionnaire for most recent toothache and additional questions developed by the authors related to virtual clinics were used to determine the need for implementation of teledentistry and remote dental consultations. Data was entered in SPSS (IBM Corp., Armonk, NY) and analyzed using descriptive statistics, chi-square test, and binary logistic regression. Around 39% out of 727 participants experienced dental pain during the COVID-19 Makkah city lockdown; 58%of them reported that the pain was related to a tooth.The majority reported that it was exaggerated with coldbeverages and foods [67.1%]. A chi-square association test showed that the age group between 20-30 significantly used the Sehaty(Lean, Riyadh, Saudi Arabia) application more than other age groups. Additionally, women were notably found to use home remedies more frequently than men. Furthermore, individuals with a bachelor's degree believed more in the importance of having a virtual dental clinic during the periods of lockdown. During the COVID-19 pandemic, acute dental pain and self-medication were found common among this study population.The practice of self-medication was also documentedfrequently, therefore, it is important to educate the general population on the proper way to manage dental pain. However, The use of teledentistry services was found uncommon, so to improve patient care especially when accessibility to professional treatment is difficult, the implementation of teledental services need to be considered.

The relation between alexithymia, eating attitude, and sleep pattern among university students during the lockdown period of COVID-19 pandemic

The relation between alexithymia, eating attitude, and sleep pattern among university students during the lockdown period of COVID-19 pandemic

Resilience to COVID-19 challenges: Lessons for school psychologists serving school-attending black South African youth aged 10 to 19 years old.

Several studies have highlighted the mental health challenges of children and youth during the COVID-19 pandemic lockdown period, especially, in relation to an escalation of depression, anxiety, and stress. Whilst this may be the reality, it is unfortunate that most of the studies adopt a psychopathological point of departure often portraying doom and gloom. Adopting a social ecological resilience perspective the author focuses on the resilience of school-attending black South African youth during the COVID-19 lockdown period. The Child and Youth Resilience Measurement (CYRM-28) was completed by 4165 respondents in grades 4 to 12 (females = 2431, 58.4%; males = 1734, 41.6%) from the Gauteng, Mpumalanga and North-West provinces in South Africa. The findings indicate that school psychologists must consider gender, age and school levels when they design school-based resilience programmes for black South African children. Particular emphasis should be placed on contextual resilience highlighting spiritual, religious, cultural and educational factors. A major lesson for school psychologists is to ensure that school-based resiliency programmes adopt a whole school approach that includes children, their families and local communities for the successful promotion of resilience during adverse situations as postulated by the social ecological resilience model.

How Lifestyle Changes during the COVID-19 Global Pandemic Affected the Pattern and Symptoms of the Menstrual Cycle.

This research investigated the implications that the COVID-19 pandemic had on the menstrual cycle and any contributing factors to these changes. A questionnaire was completed by 559 eumenorrheic participants, capturing detail on menstrual cycle symptoms and characteristics prior to and during the COVID-19 pandemic lockdown period. Over half of all participants reported to have experienced lack of motivation (61.5%), focus (54.7%) and concentration (57.8%). 52.8% of participants reported an increase in cycle length. Specifically, there was an increase in the median cycle length reported of 5 days (minimum 2 days, maximum 32 days), with a median decrease of 3 days (minimum 2 days and maximum 17 days). A lack of focus was significantly associated with a change in menstrual cycle length (p = 0.038) reported to have increased by 61% of participants. Changes to eating patterns of white meat (increase p = 0.035, decrease p = 0.003) and processed meat (increase p = 0.002 and decrease p = 0.001) were significantly associated with a change in menstrual cycle length. It is important that females and practitioners become aware of implications of environmental stressors and the possible long-term effects on fertility. Future research should continue to investigate any long-lasting changes in symptoms, as well as providing education and support for females undergoing any life stressors that may implicate their menstrual cycle and/or symptoms.

The Association between COVID-19 Pandemic and the Quality of Life of Medical Students in Silesian Voivodeship, Poland.

(1) Background: Since the COVID-19 pandemic spread rapidly in 2020, medical universities have been affected by a particular crisis. Due to the increased risk of SARS CoV-2 transmission, the authorities of medical faculties all over the world, including Poland, started to minimize direct contact between students. The objective of the paper is to identify and assess determinants of the quality of life among medical students in Poland before and during the COVID-19 pandemic. (2) Methods: We analyzed data obtained in a cross-sectional study performed among three groups of students tested in three consecutive research periods: period before the COVID-19 pandemic, the COVID-19 pandemic lockdown period and the COVID-19 pandemic period following lockdown. (3) Results: The total number of participants was 1098. We identified that the research period before the COVID-19 pandemic was the risk factor for lower quality of life in terms of the somatic and environmental domains. It was also confirmed that determinants such as poor financial situation, low frequency of physical activity and bad self-declared health status harmed the QoL scores in all domains. (4) Conclusions: The obtained results confirmed that better financial situation, higher physical activity and better self-declared health status were statistically significant factors improving the quality of life of first-year medical students in Poland. The findings of our study also showed that the declared somatic and environmental domains of QoL among medical students were better during the COVID-19 pandemic period. Our observations confirmed that the immediate implementation of e-learning could protect against the deterioration of mental health and quality of life in first-year medical students during possible future epidemic crises.

Predicting behavioural intention among graduate students in emergency remote teaching: evidence from a transition country

Emergency remote teaching (ERT) is a new concept that describes the context in which instructional delivery is switched entirely online due to crisis circumstances. Recent research in such a context has been focused either on exploring the unique learning environment and enabling factors or on instructors’ intended behavior, with few studies exploring the students’ perspective. This study aims to contribute to the literature on technology-mediated teaching and learning by deepening the knowledge of the factors determining students’ behavioral intentions (BI) in ERT settings, using a survey of 487 graduate students attending public and non-public universities in Albania conducted during the COVID-19 pandemic lockdown period. The Technology Acceptance Model (TAM) was employed to explore the chain relationship between ease of use (EASYUSE), expected efficiency (EE), attitudes (ATT), and BI. We expand the TAM model and increase its explanatory power by introducing new variables, such as co-presence (CP), and emergent variables, such as lack of learning materials and time constraints. Variance-based partial least squares techniques were used to validate our conceptual model. As hypothesized, EE and EASYUSE have a direct, positive effect on BI and an indirect effect via ATT. CP does not influence the BI directly but only indirectly via ATT and EE. Finally, the lack of learning materials is shown to negatively affect EE. While some of the findings have limited generalizability the specific research setting provides a unique opportunity to investigate the critical role of interactive teaching methods and learning barriers on students’ intentions and ATT. The fresh insights gained from the extended TAM model have important implications concerning the effective and systematic use of online modalities in similar settings.Supplementary InformationThe online version of this article (10.1007/s40692-022-00239-7) contains supplementary material, which is available to authorized users.

The Impact of COVID-19 Pandemic on Ischemic Stroke Patients in a Comprehensive Hospital.

PurposeThis study aimed to investigate the impact of characteristic ischemic stroke and outcomes during the first COVID-19 pandemic lockdown.Patients and MethodsA retrospective, observational cohort study of a comprehensive tertiary stroke center was conducted. Patients with ischemic stroke were divided into pre-COVID-19 lockdown (11/1/2019 to 1/30/2020) and COVID-19 lockdown (1/31/2020 to 4/30/2020) period groups. Patient data on stroke admission, thrombolysis, endovascular treatment, and 3-month routine follow-up were recorded. Data analysis was performed using SPSS according to values following a Gaussian distribution.ResultsThe pre-COVID-19 lockdown period group comprised 230 patients compared to 215 patients in the COVID-19 lockdown period group. Atrial fibrillation was more predominant in the COVID-19 lockdown period group (11.68% vs 5.65%, p=0.02) alongside patients who were currently smoking (38.8% vs 28.7%, p=0.02) and drinking alcohol (30.37% vs 20.00%, p=0.012) compared with that of the pre-COVID-19 lockdown period group. For patients receiving thrombolysis, the median door-to-CT time was longer in the COVID-19 lockdown period group (17.0 min (13.0, 24.0) vs 12.0 min (8.0, 17.3), p=0.012), median door to needle time was 48.0 minutes (35.5, 73.0) vs 43.5 minutes (38.0, 53.3), p=0.50, compared with that of the pre-COVID-19 lockdown period group. There were no differences for patients receiving mechanical thrombectomy. The median length of hospitalization (IQR) was no different. Discharge mRS scores (IQR) were higher in the COVID-19 lockdown period group (1.0 (1.0, 3.0) vs 1.0 (1.0, 2.0), p=0.022). Compared with the pre-COVID-19 lockdown period, hospitalization cost (Chinese Yuan) in the COVID-19 period group was higher (13,445.7 (11,009.7, 20,030.5) vs 10,799.2 (8692.4, 16,381.7), p=0.000). There was no difference observed in 3-month mRS scores.ConclusionPatients presenting with ischemic stroke during the COVID-19 pandemic lockdown period had longer median door-to-CT time and higher hospitalization costs. There were no significant differences in 3-month outcomes. Multidisciplinary collaboration and continuous workflow optimization may maintain stroke care during the COVID-19 pandemic lockdown.

Analyzing historical and future acute neurosurgical demand using an AI-enabled predictive dashboard

Characterizing acute service demand is critical for neurosurgery and other emergency-dominant specialties in order to dynamically distribute resources and ensure timely access to treatment. This is especially important in the post-Covid 19 pandemic period, when healthcare centers are grappling with a record backlog of pending surgical procedures and rising acute referral numbers. Healthcare dashboards are well-placed to analyze this data, making key information about service and clinical outcomes available to staff in an easy-to-understand format. However, they typically provide insights based on inference rather than prediction, limiting their operational utility. We retrospectively analyzed and prospectively forecasted acute neurosurgical referrals, based on 10,033 referrals made to a large volume tertiary neurosciences center in London, U.K., from the start of the Covid-19 pandemic lockdown period until October 2021 through the use of a novel AI-enabled predictive dashboard. As anticipated, weekly referral volumes significantly increased during this period, largely owing to an increase in spinal referrals (p < 0.05). Applying validated time-series forecasting methods, we found that referrals were projected to increase beyond this time-point, with Prophet demonstrating the best test and computational performance. Using a mixed-methods approach, we determined that a dashboard approach was usable, feasible, and acceptable among key stakeholders.

Using Bloom's Digital Taxonomy as a framework to evaluate webcast learning experience in the context of Covid-19 pandemic.

Distance education has been the concern of educational institutions nowadays due to COVID 19 pandemic. The purpose of this study which was carried out during COVID-19 pandemic lockdown period in 2020 was to evaluate the effectiveness of webcast applications on teacher training. Since it was a sudden and an unpredicted transition from face-to-face education to webcast education, it was crucial to evaluate the outcome of teaching applications in order to compensate for the missing points in education. The evaluation framework in this study was based on Bloom’s Digital Taxonomy. The participants’ responses demonstrated that as a consequence of the webcast application in education, remembering, understanding, and analyzing skills were activated better than applying, evaluating, and creating thinking skills in the digital taxonomy. The findings would not be applicable to all webcast training but only to the course design that was delivered as an emergency remote course in a global pandemic.

Factors Associated with Smartphone Addiction during COVID-19 Pandemic Lockdown in Students of Faculty of Medicine in North Sumatera

Introduction: The popularity of cell phones among the younger generation has increased rapidly in a short period leading to the high prevalence of smartphone addiction among adolescents worldwide, especially during the Covid-19 pandemic lockdown period. This study aimed to investigate the factors associated with smartphone addiction measured by the Indonesian version of the Smartphone Addiction Scale-Short version (SAS-SV) score in both preclinical and clerkship students. Methods: A cross-sectional study was conducted from November 2020 to December 2020 in preclinical and clerkship students of the Faculty of Medicine from the Universitas Sumatera Utara, North Sumatra Islamic University, Hospital of North Sumatra University, and Hospital of Haji Medan academic year of 2019-2020. The Indonesian version of the SAS-SV questionnaire was distributed to the study subjects through Google Form. Results: Bivariate analysis showed all variables to be significantly associated with SAS-SV score (all p values were &lt;0.05). Meanwhile, multivariate analysis showed all variables but the type of smartphone and the closest family members to be significantly associated with the SAS- SV score. Conclusion: Age, gender, education level, monthly income, duration of smartphone use, sleep duration, parental educational background, monthly internet costs, and other uses of smartphones were found to be associated with smartphone addiction as measured by the Indonesian version of the SAS-SV score. Meanwhile, the type of smartphone and the closest family members were not associated with smartphone addiction as measured by the Indonesian version of the SAS-SV score.