The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Impact of the COVID-19 pandemic on medical education: Medical students’ knowledge, attitudes, and practices regarding electronic learning
Open accessAbstract
The Coronavirus Disease 2019 (COVID-19) pandemic has caused an unprecedented disruption in medical education and healthcare systems worldwide. The disease can cause life-threatening conditions and it presents challenges for medical education, as instructors must deliver lectures safely, while ensuring the integrity and continuity of the medical education process. It is therefore important to assess the usability of online learning methods, and to determine their feasibility and adequacy for medical students. We aimed to provide an overview of the situation experienced by medical students during the COVID-19 pandemic, and to determine the knowledge, attitudes, and practices of medical students regarding electronic medical education. A cross-sectional survey was conducted with medical students from more than 13 medical schools in Libya. A paper-based and online survey was conducted using email and social media. The survey requested demographic and socioeconomic information, as well as information related to medical online learning and electronic devices; medical education status during the COVID-19 pandemic; mental health assessments; and e-learning knowledge, attitudes, and practices. A total of 3,348 valid questionnaires were retrieved. Most respondents (64.7%) disagreed that e-learning could be implemented easily in Libya. While 54.1% of the respondents agreed that interactive discussion is achievable by means of e-learning. However, only 21.1% agreed that e-learning could be used for clinical aspects, as compared with 54.8% who disagreed with this statement and 24% who were neutral. Only 27.7% of the respondents had participated in online medical educational programs during the COVID-19 pandemic, while 65% reported using the internet for participating in study groups and discussions. There is no vaccine for COVID-19 yet. As such, the pandemic will undeniably continue to disrupt medical education and training. As we face the prospect of a second wave of virus transmission, we must take certain measures and make changes to minimize the effects of the COVID-19 outbreak on medical education and on the progression of training. The time for change is now, and there should be support and enthusiasm for providing valid solutions to reduce this disruption, such as online training and virtual clinical experience. These measures could then be followed by hands-on experience that is provided in a safe environment.
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Cites
A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7
Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006) · Archives of Internal Medicine · doi:10.1001/archinte.166.10.1092 · Cited by 31,765
An interactive web-based dashboard to track COVID-19 in real time
Dong, E., Du, H., & Gardner, L. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30120-1 · Cited by 10,048
Spitzer, R. L. (1999) · JAMA · doi:10.1001/jama.282.18.1737 · Cited by 9,802 · cited 1×
“This tool has been validated in a previous study [15].”
MethodThe psychological impact of the COVID-19 epidemic on college students in China
Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020) · Psychiatry Research · doi:10.1016/j.psychres.2020.112934 · Cited by 5,843
Virtually perfect? Telemedicine for COVID-19
Hollander, J. E., & Carr, B. G. (2020) · New England Journal of Medicine · doi:10.1056/nejmp2003539 · Cited by 2,970
Utility of a new procedure for diagnosing mental disorders in primary care. The PRIME-MD 1000 study
Spitzer, R. L. (1994) · JAMA · doi:10.1001/jama.272.22.1749 · Cited by 2,635
Utility of a New Procedure for Diagnosing Mental Disorders in Primary Care: The PRIME-MD 1000 Study
Spitzer, R. L. (1994) · JAMA · doi:10.1001/jama.1994.03520220043029 · Cited by 1,873
Validation of PHQ-2 and PHQ-9 to Screen for Major Depression in the Primary Care Population
Arroll, B., Goodyear-Smith, F., Crengle, S., Gunn, J., Kerse, N., Fishman, T., Falloon, K., & Hatcher, S. (2010) · The Annals of Family Medicine · doi:10.1370/afm.1139 · Cited by 1,279 · cited 1×
“A score of 3 indicates high sensitivity in the depressed individual [16].”
BackgroundBarriers and solutions to online learning in medical education – an integrative review
O’Doherty, D., Dromey, M., Lougheed, J., Hannigan, A., Last, J., & McGrath, D. (2018) · BMC Medical Education · doi:10.1186/s12909-018-1240-0 · Cited by 1,032
The Global Prevalence of Anxiety Among Medical Students: A Meta-Analysis
Tian-Ci Quek, T., Wai-San Tam, W., X. Tran, B., Zhang, M., Zhang, Z., Su-Hui Ho, C., & Chun-Man Ho, R. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph16152735 · Cited by 990 · cited 1×
“8% of them experienced anxiety symptoms when the results were pooled [24].”
Background
Cited by
Using ChatGPT for medical education: the technical perspective
Chan, K. Y., Yuen, T. H., & Co, M. (2025) · BMC Medical Education · doi:10.1186/s12909-025-06785-9 · Cited by 34
Co, M., John Yuen, T. H., & Cheung, H. H. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e09751 · Cited by 31
Elnour, A. A., Abou Hajal, A., Goaddar, R., Elsharkawy, N., Mousa, S., Dabbagh, N., Mohamad Al Qahtani, M., Al Balooshi, S., Othman Al Damook, N., & Sadeq, A. (2023) · Saudi Pharmaceutical Journal · doi:10.1016/j.jsps.2023.05.024 · Cited by 12
Deng, H., Jiang, Y., Han, Q., Zhou, X., Zhong, S., Hu, K., & Yang, L. (2023) · BMC Medical Education · doi:10.1186/s12909-023-04193-5 · Cited by 11
Metadata
- Authors
- Alsoufi, A., Alsuyihili, A., Msherghi, A., Elhadi, A., Atiyah, H., Ashini, A., Ashwieb, A., Ghula, M., Ben Hasan, H., Abudabuos, S., Alameen, H., Abokhdhir, T., Anaiba, M., Nagib, T., Shuwayyah, A., Benothman, R., Arrefae, G., Alkhwayildi, A., Alhadi, A., Zaid, A., & Elhadi, M.
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2020-11-25
- Volume
- 15
- Issue
- 11
- Pages
- e0242905
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W3108215075
- Cited by
- 747
- References
- 32
- FWCI
- 100.85
- Type
- journal article
- Language
- en
- Open access
- gold
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- Alsoufi, A., Alsuyihili, A., Msherghi, A., Elhadi, A., Atiyah, H., Ashini, A., Ashwieb, A., Ghula, M., Ben Hasan, H., Abudabuos, S., Alameen, H., Abokhdhir, T., Anaiba, M., Nagib, T., Shuwayyah, A., Benothman, R., Arrefae, G., Alkhwayildi, A., Alhadi, A., . . . Elhadi, M. (2020). Impact of the COVID-19 pandemic on medical education: Medical students’ knowledge, attitudes, and practices regarding electronic learning. PLOS ONE. https://doi.org/10.1371/journal.pone.0242905
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.