Investigating patients’ intention to continue using teleconsultation to anticipate postcrisis momentum: survey study
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Abstract
Background: The COVID-19 crisis has drastically changed care delivery with teleconsultation platforms experiencing substantial spikes in demand, helping patients and care providers avoid infections and maintain health care services. Beyond the current pandemic, teleconsultation is considered a significant opportunity to address persistent health system challenges, including accessibility, continuity, and cost of care, while ensuring quality. Objective: This study aims at identifying the determinants of patients’ intention to continue using a teleconsultation platform. It extends prior research on information technology use continuance intention and teleconsultation services. Methods: Data was collected in November 2018 and May 2019 with Canadian patients who had access to a teleconsultation platform. Measures included patients’ intention to continue their use; teleconsultation usefulness; teleconsultation quality; patients’ trust toward the digital platform, its provider. and health care professionals; and confirmation of patients’ expectations toward teleconsultation. We used structural equation modeling employing the partial least squares component-based technique to test our research model and hypotheses. Results: We analyzed a sample of 178 participants who had used teleconsultation services. Our findings revealed that confirmation of expectations had the greatest influence on continuance intention (total effects=0.722; P<.001), followed by usefulness (total effects=0.587; P<.001) and quality (total effects=0.511; P<.001). Usefulness (β=.60; P<.001) and quality (β=.34; P=.01) had direct effects on the dependent variable. The confirmation of expectations had direct effects both on usefulness (β=.56; P<.001) and quality (β=.75; P<.001) in addition to having an indirect effect on usefulness (indirect effects=0.282; P<.001). Last, quality directly influenced usefulness (β=.34; P=.002) and trust (β=.88; P<.001). Trust does not play a role in the context under study. Conclusions: Teleconsultation is central to care going forward, and it represents a significant lever for an improved, digital delivery of health care in the future. We believe that our findings will help drive long-term teleconsultation adoption and use, including in the aftermath of the current COVID-19 crisis, so that general care improvement and greater preparedness for exceptional situations can be achieved.
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The heightened interest in telehealth and AI education at t1 could be attributed to the rise of telemedicine during the COVID-19 pandemic and the increasing prominence of generative AI tools such as ChatGPT.
“The heightened interest in telehealth and AI education at t1 could be attributed to the rise of telemedicine during the COVID-19 pandemic [39] and the increasing prominence of generative AI tools such as ChatGPT [40].”
From Evolving Medical Students’ Digital Health Perceptions and Intentions: Insights From a Prepandemic and Postpandemic Survey Study (2025) · cites this paper as [39]
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Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,588 · see citing works
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194 · see citing works
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
Statistical Power Analysis for the Behavioral Sciences
Cohen, J. (2013) · doi:10.4324/9780203771587 · Cited by 25,373 · see citing works
The DeLone and McLean Model of Information Systems Success: A Ten-Year Update
(2003) · Journal of Management Information Systems · doi:10.1080/07421222.2003.11045748 · Cited by 11,791 · see citing works
An integrative model of organizational trust
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995) · The Academy of Management Review · doi:10.2307/258792 · Cited by 10,736 · see citing works
Information Systems Success: The Quest for the Dependent Variable
DeLone, W. H., & McLean, E. R. (1992) · Information Systems Research · doi:10.1287/isre.3.1.60 · Cited by 10,697 · see citing works
Understanding Information Systems Continuance: An Expectation-Confirmation Model1
Bhattacherjee, A. (2001) · MIS Quarterly · doi:10.2307/3250921 · Cited by 8,767 · see citing works
Accounting for common method variance in cross-sectional research designs
Lindell, M. K., & Whitney, D. J. (2001) · Journal of Applied Psychology · doi:10.1037/0021-9010.86.1.114 · Cited by 8,490 · see citing works
Using pls path modeling in new technology research: updated guidelines
Henseler, J., Hubona, G., & Ray, P. A. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-09-2015-0382 · Cited by 7,173 · see citing works
Texas A&M International University, Kock, N., Lynn, G., & Stevens Institute of Technology (2012) · Journal of the Association for Information Systems · doi:10.17705/1jais.00302 · Cited by 3,783 · see citing works
Diamantopoulos, A., & Siguaw, J. A. (2006) · British Journal of Management · doi:10.1111/j.1467-8551.2006.00500.x · Cited by 3,410 · cited 1× · see citing works
“One must first note in this regard that a single research construct, namely, the quality of the medical teleconsultation, is modeled as being formative due to the composite and multidimensional nature of its conceptualization [44], whereas the other four constructs are reflective [45].”
BackgroundPavlou, P. A., Liang, H., & Xue, Y. (2007) · MIS Quarterly · doi:10.2307/25148783 · Cited by 2,646 · see citing works
Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012) · MIS Quarterly · doi:10.2307/41410402 · Cited by 2,184 · see citing works
Gefen, D., & Straub, D. W. (2004) · Omega · doi:10.1016/j.omega.2004.01.006 · Cited by 2,025 · see citing works
MACKENZIE, S. B., Podsakoff, P. M., & Jarvis, C. B. (2005) · Journal of Applied Psychology · doi:10.1037/0021-9010.90.4.710 · Cited by 1,685 · see citing works
Gefen (2011) · doi:10.2307/23044042 · Cited by 1,596 · see citing works
Covid-19 and Health Care’s Digital Revolution
Keesara, S., Jonas, A., & Schulman, K. (2020) · New England Journal of Medicine · doi:10.1056/nejmp2005835 · Cited by 1,126 · see citing works
Hong, S., Thong, J. Y. L., & Tam, K. Y. (2006) · Decision Support Systems · doi:10.1016/j.dss.2006.03.009 · Cited by 955 · see citing works
A Hierarchical Model of Health Service Quality
Dagger, T. S., Sweeney, J., & Johnson, L. W. (2007) · Journal of Service Research · doi:10.1177/1094670507309594 · Cited by 776 · see citing works
Telemedicine and the COVID-19 Pandemic, Lessons for the Future
Bashshur, R., Doarn, C. R., Frenk, J. M., Kvedar, J. C., & Woolliscroft, J. O. (2020) · Telemedicine and e-Health · doi:10.1089/tmj.2020.29040.rb · Cited by 642 · see citing works
A Framework and Guidelines for Context-Specific Theorizing in Information Systems Research
Hong, W., Chan, F. K. Y., Thong, J. Y. L., Chasalow, L. C., & Dhillon, G. (2014) · Information Systems Research · doi:10.1287/isre.2013.0501 · Cited by 609 · see citing works
Determinants of continuance intention to use the smartphone banking services
Susanto, A., Chang, Y., & Ha, Y. (2016) · Industrial Management & Data Systems · doi:10.1108/imds-05-2015-0195 · Cited by 443 · see citing works
How Socioeconomic Status Affects Patient Perceptions of Health Care: A Qualitative Study.
Arpey, N. C., Gaglioti, A. H., & Rosenbaum, M. E. (2017) · Journal of Primary Care & Community Health · doi:10.1177/2150131917697439 · Cited by 413 · see citing works
Greenhalgh, T., Shaw, S., Wherton, J., Vijayaraghavan, S., Morris, J., Bhattacharya, S., Hanson, P., Campbell-Richards, D., Ramoutar, S., Collard, A., et al. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9897 · Cited by 371 · see citing works
Privacy and Security in Mobile Health Apps: A Review and Recommendations
Martínez-Pérez, B., Díez, I. D. L. T., & López-Coronado, M. (2014) · Journal of Medical Systems · doi:10.1007/s10916-014-0181-3 · Cited by 350 · see citing works
A unified model of IT continuance: Three complementary perspectives and crossover effects
Bhattacherjee, A., & Lin, C.-P. (2015) · European Journal of Information Systems · doi:10.1057/ejis.2013.36 · Cited by 336 · see citing works
Demiris, G., Afrin, L. B., Speedie, S. M., Courtney, K. L., Sondhi, M. M., Vimarlund, V., Lovis, C., Goossen, W. T. F., & Lynch, C. (2007) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2492 · Cited by 310 · see citing works
Jacob, C., Sanchez-Vazquez, A., & Ivory, C. (2020) · JMIR mHealth and uHealth · doi:10.2196/15935 · Cited by 292 · see citing works
Conceptualizing and testing formative constructs
Roberts, N., & Thatcher, J. B. (2009) · ACM SIGMIS Database the DATABASE for Advances in Information Systems · doi:10.1145/1592401.1592405 · Cited by 290 · see citing works
The impact of post-adoption beliefs on the continued use of health apps
Cho, J. (2015) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2015.12.016 · Cited by 277 · see citing works
The Use Of Telemedicine By Physicians: Still The Exception Rather Than The Rule
Kane, C. K., & Gillis, K. D. (2018) · Health Affairs · doi:10.1377/hlthaff.2018.05077 · Cited by 268 · see citing works
Covid-19: A&E visits in England fall by 25% in week after lockdown
Thornton, J. (2020) · BMJ · doi:10.1136/bmj.m1401 · Cited by 268 · see citing works
Wu, J., & Lu, X. (2013) · Journal of the Association for Information Systems · doi:10.17705/1jais.00325 · Cited by 255 · see citing works
Evaluating Effect, Composite, and Causal Indicators in Structural Equation Models1
Bollen, K. A. (2011) · MIS Quarterly · doi:10.2307/23044047 · Cited by 239 · see citing works
Service quality of mHealth platforms: development and validation of a hierarchical model using PLS
Akter, S., D’Ambra, J. D., & RAY, P. K. (2010) · Electronic Markets · doi:10.1007/s12525-010-0043-x · Cited by 209 · see citing works
Continuance of mHealth services at the bottom of the pyramid: the roles of service quality and trust
Akter, S., RAY, P. K., & D’Ambra, J. D. (2012) · Electronic Markets · doi:10.1007/s12525-012-0091-5 · Cited by 181 · see citing works
Electronic Consultation in Primary Care Between Providers and Patients: Systematic Review
Mold, F., Hendy, J., Lai, Y.-L., & de Lusignan, S. (2019) · JMIR Medical Informatics · doi:10.2196/13042 · Cited by 181 · see citing works
Templier, M., & Paré, G. (2018) · European Journal of Information Systems · doi:10.1080/0960085x.2017.1398880 · Cited by 180 · see citing works
Telemedicine During the COVID-19 in Italy: A Missed Opportunity?
Omboni, S. (2020) · Telemedicine and e-Health · doi:10.1089/tmj.2020.0106 · Cited by 148 · see citing works
Chen, Y., Yang, L., Zhang, M., & Yang, J. (2018) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2018.04.008 · Cited by 131 · see citing works
Virtual Visits for Acute, Nonurgent Care: A Claims Analysis of Episode-Level Utilization
Gordon, A. S., Adamson, W., & DEVRIES, A. R. (2017) · Journal of Medical Internet Research · doi:10.2196/jmir.6783 · Cited by 120 · see citing works
Examining customers’ continuance intentions towards internet banking usage
Ofori, K. S., Boateng, H., Okoe, A. F., & Gvozdanović, I. (2017) · Marketing Intelligence & Planning · doi:10.1108/mip-11-2016-0214 · Cited by 116 · see citing works
Interpreting COVID-19 and Virtual Care Trends: Cohort Study
Khairat, S., Meng, C., Xu, Y., Edson, B. S., & Gianforcaro, R. (2020) · JMIR Public Health and Surveillance · doi:10.2196/18811 · Cited by 114 · see citing works
Diffusion of the Digital Health Self-Tracking Movement in Canada: Results of a National Survey
Paré, G., Leaver, C. A., & Bourget, C. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9388 · Cited by 113 · see citing works
Belanche, D., Casaló, L. V., & Pérez-Rueda, A. (2015) · Government Information Quarterly · doi:10.1016/j.giq.2014.12.004 · Cited by 112 · see citing works
Impediments to mobile shopping continued usage intention: A trust-risk-relationship
Groß, M. (2016) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2016.08.013 · Cited by 104 · see citing works
Information Technology Continuance Intention
Nabavi, A., Taghavifard, M. T., Hanafizadeh, P., & Taghva, M. R. (2016) · International Journal of E-Business Research · doi:10.4018/ijebr.2016010104 · Cited by 96 · see citing works
Testing Mediation in Structural Equation Modeling
Leth‐Steensen, C., & Gallitto, E. (2015) · Educational and Psychological Measurement · doi:10.1177/0013164415593777 · Cited by 95 · see citing works
The use of patient-facing teleconsultations in the national health service: scoping review
O'Cathail, M., Sivanandan, M. A., Diver, C., Patel, P., & Christian, J. (2020) · JMIR Medical Informatics · doi:10.2196/15380 · Cited by 86 · see citing works
Teleconsulta: uma Revisão Integrativa da Interação Médico-Paciente Mediada pela Tecnologia
Catapan, S. D. C., & Calvo, M. C. M. (2020) · Revista Brasileira de Educação Médica · doi:10.1590/1981-5271v44.1-20190224.ing · Cited by 77 · see citing works
Factors Associated with the Use of a Teleconsultation System in Brazilian Primary Care
Alkmim, M. B. M., Marcolino, M. S., Figueira, R. M., Sousa, L., Nunes, M. S., Cardoso, C. S., & Ribeiro, A. L. (2015) · Telemedicine and e-Health · doi:10.1089/tmj.2014.0112 · Cited by 51 · see citing works
Assessing m-Health success in Bangladesh
Hossain, M. A. (2016) · Journal of Enterprise Information Management · doi:10.1108/jeim-02-2014-0013 · Cited by 50 · see citing works
The distinct roles of dedication-based and constraint-based mechanisms in social networking sites
Kim, B., & Min, J.-Y. (2015) · Internet Research · doi:10.1108/intr-11-2013-0253 · Cited by 49 · see citing works
Software, C., Forsgren, N., Durcikova, A., Clay, P. F., & Wang, X. (2016) · Communications of the Association for Information Systems · doi:10.17705/1cais.03839 · Cited by 44 · see citing works
Video Consultation Use by Australian General Practitioners: Video Vignette Study
Jiwa, M., & Meng, X. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2638 · Cited by 37 · see citing works
Li, J., Liu, M., Liu, X., & Ma, L. (2017) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2016.0268 · Cited by 34 · see citing works
Trust and online consumer health service success
Mou, J., & Cohen, J. F. (2016) · Information Development · doi:10.1177/0266666916642507 · Cited by 27 · see citing works
Teleoncology for children with cancer: A scoping review on applications and outcomes
Kermani, F., Orooji, A., & Sheikhtaheri, A. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104118 · Cited by 21 · see citing works
Operationalizing Virtual Visits During a Public Health Emergency.
Magoon, V. (2021) · PubMed · Cited by 11 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Wu, C., Zhou, Y., Wang, R., Huang, S., & Yuan, Q. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.121449 · Cited by 93 · see citing works
Wang, T., Wang, W., Liang, J., Nuo, M., Wen, Q., Wei, W., Han, H., & Lei, J. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00692-9 · Cited by 84 · see citing works
Amin, R., Hossain, M. A., Uddin, M. M., Jony, M. T. I., & Kim, M. (2022) · Healthcare · doi:10.3390/healthcare10071327 · Cited by 43 · see citing works
Understanding Adherence to Digital Health Technologies: Systematic Review of Predictive Factors
Figueiredo, T., Alcântara, L., Carrilho, J., Paúl, C., & Costa, E. M. (2025) · Journal of Medical Internet Research · doi:10.2196/77362 · Cited by 27 · see citing works
Min, H., Li, J., Di, M., Huang, S., Sun, X., Li, T., & Wu, Y. (2024) · Frontiers in Public Health · doi:10.3389/fpubh.2024.1348673 · Cited by 21 · see citing works
Bouabida, K., Malas, K., Talbot, A., Desrosiers, M.-È., Lavoie, F., Lebouché, B., Taghizadeh, N., Normandin, L., Vialaron, C., Fortin, O., et al. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12040529 · Cited by 21 · see citing works
Paré, G., Raymond, L., Pomey, M., Grégoire, G., Castonguay, A., & Ouimet, A. G. (2022) · Digital Health · doi:10.1177/20552076221114195 · Cited by 15 · see citing works
Self-citationLi, X., Xie, S., Ye, Z., Ma, S., & Yu, G. (2022) · Journal of Medical Internet Research · doi:10.2196/40681 · Cited by 15 · see citing works
Peixoto, M. R., Ferreira, J. B., & Oliveira, L. (2021) · Revista de Administração Contemporânea · doi:10.1590/1982-7849rac2022210063.en · Cited by 15 · see citing works
Bai, X., Wang, S., Zhao, Y., Feng, M., Ma, W., & Liu, X. (2025) · Journal of Medical Internet Research · doi:10.2196/67462 · Cited by 16 · see citing works
Shen, Y., Xu, W., Liang, A., Wang, X., Lu, X., Lu, Z., & Gao, C. (2022) · Health Informatics Journal · doi:10.1177/14604582221119950 · Cited by 12 · see citing works
Nurses’ Intention to Integrate AI Into Their Practice: Survey Study in Canada
Paré, G., Raymond, L., & Sosso, F. A. E. (2025) · JMIR Nursing · doi:10.2196/76795 · Cited by 16 · see citing works
Self-citationRaymond, L., Paré, G., Doyon, O., & Wagner, G. (2025) · Journal of Advanced Nursing · doi:10.1111/jan.70307 · Cited by 6 · see citing works
Self-citationWu, C., Yang, Z., Yuan, Q., & Zhang, H. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2024.102867 · Cited by 7 · see citing works
Zhang, L., Hussain, W. M. H. W., & Ali, S. H. M. (2025) · Digital Health · doi:10.1177/20552076251396560 · Cited by 4 · see citing works
Vannelli, S., Visintin, F., & Gitto, S. (2025) · Journal of Medical Internet Research · doi:10.2196/60694 · Cited by 4 · see citing works
How Are Security, Privacy and Trust Affecting Continuance Intention of Contact Tracing Applications?
(2023) · Journal of System and Management Sciences · doi:10.33168/jsms.2023.0103 · Cited by 4 · see citing works
Ringeval, M., Raymond, L., Pomey, M.-P., & Paré, G. (2025) · Journal of Medical Internet Research · doi:10.2196/64804 · Cited by 4 · see citing works
Self-citationSedlack, J. D., & Aamer, A. M. (2025) · Global Journal of Flexible Systems Management · doi:10.1007/s40171-025-00456-w · Cited by 3 · see citing works
Effectiveness and acceptability of remote consultation to promote positive behaviors in preschoolers
Kahan, S., & Rahill, S. A. (2024) · Psychology in the Schools · doi:10.1002/pits.23262 · Cited by 2 · see citing works
Rosas, F., Gayoso, A., Tomateo-Torvisco, D., & Orellano, C. (2024) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2023.0428 · Cited by 1 · see citing works
Durachman, Y., Nurbojatmiko, Aryan, A., Huda, M. Q., & Nuryasin (2025) · International Conference on Cyber and IT Service Management (CITSM) · doi:10.1109/citsm67730.2025.11291545 · Cited by 1 · see citing works
Implementation and Evaluation of Virtual Care in Canadian Health Care Systems: A Scoping Review
Yang, B., Leader, J. S., Bowes, B., Aiyer, H. P., Dunn, H., Adams, S., O’Connell, M. E., McIntyre, L. J., Dani, H., Johnson, R., et al. (2026) · Telemedicine Journal and e-Health · doi:10.1177/15305627261425160 · Cited by 2 · see citing works
Zahoor, A.-W., Khan, Z. A., Khan, A., Qamar, N., Farooqui, S. I., & Allana, R. (2023) · International Archives of Health Sciences · doi:10.4103/iahs.iahs_4_22 · Cited by 1 · see citing works
Garcia, G. G., Alvarez, S. G., & Quintana, P. V. B. (2025) · Smart innovation, systems and technologies · doi:10.1007/978-981-96-0426-5_9 · Cited by 1 · see citing works
Yuan, R., Xie, Q., & Caibo, W. (2021) · doi:10.2196/preprints.32028
Percepções sobre o atendimento nutricional on-line: uma revisão
de Araújo, A. S. B., Lemos, D. E. D. A., Maciel, F. F. C., da Silva, R. R. F., Donato, N., Esmero, J. A. D., & Barbosa, M. Q. (2022) · Research Society and Development · doi:10.33448/rsd-v11i13.35858
Role of Digital Healthcare in Rehabilitation During a Pandemic
Gupta, M., & Kalra, R. (2023) · Signals and communication technology · doi:10.1007/978-3-031-19752-9_16
Cynthia, C., Antonio, F., & Wuisan, D. S. S. (2023) · JMMR (Jurnal Medicoeticolegal dan Manajemen Rumah Sakit) · doi:10.18196/jmmr.v12i2.51
Tandon, A., Nambiar, U., Sivapuram, M. S., & Kumar, A. (2024) · Studies in computational intelligence · doi:10.1007/978-981-97-4335-3_1
Kim, E. M., & Lee, E. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5248209
Paré, G., Raymond, L., & Sosso, F. A. E. (2025) · doi:10.2196/preprints.76795
Self-citationGalegale, G. P., Pinochet, L. H. C., de Souza, C. A., & Sun, V. (2026) · Journal of Health Organization and Management · doi:10.1108/jhom-01-2026-0026
- Authors
- Grenier Ouimet, A., Wagner, G., Raymond, L., & Pare, G.
- Affiliations
- HEC Montréal (CA)
- Université du Québec à Trois-Rivières (CA)
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2020-11-26
- Volume
- 22
- Issue
- 11
- Pages
- e22081
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7695543
- OpenAlex
- W3096220191
- Cited by
- 34
- References
- 60
- Citations by year
- 2026: 2 · 2025: 12 · 2024: 5 · 2023: 4 · 2022: 8 · 2021: 3
- FWCI
- 2.81
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- teleconsultation, continuance intention, telehealth adoption, perceived usefulness, perceived quality, COVID-19 pandemic, health system preparedness
- MeSH terms
- COVID-19, SARS-CoV-2, Adolescent, Adult, Humans, Middle Aged, Patients, Remote Consultation, Intention, Young Adult, Pandemics
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