Published on in Vol 22, No 11 (2020): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22081, first published .
Investigating Patients’ Intention to Continue Using Teleconsultation to Anticipate Postcrisis Momentum: Survey Study

Investigating Patients’ Intention to Continue Using Teleconsultation to Anticipate Postcrisis Momentum: Survey Study

Investigating Patients’ Intention to Continue Using Teleconsultation to Anticipate Postcrisis Momentum: Survey Study

Journals

  1. Amin R, Hossain M, Uddin M, Jony M, Kim M. Stimuli Influencing Engagement, Satisfaction, and Intention to Use Telemedicine Services: An Integrative Model. Healthcare 2022;10(7):1327 View
  2. Wu C, Zhou Y, Wang R, Huang S, Yuan Q. Understanding the Mechanism Between IT Identity, IT Mindfulness and Mobile Health Technology Continuance Intention: An Extended Expectation Confirmation Model. Technological Forecasting and Social Change 2022;176:121449 View
  3. Paré G, Raymond L, Pomey M, Grégoire G, Castonguay A, Ouimet A. Medical students’ intention to integrate digital health into their medical practice: A pre-peri COVID-19 survey study in Canada. DIGITAL HEALTH 2022;8:205520762211141 View
  4. Wang T, Wang W, Liang J, Nuo M, Wen Q, Wei W, Han H, Lei J. Identifying major impact factors affecting the continuance intention of mHealth: a systematic review and multi-subgroup meta-analysis. npj Digital Medicine 2022;5(1) View
  5. Bouabida K, Malas K, Talbot A, Desrosiers M, Lavoie F, Lebouché B, Taghizadeh N, Normandin L, Vialaron C, Fortin O, Lessard D, Pomey M. Healthcare Professional Perspectives on the Use of Remote Patient-Monitoring Platforms during the COVID-19 Pandemic: A Cross-Sectional Study. Journal of Personalized Medicine 2022;12(4):529 View
  6. Shen Y, Xu W, Liang A, Wang X, Lu X, Lu Z, Gao C. Online health management continuance and the moderating effect of service type and age difference: A meta-analysis. Health Informatics Journal 2022;28(3) View
  7. Li X, Xie S, Ye Z, Ma S, Yu G. Investigating Patients' Continuance Intention Toward Conversational Agents in Outpatient Departments: Cross-sectional Field Survey. Journal of Medical Internet Research 2022;24(11):e40681 View
  8. Zahoor A, Khan Z, Khan A, Qamar N, Farooqui S, Allana R. Clinician satisfaction and experience using teleconsultation during the COVID-19 pandemic in Pakistan: A cross-sectional study. International Archives of Health Sciences 2023;10(1):7 View
  9. Rosas F, Gayoso A, Tomateo D, Orellano C. Patient Perceptions on Telepsychiatry as an In-Consult Alternative During COVID-19 Pandemic: Peruvian Adaptation of the Telehealth Usability Questionnaire. Telemedicine and e-Health 2024;30(6):e1727 View
  10. Min H, Li J, Di M, Huang S, Sun X, Li T, Wu Y. Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM. Frontiers in Public Health 2024;12 View
  11. Kahan S, Rahill S. Effectiveness and acceptability of remote consultation to promote positive behaviors in preschoolers. Psychology in the Schools 2024;61(10):3982 View
  12. Vannelli S, Visintin F, Gitto S. Investigating Continuance Intention for Telehealth Visits in Children’s Hospitals: Survey-Based Study. Journal of Medical Internet Research 2025;27:e60694 View
  13. Bai X, Wang S, Zhao Y, Feng M, Ma W, Liu X. Application of AI Chatbot in Responding to Asynchronous Text-Based Messages From Patients With Cancer: Comparative Study. Journal of Medical Internet Research 2025;27:e67462 View
  14. Pare G, Raymond L, Etindele Sosso F. Nurses’ Intention to Integrate AI Into Their Practice: Survey Study in Canada. JMIR Nursing 2025;8:e76795 View
  15. Sedlack J, Aamer A. Examining Non-emergency Medical Transportation in Maine: Challenges and Opportunities in Healthcare Logistics. Global Journal of Flexible Systems Management 2025;26(3):529 View
  16. Ringeval M, Raymond L, Pomey M, Paré G. Evolving Medical Students’ Digital Health Perceptions and Intentions: Insights From a Prepandemic and Postpandemic Survey Study. Journal of Medical Internet Research 2025;27:e64804 View
  17. Raymond L, Paré G, Doyon O, Wagner G. Understanding Nurses' Intention to Use Artificial Intelligence Technologies in Their Clinical Practice: A Survey‐Based Configurational Analysis. Journal of Advanced Nursing 2025 View
  18. Figueiredo T, Alcântara L, Carrilho J, Paúl C, Costa E. Understanding Adherence to Digital Health Technologies: Systematic Review of Predictive Factors. Journal of Medical Internet Research 2025;27:e77362 View
  19. Zhang L, Hussain W, Md Ali S. Trust transfer in digital healthcare: The role of self-service systems in reducing patient treatment barriers. DIGITAL HEALTH 2025;11 View
  20. Verbraecken J, Amodio E, Basoglu O, Bellazzi R, Bradicich M, Bruyneel M, Ersu R, Fanfulla F, Fauroux B, Grote L, Lombardi C, McNicholas W, Miltz C, Peker Y, Schiza S, Suarez M, Tamisier R, Tan H, Testelmans D, Tonia T, van Mechelen P, Vrijsen B, Bonsignore M. European Respiratory Society statement on advanced telemedicine for obstructive sleep apnoea (e-Sleep). European Respiratory Journal 2025;66(5):2500557 View

Books/Policy Documents

  1. Gupta M, Kalra R. System Design for Epidemics Using Machine Learning and Deep Learning. View
  2. Tandon A, Nambiar U, Sivapuram M, Kumar A. Proceedings of the 14th Indian Conference on Human-Computer Interaction. View
  3. Garcia G, Alvarez S, Quintana P. Communication and Applied Technologies. View