Modeling telemedicine continuance usage: findings from PLS-SEM and fsQCA

Area of Science:

• Health Informatics
• Digital Health
• Healthcare Management

Background:

• The COVID-19 pandemic accelerated the adoption of telemedicine globally.
• Telemedicine is crucial for overcoming healthcare access barriers in resource-constrained settings.
• Sustained use of telemedicine in low-income countries post-pandemic requires understanding user retention drivers.

Purpose of the Study:

• To explore the key drivers of sustained telemedicine service use in low-income countries.
• To identify factors influencing user satisfaction and attitude towards telemedicine.
• To provide actionable insights for healthcare providers and policymakers.

Main Methods:

• Quantitative research approach with purposive sampling in Bangladesh (n=273).
• Comparative analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM).
• Fuzzy-set Qualitative Comparative Analysis (fsQCA) for deeper causal insights.

Main Results:

• PLS-SEM: Expectation confirmation and ease of use enhance satisfaction; usefulness and ease of use impact attitude.
• PLS-SEM: Usefulness and security showed no significant association with satisfaction/attitude, respectively.
• fsQCA: Usefulness significantly impacts satisfaction; security effectively contributes to continuous use intention, irrespective of its level.

Conclusions:

• User satisfaction and positive attitude are crucial for telemedicine continuance intention.
• Telemedicine providers should focus on enhancing user satisfaction and fostering positive attitudes.
• Findings offer strategies for governments and providers to improve healthcare access and efficiency.