Investigating the Predictors of Telemedicine Service Usage Intention in China During the COVID-19 Pandemic: An Extended Technology Acceptance Perspective

Patients' Acceptability and Perspective on Utilizing Telemedicine in Breast Cancer Care and Management

Background: Telemedicine has emerged as a promising solution to address the challenges of providing continuous care to breast cancer patients, particularly in remote areas. This study aims to assess the acceptability of using telemedicine for breast cancer follow-up. Methods: A cross-sectional study utilizing a self-administered survey was conducted from January to March 2024 among 450 breast cancer patients at the Universiti Malaya Medical Center, Malaysia. Partial least-squares structural equation modeling was used to identify factors such as demographics, patients' characteristics, experience with telemedicine, attitudes, and concern of telemedicine use influencing willingness to use telemedicine for breast cancer follow-up. Results: Of the total 450 complete responses received, nearly half (49.3%) reported being somewhat likely to seek telemedicine for breast cancer follow-up, while only 11.1% reported being very likely. Comfort with telemedicine emerged as the strongest predictor of willingness to use it (β = 0.757, p < 0.001). A higher level of concern significantly negatively impacted willingness (β = -0.138, p < 0.001). However, attitudes toward telemedicine (β = 0.059, p = 0.144) were not significantly associated with its use. Among demographic factors, only age (β = 0.074, p = 0.018) was significantly positively associated with the willingness to use telemedicine, while education levels were found to have a significant inverse association (β = -0.076, p = 0.034). Conclusions: Improving comfort with telemedicine and addressing various concerns about its use for breast cancer follow-up through educational programs and support services are essential. Tailoring communication and support for different age groups and education levels can also enhance acceptance and utilization.

Factors Influencing Telemedicine Usage Intentions: A Comparative Study in Gynecology and Pediatrics

Introduction: Telemedicine has seen rapid growth, especially following the COVID-19 pandemic, providing diverse options for patient care. This study, grounded in the Technology Acceptance Model, examines and compares factors influencing women's usage intentions of telemedicine, considering their roles as both direct patients in gynecology and indirect patients in pediatrics. Methods: The study conducted a survey to collect data from women who have used telemedicine services (N = 758). Structural equation modeling was employed to assess the relationships between variables, including previous satisfaction, social media health content consumption, perceived ease of use (PEOU), perceived usefulness (PU), trust, and future usage intention. Results: The results demonstrate that social media health content consumption, PEOU, PU, and trust in telemedicine have significant direct effects on future usage intention. PEOU and trust mediate the relationships between social media consumption, previous satisfaction, and future usage intention. Notably, the study reveals differences in the factors influencing telemedicine usage between pediatrics and obstetrics/gynecology. Social media health content consumption positively affects usage intention for gynecological but not for pediatric. Trust in telemedicine significantly enhances usage intentions for gynecology but not for pediatrics. Conclusions: The findings reveal disparities in telemedicine usage patterns between obstetrics/gynecology and pediatrics. Practical implications suggest that telemedicine platforms should leverage social media to enhance health education and provide clear guidance, particularly for gynecological services. In addition, strengthening patient privacy protections is essential to build trust and promote telemedicine adoption.

Embracing the Future of Health Care: Investigating Medical Students' Willingness to Become Online Doctors

Purpose: With the rapid advancement of technology, online health care services are becoming increasingly prominent. This study aims to investigate medical students' perceptions, attitudes, and readiness to adopt online health care services. Methods: Based on a literature review, this study constructed a conceptual model describing the relationships among medical students' perception, personality traits, and usage intention, grounded in the Technology Acceptance Model and Technology Readiness Index (TRI). The data for this study were collected from January to February 2023 through a questionnaire survey at Wenzhou Medical University, China. The proposed hypotheses were tested using structural equation modeling through AMOS software. Results: Out of the 340 respondents, 281 (82.6%) validly responded. Among these, 58.4% of medical students agreed and strongly agreed with the intention to become an online doctor. Within the TRI's motivational factors, optimism positively and significantly affected perceived usefulness (PU) and perceived ease of use (PEOU). Innovativeness also significantly enhanced PEOU. Among the inhibitory factors, insecurity was found to have a negative and statistically significant influence on PU. The rest of the dimensions did not have a significant effect on either PU or PEOU. Importantly, both PU and PEOU demonstrated a direct and substantial effect on usage intention. Conclusions: This study emphasizes the significance of comprehending medical students' readiness to adopt the role of online doctors in shaping the future of health care. By equipping medical students with the necessary skills and competencies, health care institutions can effectively leverage the full potential of online health care services while ensuring the provision of high-quality, accessible, and patient-centered care in the digital era.

Exploring Patients' Intentions for Usage of Video Telemedicine Follow-Up Services: Cross-Sectional Study

Background: Data suggest that regarding completion rates and lower readmission rates, video telemedicine follow-up is as efficient as in-person consultations. However, evidence of patients' intention to adopt such service is lacking. The objective of this study was to determine the essential factors influencing Chinese patients' intention to adopt video telemedicine follow-up. Methods: The researchers extended the technology acceptance model (TAM) by incorporating trust, subjective norms (SNs), perceived risk (PR), and perceived disease threat (PDT). A survey was conducted with 793 Chinese patients, and the collected data were analyzed using the partial least-squares approach. Results: The study revealed that trust emerged as the strongest factor influencing patients' behavioral intention (BI) to use video telemedicine follow-up, followed by SNs, perceived ease of use (PEOU), and perceived usefulness (PU). PR and PDT had no significant influence on patients' intention to adopt video telemedicine follow-up. PEOU mediated the relationship between trust, SNs, and BI, and PU mediated the relationship between trust and BI. The study also found that gender, age, and usage experience moderated certain relationships in the model. Conclusions: Our findings support the use of the extended TAM in understanding individual's motivations for using video telemedicine follow-up in China. In addition, this study contributes to the existing literature on telemedicine promotion by identifying significant mediation mechanisms. These findings have practical implications for planning, creating, and implementing improved video telemedicine follow-up services.

Technology Acceptance of Socially Assistive Robots Among Older Adults and the Factors Influencing It: A Meta-Analysis

The purpose of this study was to deeply understand older adults' acceptance of socially assistive robots and their influencing factors and to compare the strength of the correlation between each influencing factor variable and the acceptance. The literature search was performed in five databases from their inception to January 17, 2023. The meta-analysis was performed using Review Manager 5.4 and Stata 16.0 software. Thirteen papers were included in this study. The mean value of acceptability after using the inverse variance method was 3.68. Education level is strongly related to technology acceptance; perceived ease of use, perceived usefulness, technology experience, technology attitude, perceived hedonism, and convenience are moderately related; anxiety is only weakly related.