Examining User’s Initial Trust Building in Mobile Online Health Community Adopting

Abstract

Due to the high perceived risk, it is critical to foster users’ initial trust in the promotion of mobile online health community (MOHC) adoption. The present study focused on the role of two different trust elements and examined the initial trust building process based on elaboration likelihood model and trust transfer theory. The results indicated that initial trust in MOHC context was composed of two interrelated components: health service provider (doctor) and underlying technology (MOHC platform). Especially, the initial trust in MOHC platform exerted greater effects on adopting intention. Both performance-based cue (doctors’ information quality and interaction quality) and transfer-based cue (trust in the offline doctors’ health service) positively shaped the initial trust in doctor. Meanwhile, only the performance-based cue (MOHC platform’s information quality and service quality) has significant positive association with initial trust in MOHC platform. However, interpersonal recommend is insignificantly related to the initial trust in doctor. Trust in the mobile internet service is insignificantly related to the initial trust in MOHC platform.

Antecedents of Intention to Adopt Mobile Health (mHealth) Application and Its Impact on Intention to Recommend: An Evidence from Indonesian Customers

“…Compatibility, performance expectancy, facilitating conditions, information-seeking motive, initial trust in the doctor, and initial trust in the mHealth platform explained 53.2% of the variance of intention to adopt with a medium predictive power Q 2 predict . Intention to adopt explains 48.3% of the variance of intention to [37,63]. In conclusion, the use of three major theories of UTAUT2, DOI, and internet customer trust models was successful because at least one construct had a statistically significant impact on explaining mHealth application's adoption.…”

“…So, the initial trust in a health service application, including doctors and platforms, is an essential factor for users to decide whether to use such a platform [78]. Cao et al [37] also found that their previously received medical services were primarily offline for first-time healthcare 14 International Journal of Telemedicine and Applications application users. The healthcare application platform has changed the medical service delivery channel, and thus, users will be paying more attention to the providers of this new underlying technology.…”

“…Initial trust in doctor is associated with the doctor's information quality and interaction quality, while initial trust in mHealth platform is associated with its services. Cao et al [ 37 ] found that both initial trust in the doctor and initial trust in mHealth platform are significant predictors of intention to adopt mHealth. Hence, both initial trust in the doctor and initial trust in mHealth platforms are incorporated in this study.…”

Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective

“…Smart PLS 2.0., a user-friendly modeling software for partial least squares (PLS) which has been widely adopted in the existing research [ 69 , 70 ], was employed to analyze the measurement model and structural model. The reliability and validity of the measurement model were examined.…”

“…The measurement scales used in the present research were adapted from the existing relevant literatures regarding mHealth service, elderly user’s mHealth application usage, information system environment overload, information system resistance behavior, and so on. To ensure consistency, following the back-translation procedures which were widely used in the prior studies [ 69 , 70 , 71 ], one researcher translated the initial English version of the questionnaire into Chinese. After that, the other three researchers translated them back into English independently as a double check.…”