DEVELOPMENT OF MHEALTH USE INTENTION MODEL BY USING PUSH-PULL-MOORING FRAMEWORK - Valentino Bimo P, Anthonius
Mobile health or mHealth is a digital service that aims to facilitate public accessibility in meeting health needs. There have been many studies on the positive factors of the benefits provided by mHealth services, while the inhibiting factors that can inhibit the intention to use this service have not received much attention. An aspect that can be a potential obstacle to mHealth adoption is the habit that has been formed in the community to visit clinics or hospitals to get health services. This habit pattern can raise doubts regarding the doctor's capability, accuracy of diagnosis and also the security of personal health data if the consultation is carried out online without face-to-face meetings. This research was conducted not only to determine the effect of the positive characteristics of mHealth services and their comparison with conventional health services on usage intentions, but also the influence of negative factors that have the potential to hinder the intention to use mHealth services. The model used in this study is the push-pull-mooring framework. In this study, the push factor is a negative factor from conventional health services that encourages people to seek better alternative services, one of which is through mHealth, the pull factor is a positive factor that becomes an advantage of mHealth services and the mooring factor is a negative factor that has the potential to hinder the intention to use mHealth services. The inhibiting factors are formed based on the innovation resistance theory with two main constituent components, namely active resistance and passive resistance. Active resistance is an obstacle that arises after evaluating the weaknesses and shortcomings of an innovation or product, while passive resistance can arise due to a mismatch between the characteristics of an innovation or product with the values, beliefs or habits of prospective users. Data collection used a questionnaire on 174 users of mHealth services in Indonesia. Data processing was carried out using the PLS-SEM statistical method to see the interaction and significance of the research variable relationship. Data collection shows that the majority of respondents are young people and are still students. Based on the knowledge and experience of using mHealth services, the most widely used application is halodoc. The results showed that the pull factor has the greatest influence on the intention to use and the most influential variable is usefulness value. The second biggest influence is the negative influence of the mooring factor, mainly due to usage barriers and risk barriers. Mooring has a direct significant effect on usage intention but does not moderate push and pull factors. The push factor formed by dissatisfaction and high price perception has the weakest significant effect on the intention to use mHealth. The difference in the structural relationship based on the demographics of the respondents is that the influence of the pull factor is greater on the intention to use mHealth in respondents who are already working compared to those who are not working.