JMIR Publications

ABSTRACT

Background:

Nutrition and fitness mobile health applications (mHealth apps) provide tracking and support mechanism on demand and it became a new trend for health service providers to shift into mHealth apps. Those services come to end-users with no cost to use but premium services into the apps can be purchased with an additional cost. Although Turkey’s most commonly used diet platform Diyetkolik, in its 7th year, is now more engaging with their users, customers’ behavioural intention to use these innovative apps is unknown.

Objective:

The aim of this study is to investigate influencing factors on nutrition-based mobile-health service to find out the behavioural intentions of users to adopt that kind of apps. To work on the issue, perceived usefulness, ease of use, price-performance, perceived risk, and trust factors were explored to assess the extended technology acceptance model.

Methods:

We conducted quantitative research methodology on the app users by using random sampling and valid data sample gathered from 658 app users were analysed statistically to investigate the framework by applying structural equation modelling (SEM).

Results:

Statistical findings suggested that perceived usefulness, perceived ease of use, trust, and price-performance have a significant relationship with behavioural intention. But, the relation between the observed risk factor and behavioural intention has been statistically rejected in this research. Additionally, there were no statistically significant results for age groups, gender differences and previous categorical app experience on the intention to use the app.

Conclusions:

This research provided precious insights into TAM literature and mobile-health app developers and managers to recognize their customs’ behaviours and apparent external factors. Effects of proposed factors showed significant intention to use the app, except perceived risk. However, moderating effects should be kept in mind when examining extended TAM- based interventions to understand perceived risk factor via application use.