Table 2.
Influence of individual factor in use behavior.
| Influencing Factor (Number of Related Papers) |
Related Variable | Main Conclusion | Literature |
|---|---|---|---|
| Demographic characteristics (74) |
Age | Mobile health applications are mainly used by the young, while seniors, especially those aged over 70, seldom adopt or use mobile health applications | [15,16,17,18] |
| Gender | Males prefer fitness applications, while females prefer applications related to nutrition, self-healthcare, and reproduction | [19,20,21] | |
| Education level | Populations with a high education level tend to use mobile health applications | [22] | |
| Income | Income levels are positively correlated with the use of mobile health applications | [4,23,24] | |
| Medical insurance | Populations with a high medical insurance level have a stronger tendency to use mobile health applications | [16] | |
| Region | Compared to urban residents, rural ones are not likely to use mobile health applications | [16,25] | |
| Ethnicity and language | Difficulties in searching and understanding health information for non-native speakers may restrict their acceptance and use | [26,27] | |
| Health condition | Those with a lower self-rated health status are less likely to use mobile health applications; a chronic history is associated with use | [4,28] | |
| Motivation (25) |
Health awareness | Populations with higher health awareness have a higher acceptance level of mobile health applications | [9,29,30,31,32] |
| E-health literacy | E-health literacy is considered as a prerequisite of using mobile health applications | [5,20,29] |