From self-reliers to expert-dependents: identifying classes based on health-related need for autonomy and need for external control among mobile users

Abstract

Mobile health apps are seen as promising tools to support autonomous consumers in their quest for better health. However, individual differences in the need for autonomy and need for external control may impact the degree to which individuals perceive mobile health apps to be useful in their daily life. Using data from a representative sample of the Dutch population (N = 1,027), we applied latent class analysis to identify subtypes among mobile users based on their need for autonomy and need for external control, and to examine differences among these subtypes. We identified four subgroups: the self-reliers, confirmation-seekers, expert-dependents, and indifferents. Next to demographic differences, self-reliers and confirmation-seekers were generally more e-health literate and expressed more privacy concerns than the expert-dependents and indifferents. Our findings demonstrate that subgroups of people express different degrees of health-related need for autonomy and need for external control, which should be taken into account in online and mobile health communication efforts.