Privacy Concerns About Health Information Disclosure in Mobile Health: Questionnaire Study Investigating the Moderation Effect of Social Support (Preprint)
Authors: Dang Yuanyuan , Guo Shanshan , Guo Xitong , Wang Mohan , Xie Kexin 
Published: April 2020

BACKGROUND

Mobile health (mHealth) provides a new opportunity for disease prediction and patient health self-management. However, privacy problems in mHealth have drawn significant attention to patients’ online health information disclosure and to the possibility that privacy concerns may hinder mHealth development.

OBJECTIVE

Privacy calculus theory (PCT) has been widely used to understand personal information disclosure behaviors with the basic assumption of a rational and linear decision-making process. However, cognitive behavior processes are complex and mutual. In an attempt to gain a fuller understanding of information disclosure behavior, we further optimize a PCT-based information disclosure model by identifying the mutual relationship between costs (privacy concerns) and benefits. Social support, which has been proven to be a distinct and significant disclosure benefit of mHealth, was chosen as the representative benefit of information disclosure.

METHODS

We examine a structural equation model that incorporates privacy concerns, health information disclosure intention in mHealth, and social support from mHealth, all at the individual level.

RESULTS

A validated questionnaire was completed by 253 randomly selected participants. The result indicated that perceived health information sensitivity positively enhances patients’ privacy concern (beta path coefficient 0.505, <i>P</i>&lt;.001), and higher privacy concern levels will decrease their health information disclosure intention (beta path coefficient –0.338, <i>P</i>&lt;.001). Various individual characteristics influence perceived health information sensitivity in different ways. One dimension of social support, informational support, negatively moderates the effect of the relationship between perceived health information sensitivity and privacy concerns (beta path coefficient –0.171, <i>P</i>=.092) and the effect of the relationship between privacy concerns and health information disclosure intention (beta path coefficient –0.105, <i>P</i>=.092). However, another dimension, emotional support, has no direct moderation effect on the relationship between privacy concerns and health information disclosure intention.

CONCLUSIONS

The results indicate that social support can be regarded as a disutility reducer. That is, on the one hand, it reduces patients’ privacy concerns; on the other hand, it also reduces the negative impact of privacy concerns on information disclosure intention. Moreover, the moderation effect of social support is partially supported. Informational support, one dimension of social support, is significant (beta path coefficient –0.171, <i>P</i>=.092), while the other dimension, emotional support, is not significant (beta path coefficient –0.137, <i>P</i>=.146), in mHealth. Furthermore, the results are different among patients with different individual characteristics. This study also provides specific theoretical and practical implications to enhance the development of mHealth.