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. 2023 Aug 16:10:e45503.
doi: 10.2196/45503.

Extending the Privacy Calculus to the mHealth Domain: Survey Study on the Intention to Use mHealth Apps in Germany

Niklas von Kalckreuth  1 , Markus A Feufel  1
Affiliations

Extending the Privacy Calculus to the mHealth Domain: Survey Study on the Intention to Use mHealth Apps in Germany

Niklas von Kalckreuth et al. JMIR Hum Factors. .

Abstract

Background: With the increasing digitalization of the health sector, more and more mobile health (mHealth) apps are coming to the market to continuously collect and process sensitive health data for the benefit of patients and providers. These technologies open up new opportunities to make the health care system more efficient and save costs but also pose potential threats such as loss of data or finances.

Objective: This study aims to present an empirical review and adaptation of the extended privacy calculus model to the mHealth domain and to understand what factors influence the intended usage of mHealth technologies.

Methods: A survey study was conducted to empirically validate our model, using a case vignette as cover story. Data were collected from 250 German participants and analyzed using a covariance-based structural equation model.

Results: The model explains R2=79.3% of the variance in intention to use. The 3 main factors (social norms, attitude to privacy, and perceived control over personal data) influenced the intention to use mHealth apps, albeit partially indirectly. The intention to use mHealth apps is driven by the perceived benefits of the technology, trust in the provider, and social norms. Privacy concerns have no bearing on the intention to use. The attitude to privacy has a large inhibiting effect on perceived benefits, as well as on trust in the provider. Perceived control over personal data clearly dispels privacy concerns and supports the relationship of trust between the user and the provider.

Conclusions: Based on the privacy calculus, our domain-specific model explains the intention to use mHealth apps better than previous, more general models. The findings allow health care providers to improve their products and to increase usage by targeting specific user groups.

Keywords: adoption; attitude to privacy; benefit; confidential; data autonomy; intention; intention to use; mHealth; mobile health; privacy; privacy calculus; privacy concern; social norms; survey; trust; trust in the provider.

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Conflict of interest statement

Conflicts of Interest: The survey was funded by BARMER. We, the authors, state that we are not in an employment relationship with BARMER nor have we accepted any other payments. BARMER had no influence on the design of the study, the questionnaire, the analysis, and the interpretation of results. The study design for execution was given by us directly to the survey agency, just as we got the data set directly from them without any interference from the health insurance company.

Figures

Figure 1
Figure 1
Extension of the privacy calculus model to predict intention to use mHealth apps [22].
Figure 2
Figure 2
Factor relationships in the structural model. Solid lines represent statistically significant links and dashed lines represent statistically nonsignificant links. *P<.05. **P<.01. ***P<.001. ns: not significant.
See this image and copyright information in PMC

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