A Proposal for a Robust Validated Weighted General Data Protection Regulation-based Scale to Assess the Fairness of Privacy Policies of Mobile Health Applications: a Delphi Study

Nowadays, the health sector is involved in a digital transformation. The use of technological systems supporting in the health care are becoming common among all stakeholders. The COVID-19 pandemic has also accelerated this process increasing the use of digital tools, devices, and services supporting patients in the self-management and/or in the communication with healthcare providers. In such circumstances, mobile health (mHealth) has also experienced a significant growth because of the potential benefits of its use in health self-management. However, the quality of the mHealth solutions is not always high enough reducing its adoption and acceptance. This study is focused on one of the components of the quality of mHealth solutions, privacy, particularly on the fairness of the privacy policies. Following a modified Delphi method, we assessed the robustness of a General Data Protection Regulation-based privacy scale, identified new tentative items to be included, and define weights to items according to their relevance. This Delphi study was conducted in two rounds through two online questionnaires that a selected expert panel filled out. Most of the experts considered all the items defined in the original scale as “important” or “very important” (4 and 5 in a 5-point Likert scale, respectively). An original item was reworded, and two new items were added. Regarding weight assignment, 11 of the 16 items in the scale were considered "very important", so that they were assigned a weight of 1, while the other 5 were considered "important", and were assigned a weight of 0.5. As a result, a new robust scale to assess the fairness of the privacy policy of a mHealth solution is defined. The Benjumea privacy scale is a new tool to assess a key component of privacy, privacy policy, providing a deeper and complementary analysis to other scales that assesses the general quality of mHealth solutions. Also, this robust scale provides a guideline for development of high-quality privacy policies of mHealth solutions.