Developing a process for assessing the safety of a digital mental health intervention and gaining regulatory approval: A case study and academic’s guide

Background
The field of digital mental health has followed an exponential growth trajectory in recent years. While the evidence base has increased significantly, its adoption within health and care services has been slowed by several challenges, including a lack of knowledge from researchers regarding how to navigate the pathway for mandatory regulatory approval. This paper details the steps that a team must take to achieve the required approvals to carry out a research study using a novel digital mental health intervention. We used a randomised controlled trial of a digital mental health intervention called STOP (Successful Treatment of Paranoia) as a worked example.

Methods
The methods section explains the two main objectives that are required to achieve regulatory approval (MHRA Notification of No Objection) and the detailed steps involved within each, as carried out for the STOP trial. First, the existing safety of digital mental health interventions must be demonstrated. This can refer to literature reviews, any feasibility/pilot safety data, and requires a risk management plan. Second, a detailed plan to further evaluate the safety of the digital mental health intervention is needed. As part of this we describe the STOP study’s development of a framework for categorising adverse events and based on this framework, a tool to collect adverse event data.

Results
We present literature review results, safety-related feasibility study findings and the full risk management plan for STOP, which addressed 26 possible hazards, and included the 6-point scales developed to quantify the probability and severity of typical risks involved when a psychiatric population receives a digital intervention without the direct support of a therapist. We also present an Adverse Event Category Framework for Digital Therapeutic Devices and the Adverse Events Checklist—which assesses 15 different categories of adverse events—that was constructed from this and used in the STOP trial.

Conclusions
The example shared in this paper serves as a guide for academics and professionals working in the field of digital mental health. It provides insights into the safety assessment requirements of regulatory bodies when a clinical investigation of a digital mental health intervention is proposed. Methods, scales and tools that could easily be adapted for use in other similar research are presented, with the expectation that these will assist other researchers in the field seeking regulatory approval for digital mental health products.