A transdiagnostic app–based cognitive bias modification intervention for paranoia (STOP: “Successful Treatment of Paranoia”): Protocol for a mixed–methods process evaluation embedded in a randomized controlled trial

Background:

Paranoia (unfounded concerns that other people are deliberately trying to harm you) can be a distressing experience that impacts day–to–day functioning for many people. Digitally delivered interventions are a promising treatment mode that can increase access to support and reach populations underserved by current provision. One such intervention is the Successful Treatment of Paranoia (STOP) intervention which is a self–administered smartphone app for paranoia that was evaluated for efficacy in England in a large, multi–site, Randomized Controlled Trial (RCT).

Objective:

This paper describes the protocol for a process evaluation that will explore intervention implementation to understand how much, by whom, and under what circumstances, STOP was used in a trial context and what factors might influence future implementation efforts in routine practice.

Methods:

We will conduct a mixed–methods process evaluation informed by the guidance published by the Medical Research Council in the United Kingdom, embedded in the main STOP efficacy RCT, with the aim of understanding who agreed to try using STOP, how they used STOP, and user and healthcare professionals’ views on factors which would affect future implementation in terms of barriers and facilitators. Process evaluation participants include STOP trial participants, those who agreed to try STOP, a paranoia population in England, and healthcare professionals in England. We used mixed-methods data collected in the STOP trial (demographics, app usage, and recruitment data and additional qualitative data exploring intervention acceptability from the perspective of users and potential prescribers of STOP post–trial) and demographic data from another paranoia population collected in the Adult Psychiatric Morbidity Survey in England.

Results:

To understand who agreed to try STOP in a trial, study 1 will use STOP trial recruitment and demographic data to assess their proportion and representativeness. To understand how STOP was used in a trial, study 2 will analyze user feedback and demographics and usage data. To understand what factors might affect post–trial implementation, study 3 will analyze stakeholder perspectives using framework analysis and the Consolidated Framework for Implementation Research. We will triangulate findings from studies 1–3 to identify barriers and facilitators to intervention implementation in and after a trial, and to summarize this knowledge in a hypothetical implementation framework for post–trial delivery.

Conclusions:

Findings from this process evaluation will develop an evidence-based understanding of implementing STOP, including identifying suitable implementation strategies for post–trial delivery both in and outside of mental health services. Our findings will inform future iterations and the upscaling of STOP and may inform implementation of other self–administered digital mental health interventions. Clinical Trial: ISRCTN registry: ISRCTN17754650; https://www.isrctn.com/ISRCTN17754650.