Digital mental health research produces a particular challenge for involvement: asking young people with lived experience to engage with tools, data, and methods that are themselves digital, and whose design and evaluation are the subject of the research. BRIDGE, based at the University of Nottingham, is a project investigating the facilitators, barriers, and solutions to involving young people meaningfully in digital mental health trials. Rather than treating involvement as a box to tick, BRIDGE treats it as something that itself needs to be studied, understood, and improved.
The Research
BRIDGE's central research question is: what are the facilitators, barriers, and solutions to meaningful public and patient involvement in digital mental health research with young people? The project uses a mixed-methods design across two studies. Study 1 involved workshops with young people and interviews with researchers to understand what makes a digital mental health trial genuinely useful and well-designed from both perspectives. Study 2 is a Children and Young People (CYP) survey exploring the same questions quantitatively across a broader sample.
The project is supervised by Camilla Babbage, Research Fellow at the NIHR MindTech HealthTech Research Centre, University of Nottingham. Babbage has published on participatory methodologies in digital mental health, including a paper on cultivating participatory processes in self-harm app development in JCPP Advances. A protocol for the BRIDGE scoping review of PPI and Responsible Research and Innovation in youth mental health projects is published in Research Involvement and Engagement.
Co-Analysing Qualitative Data
One of the more substantive aspects of BRIDGE's involvement model is genuine co-analysis: PPI members were trained in Reflexive Thematic Analysis (RTA), a qualitative method developed by Braun and Clarke for identifying patterns of meaning across interview and focus group data, and participated in coding transcripts from Study 1 alongside the research team.
In a structured workshop, PPI members were introduced to the six phases of RTA: familiarising with the data, generating initial codes, developing themes, reviewing themes against the data, refining and naming themes, and writing up. The central ideas, that codes are short labels of meaning applied to text, that themes capture shared patterns across the data rather than just topics, and that the analyst's own background and experience (reflexivity) is a strength rather than a problem, were introduced in accessible terms, with examples drawn from imaginary transcripts before moving to real data.
The workshop focused on phases one and two: reading the Study 1 transcripts and generating initial codes. Participants highlighted text that seemed meaningful, applied codes to it, and then shared and discussed their interpretations as a group, with the explicit recognition that different analysts might code the same passage differently, and that this variation was analytically valuable rather than a problem to resolve. The coded transcripts and notes from PPI members were then used by the research team to inform the theme development phase.
Creative Dissemination
As the project moved towards dissemination, PPI members were invited to contribute to creative outputs, infographics summarising Study 1 and Study 2 findings, and a short video with voiceovers. The involvement model throughout was attentive to both the time demands placed on PPI members and the skills and experience they were building: participants left with training in qualitative research methods, an understanding of the research process, and outputs they could point to as evidence of genuine co-production.
My Involvement
I am a PPI member on the BRIDGE project. My involvement has spanned the full arc of the project: providing feedback on the survey design and focus group structure during co-production sessions, participating in the qualitative co-analysis workshop and coding Study 1 transcripts, and contributing to the creative dissemination materials for both studies. The co-analysis component in particular was a substantive methodological contribution — not just consultative review, but active participation in the process of making meaning from data.