Type 1 diabetes is a common long-term health condition affecting 40,000 young people in the UK, requiring daily management. The four UK home nations have legal commitments to support young people with medical conditions in their education. However, there are significant challenges in providing evidence to support interventions. Linking data about diabetes and education could help to provide this evidence base and to provide support for young people with diabetes, their families, health professionals, schools and universities. Wide public understanding and strong support are critical for the use of sensitive data in research, such as health and education data. Young people are particularly challenging to engage in such conversations. Researchers at Cardiff University, charity Diabetes UK and partners previously developed a data access framework and set up a Young People with Diabetes Panel to support research into education outcomes for young people with diabetes. The STEADFAST project has built on this prior work. Through STEADFAST, we explored the best ways to inform, engage and involve young people ages 13-24, their families and the wider public in important issues around the use of their sensitive data for research. We set ourselves a target of participation in the project of at least 50% from under-represented groups, which we defined in this context as young people from the lowest five deciles of deprivation and ethnic minorities. STEADFAST was co-produced by young people living with diabetes. We received 400 expressions of interest from young people to participate, of which 100 young people were consented, and 70 were involved across 19 focus groups. As well as producing this final report, we have developed our findings into a Public Involvement Toolkit for use across other health conditions and social impacts using large-scale linked data. We hope our project will have a broader impact, for example enabling research to support young people with asthma at school or young people with epilepsy in employment. This work was funded by UK Research & Innovation [Grant Number MC_PC_21031] as part of Phase 1 of the DARE UK (Data and Analytics Research Environments UK) programme, which is delivered in partnership with Health Data Research UK (HDR UK) and ADR UK (Administrative Data Research UK).