In the physical to digital transition with friends - a story of performing inclusive research together no matter what life throws at you

'Building bridges': reflections and recommendations for co-producing health research

BACKGROUND

Co-produced research is when all stakeholders, including experts by experience and researchers, work together to conceptualise, design, deliver and disseminate research to enhance understanding and knowledge. This type of participatory inquiry is being increasingly used across health research; however, it continues to be a complex area to navigate given existing institutional structures.

MAIN BODY

We collaborated across three independent co-produced research studies to share insights, reflections, and knowledge of our work in the fields of HIV, mental health, and disability research. We co-designed and delivered a three-hour online workshop at a conference to share these reflections using the metaphor of 'building bridges' to describe our co-production journey. We generated key principles of co-production from our different experiences working in each individual research project as well as together across the three projects. Our principles are to: (1) be kind, have fun and learn from each other; (2) share power (as much as you can with people); (3) connect with people you know and don't know; (4) remain connected; and (5) use clear and simple language.

CONCLUSION

We recommend that co-produced research needs additional funding, resource, and flexibility to remain impactful and ethical. Co-produced research teams need to be mindful of traditional power structures and ensure that the process is transparent, fair, and ethical. Addressing equality, diversity, and inclusion of traditionally underrepresented groups in research is essential as are the skills, expertise, and experiences of all members of the co-production team.

Participatory evaluation of the process of co-producing resources for the public on data science and artificial intelligence

BACKGROUND

The growth of data science and artificial intelligence offers novel healthcare applications and research possibilities. Patients should be able to make informed choices about using healthcare. Therefore, they must be provided with lay information about new technology. A team consisting of academic researchers, health professionals, and public contributors collaboratively co-designed and co-developed the new resource offering that information. In this paper, we evaluate this novel approach to co-production.

METHODS

We used participatory evaluation to understand the co-production process. This consisted of creative approaches and reflexivity over three stages. Firstly, everyone had an opportunity to participate in three online training sessions. The first one focused on the aims of evaluation, the second on photovoice (that included practical training on using photos as metaphors), and the third on being reflective (recognising one's biases and perspectives during analysis). During the second stage, using photovoice, everyone took photos that symbolised their experiences of being involved in the project. This included a session with a professional photographer. At the last stage, we met in person and, using data collected from photovoice, built the mandala as a representation of a joint experience of the project. This stage was supported by professional artists who summarised the mandala in the illustration.

RESULTS

The mandala is the artistic presentation of the findings from the evaluation. It is a shared journey between everyone involved. We divided it into six related layers. Starting from inside layers present the following experiences (1) public contributors had space to build confidence in a new topic, (2) relationships between individuals and within the project, (3) working remotely during the COVID-19 pandemic, (4) motivation that influenced people to become involved in this particular piece of work, (5) requirements that co-production needs to be inclusive and accessible to everyone, (6) expectations towards data science and artificial intelligence that researchers should follow to establish public support.

CONCLUSIONS

The participatory evaluation suggests that co-production around data science and artificial intelligence can be a meaningful process that is co-owned by everyone involved.

How Being a Researcher Impacted My Life

Doing research can help people to learn about a lot of different topics. For example, researchers can learn how to work in a group, collect and analyze data, how to make accessible materials, and get to know their own strengths. In this paper, a researcher shares what she learned while working on two research projects about young adults with intellectual/developmental disabilities and co-occurring mental health conditions. The first project was peer mentoring. In this project, we focused on individual needs for someone who may be struggling with mental health. The second project was about workplace disclosure. In this project, we tried to find out if young adults disclose their mental health conditions at work and in job interviews. We explain how we did the projects, how the researcher learned to do research, and what made it easy to learn. We also share about the impact of doing research on the researcher’s personal life. Finally, we share why doing inclusive research is important and how to help researchers with disabilities feel like they are valued members of the research team.