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Abstract 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.

Abstract 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.

Abstract Changes in brain morphology have been reported during development, ageing and in relation to different pathologies. Brain morphology described by the shape complexity of gyri and sulci can be captured and quantified using fractal dimension (FD). This measure of brain structural complexity, as well as brain volume, are associated with intelligence, but less is known about the sexual dimorphism of these relationships. In this paper, sex differences in the relationship between brain structural complexity and general intelligence (g) in two diverse geographic and cultural populations (UK and Indian) are investigated. 3D T1-weighted magnetic resonance imaging (MRI) data and a battery of cognitive tests were acquired from participants belonging to three different cohorts: Mysore Parthenon Cohort (MPC); Aberdeen Children of the 1950s (ACONF) and UK Biobank. We computed MRI derived structural brain complexity and g estimated from a battery of cognitive tests for each group. Brain complexity and volume were both positively corelated with intelligence, with the correlations being significant in women but not always in men. This relationship is seen across populations of differing ages and geographical locations and improves understanding of neurobiological sex-differences.