Navigating ethical risks for mental health research data: a dynamic framework
‘Equity’, ‘inclusive research’, ‘promise for mental health’.
When we asked Wellcome’s mental health lived experience advisers why they work with us, these are some of the comments we heard.
Mental health is a strategic priority for Wellcome — and we work with a team of advisers to ensure lived experience is at the heart of the decisions we make. Our goal is to create a step change in early intervention for anxiety, depression and psychosis and we fund work that will deepen our understanding of how these conditions develop and resolve.
Longitudinal data is a valuable resource to unlock this understanding. Wellcome recently commissioned a landscaping report which catalogued longitudinal datasets from around the world. It found that there are over 3000 existing longitudinal datasets worldwide and highlighted several that offer most promise when it comes to mental health research. But — as the insights from our lived experience advisers indicate — as well as supporting the creation and use of databanks, we want to ensure the data is collected and used in a transparent and fair way, with the interests of people and communities at its core.
Identifying and managing risk
To develop the thinking in this area we commissioned Sage Bionetworks in the US, who worked in collaboration with the Aapti Institute in India, to produce a framework for ethical data governance for mental health databanks. It is now openly available on Wellcome’s website.
The framework provides a structure to understand and manage ethical risks for people setting up and running databanks, and researchers using the data. It:
- Maps out ethical considerations when databanks are being built and once the data is being used
- Identifies risks at both these stages
- Suggests risk mitigations from a platform hygiene and participatory research perspective.
The framework is comprehensive, with an extensive catalogue of risks and mitigations. It is also thoughtfully laid out, so that users can navigate quickly through the sections. Plus there is a useful glossary of frequently used and technical terms.
Who is it for?
We hope the framework will be used by:
- Databank builders and researchers analysing the data, to embed an equitable approach to their planning and execution
- Funders supporting databanks, to guide evaluation of research proposals
- Civil society organisations, to advocate for trustworthy practice in this field
- Communities and people with lived experience, to help them in evaluating opportunities to engage with research in this area.
Our ambition is that the framework supports the development and implementation of ethical practices, clearly indicates where lived experience and community participation is of mutual value, and contributes to the broader debate on ethical standards for longitudinal data in mental health research.
How we got here
Sage developed the framework in three phases (summarised in the documents we link to here):
- A review of the existing literature on data governance for health data and its risks
- Analysis to consolidate the key considerations and mitigations for each of the risk areas identified
- Engaging lived experience advisers and subject matter experts to review the framework, ensuring that critical nuance was not lost through the synthesis process.
A crucial element of this work was the co-design workshops hosted by Sage with our lived experience advisers and Wellcome staff. This enabled in-depth review and iteration of the framework. Thank you to the advisers who participated in these lively and constructive workshops and in particular to Chantelle Booysen and Margaret Osolo Odhiambo who worked with us closely on this project.
We will advocate for the use of the framework within Wellcome, among our grantees and in our engagement with other funders and civil society organisations.
Tell us what you think
As Sage mentioned in their record of the co-design workshops…
‘Participants grappled with the essential truth that the risks and benefits of building and using a databank are dynamic and often difficult to quantify definitively.’
This framework is a robust and well-considered attempt to do just that, and we are very grateful to Sage and Aapti for their expertise and commitment.
The framework is available under a Creative Commons licence, so please do share and adapt it for your work — and let us know whether it measures up to the tough task of capturing this ‘dynamic’ landscape. We’d love to hear from you.
Rebecca Asher and Emily Jesper-Mir, Partnerships and Engagement Managers (job share) in Wellcome’s Data for Science and Health team.
emilyandrebecca-dsh@wellcome.org
