Mental Health Award: Leveraging longitudinal data to transform early intervention in mental health

You can apply to this call if you are a team of researchers: 

• from any relevant discipline. We consider a broad range of disciplines to be relevant to mental health science, as long as the research fits within our principles of mental health funding
• from eligible organisations
• based anywhere in the world (apart from mainland China)

We encourage applications from: 

• diverse and interdisciplinary teams, with collaborations covering multiple areas of expertise relevant to the proposed project
• researchers at any stage of their career, including those who are new to the field of mental health and data science

Your experience 

If you’ve spent time away from research 

Career breaks, parental leave, sick leave

You can apply for this award if you have spent time away from research (for example, for a career break, parental leave or long-term sick leave). We will take this into consideration during the review of your application. 

Retirement

If you have retired, you must contact us before applying. You must have a guarantee of space from your administering organisation for the duration of the award. 

Working part-time

Lead and coapplicants can be part-time. Part-time applicants should still be able to contribute at least 20% of their research time to the project. Their part-time work should be compatible with delivering the project successfully.

You should not apply for this call if: 

• You intend to carry out activities which involve the transfer of funds into mainland China.
• You cannot demonstrate that you can dedicate enough time and resources to the project, if funded.
• You already have applied for, or hold, the maximum number of Wellcome awards for your career stage. Find out how many Wellcome awards you can apply for, or hold, at one time depending on your career stage.

• You are already an applicant on two applications for this funding call. You can be, at a maximum:

  • a lead applicant on one application and a coapplicant on another one
  • a coapplicant on two applications

  You must demonstrate that you have sufficient capacity for both projects if funded. The applications should be for different projects with no overlap of activities. 
  There is no limit on the number of applications on which an individual collaborator can be named, provided they have sufficient capacity.

Check what kinds of research project aren’t right for this scheme.

The administering organisation is where the lead applicant is based. It is responsible for submitting your final application to Wellcome and managing the finances of the grant if it is awarded. 

About the administering organisation

The administering organisation can be based anywhere in the world apart from mainland China. It must be able to sign up to Wellcome’s grant conditions. 

The administering organisation can be a: 

• higher education institution
• research institute
• non-academic healthcare organisation
• not-for-profit or non-governmental research organisation 

Commercial organisations are not eligible to apply as administering organisations for this call. However, coapplicants and collaborators can be based at commercial organisations. 

One organisation can submit multiple different applications. 

What's expected of lead applicant and coapplicant organisations

We expect organisations based in the UK to meet the responsibilities required by the Concordat to Support the Career Development of Researchers for institutions, managers and researchers. 

Any organisation with Wellcome funding that is based outside the UK is expected, at a minimum, to follow the principles of the Concordat. 

Read the Concordat 

We also expect organisations to: 

• Guarantee that the space and resources applicants need have been agreed and will be made available to them from the start date through to the end date of the award
• Explain how the application fits with the strategic aims of the organisation
• Give the lead applicant, and any staff employed on the grant, 10 days a year (pro rata if part-time) to undertake training and continuous professional development (CPD) in line with the Concordat. This should include the responsible conduct of research, research leadership, people management, diversity and inclusion, and promotion of a health research culture.
• Provide a system of onboarding, embedding and planning for staff when they join the organisation and/or start the award.

Collaboration agreements 

If the application involves a collaboration or partnership between multiple organisations, the partners must enter into a suitable collaboration agreement, including provisions that cover: 

• confidentiality
• publication rights
• access to background intellectual property
• ownership of foreground intellectual property
• arrangements for the protection, management and exploitation of foreground intellectual property

The administering organisation is required under our grant conditions to own all the foreground intellectual property arising from the project and to take the lead in any commercialisation activity. For guidance, read Wellcome's intellectual property policy. 

Your research environment 

Wellcome believes that a diversity of people and expertise leads to richer understanding and more impactful discoveries. Excellent research happens in environments where people from all backgrounds are treated with respect, are supported and enabled to thrive. 

Our definition of a research environment is not limited to the quality of the infrastructure but also considers the culture and behaviours that create excellent research practice. This includes research that is inclusive in design and practice, ethical and engaged with relevant community stakeholders, as well as open and transparent. 

Read guidance on how to talk about research environment in your application.

What your research proposal must include

Your research proposal must: 

• focus on predicting the onset, early progression and/or treatment response of anxiety, depression and/or psychosis at the individual or subgroup level
• leverage existing longitudinal data
• validate the prediction model in a fully independent sample
• integrate an experimental component
• use robust and appropriate data analytics
• be carried out by a multidisciplinary team that includes mental health researchers and data scientists
• incorporate lived experience in the most appropriate and ethical ways
• include strong consideration of translational potential

Focus on early identification 

Projects can focus on onset and/or progression after onset, including relapse and treatment response, as long as the focus remains on enabling earlier identification than currently possible.

Projects can focus on one or multiple factors that predict the onset, early progression and/or treatment response of anxiety, depression and psychosis. Both data-driven and hypothesis-driven prediction models are in scope and there is no preference for one over the other. 

The proposal should focus on building and validating models enabling prediction and targeting at the individual or subgroup level (rather than population-level risk). The proposed model can include predictors that span individual, family and society levels, as long as the primary focus is still on individual or subgroup level prediction.

In your proposal, you must show that you have considered the ethical risks surrounding prediction and early identification. 

Leveraging existing longitudinal data 

Proposals must include the analysis of existing longitudinal data. 

We define longitudinal data as any data collected on the same individuals over time with a minimum of at least three time points. 

There are no eligibility restrictions on sample size. We recognise that a larger sample does not always translate to a stronger early identification model, and that small datasets might have the potential to offer valuable insights. 

Longitudinal datasets can be held by academic, non-for-profit, public or private/commercial institutions. They can include, but are not limited to: 

• cohorts
• biobanks
• electronic health records and registries
• community, village or household panels
• data from experimental research collected over time
• intervention trials with at least three time-points 

Projects can include enrichment of existing longitudinal datasets, including:

• linkage to other sources
• harmonisation between datasets
• collection of additional data and metadata (e.g. new measures, more frequent or detailed assessments, include qualitative/unstructured data)
• increasing the sample size or diversity of the dataset
• making data more findable, accessible, interoperable and reusable 

You should share your research proposal with the data holders of all the longitudinal dataset(s) you are planning to use. We expect you to have received confirmation that the dataset(s) is suited for your research. See the ‘Information you need to provide’ section for what we require. 

We encourage applicants to include data holders of the longitudinal dataset(s) as part of the research team, if appropriate. 

For projects analysing longitudinal data drawn from populations that are historically underrepresented in research, the study must consider biases in the data collected and proactively address them and seek to mitigate the risks of harm to these underrepresented groups from the research findings. 

Validation in independent dataset(s)

Applicants must validate their models in fully independent samples. 

Prediction models can often show high accuracy within the sample they were built in but fail to generalise in independent samples. To be successful, your application should show that you will validate your prediction model with independent datasets. This should include: 

• which dataset(s) you will use for validation
• why this dataset is suitable
• how you plan to harmonise the datasets
• your analysis plans 

The independent datasets should be fully separate from those used in the development of the prediction model. Subsets of the original dataset or test/validation splits are valuable for model development, but are not sufficient for independent, external validation. You can enrich the existing independent datasets for validation purposes as outlined above, including new data collection. 

Integration of an experimental component 

Proposals must include an experimental component that complements the results of the analysis of the longitudinal data. This could include, but is not limited to: 

• advancing mechanistic understanding of one or multiple early identification factors
• advancing intervention potential by acting on early identification factors
• using the early identification model to implement earlier or better targeted interventions in a pilot or feasibility study 

Our definition of an experimental component is broad, and includes any manipulation including, but not limited to: 

• molecular and cellular studies
• systems neuroscience
• animal models
• human studies, including clinical trials 

The experimental component could involve primary data collection or already collected data from an experimental study. In any case, the proposal needs to clearly lay out how the experimental approach complements the analysis of the existing longitudinal data and how it expands our mechanistic understanding or translational potential of the early identification model. 

Studies based solely on simulated data are out of scope. 

Projects with human participants must also use, as a minimum, one or more of our recommended common measures in the collection of new data where appropriate. These common measure(s) do not have to be primary outcome(s), and you may also collect any other measures. 

Robust and appropriate data methods 

Projects should integrate mental health and data science expertise and bridge the gap between the two disciplines. You should approach data analysis in a way that makes best use of the longitudinal data available to propose robust prediction models for early identification of anxiety, depression and/or psychosis. 

You can use any approach, including predictive, clustering, classification, generative, probabilistic and others. You will need to justify your approach and clearly show how your results will transform our understanding of early identification and intervention. 

Analysis of data previously collected may raise ethical considerations. You should address these concerns and provide a comprehensive data management plan that: 

• Demonstrates how the proposed work aligns with best practice guidelines for ethical data science. Please use the Wellcome ethical framework (see the data analysis section from page 38 onwards) to reflect on risks and develop mitigations.
• Outlines concrete measures to safeguard privacy, ensure confidentiality, protect data integrity and minimise the risk of data loss.
• Ensures the proposed research follows the rules set in the participants’ informed consent forms and seeks additional consent from participants as necessary. 

We expect applicants to comply with Wellcome’s research environment principles of open science and relevant diverse inputs.

Collaboration between mental health scientists and data scientists 

Each project must have a minimum of one data scientist and one scientist working in mental health as part of the core team. This means that they should be either the lead applicant or a coapplicant. Relevant expertise for this funding call could potentially include, but is not limited to: 

• data experts (for example, data scientists, analysts, ethicists and engineers)
• data holders/guardians
• psychiatrists and psychologists
• social scientists
• science, technology, engineering and mathematics
• humanities (for example, historians and ethicists)
• epidemiologists
• lived experience experts
• clinical and allied health sciences
• experimental medicine
• neuroscientists

Mental health conditions in scope 

This award focuses on the early identification of anxiety, depression and/or psychosis. These are broadly defined to include: 

• all types of mood disorders, including depressive disorders and bipolar disorders
• all types of anxiety disorders, including obsessive-compulsive disorder and post-traumatic stress disorder
• all forms of psychotic disorders, including schizophrenia and postpartum psychosis 

We don’t have a preference for which diagnostic system or classification system you follow to define a mental health condition. But we expect you to explain why you chose a particular framework or measurement approach, and why it fits the aim of your study. We invite applications where the early identifier(s) predicts the onset, early progression and/or treatment response of: 

• Anxiety, depression and psychosis as categorical diagnoses. Applicants can focus on one or more of these conditions as defined above.
• Any clinically relevant symptom(s) strongly associated with these conditions. The symptom(s) could be specific to one of the conditions, or shared across several of them.
• Functional impairments associated with any of the above conditions, that impact daily lives, such as participation in work or education.

Projects can include populations living with other physical or mental health conditions as long as the focus remains on anxiety, depression and/or psychosis. 

Lived experience involvement 

Proposals must involve lived experience expertise of anxiety, depression and/or psychosis, relevant to your research topic. There is a range of ways that research teams can involve and collaborate with lived experience experts. This may include, but is not limited to: 

• expert advisors
• coapplicants
• collaborators
• advisory group members 

Lived experience experts should be engaged as colleagues who use their knowledge and expertise to inform the strategic direction, governance, design and delivery of the research. They must be involved in appropriate and ethical ways to inform multiple aspects and stages of the research project. Their contribution should not be limited to recruitment and retention strategies. 

Read more about our approach to involving Lived Experience expertise.

Consideration of translational potential 

We want to encourage innovative and impactful projects that can transform early identification for mental health. This means that applicants must show that their early identification model has strong potential to be translated into a real-world setting and contribute to the development of new and improved early interventions for mental health.

We are looking for models that can identify mental health problems earlier than previously possible, allowing for more efficient treatment and new and improved early interventions. Applicants need to clearly indicate the practical implications of their work by showing how their model will inform early interventions, evidence-based guidelines or routine clinical practice.

What your research proposal can include

We encourage applicants to be brave and be willing to take risks if they feel their research has the potential to be transformative. We seek to fund ambitious, impactful projects. This means some of the projects we fund may not work out and we are prepared to take these risks. 

Although it is not mandatory, we have identified the following topics as areas of interest, so we encourage proposals that: 

• analyse qualitative/unstructured data either following primary data collection or through secondary data analysis. Applicants are required to follow best practices for data management and carefully address the ethical implications of the use of such data and the additional complexities of secondary analysis of qualitative data. Such qualitative/unstructured data may include, but are not limited to:
  • transcribed text files
  • data from wearable devices
  • audio and video recordings
• prioritise research within and across low- and middle-income countries, as we recognise that longitudinal datasets from these locations are particularly underutilised. Proposals can be led by or be in collaboration with data holders from low- and middle-income countries. We also expect applicants to consider ethical and equitable partnerships. 

Public engagement

When possible, we also recommend that applicants undertake engagement activities as part of this award. Before you begin planning your engagement activities, we recommend that you first reach out to the dataset holder(s). 

Based on the current literature, ‘two-way’ communication is the preferred approach to data-based research. This means that research participants want to feel part of the work being done and to be actively listened to. 

Find out more about promoting public engagement with longitudinal research. 

At Wellcome we believe using an engaged research approach improves research and makes it more impactful. This is an umbrella term for engaging with different groups interested in your research. When developing your engagement plan for this call, we recommend: 

• using deliberative methods
• giving people information about the research practices you will use as well as providing the rationale for the research itself
• ensuring you have appropriate entry points for people’s feedback to shape your work. 

Find out more about using an engaged research approach. 

What your research proposal must not include

Your research proposal must not: 

• Focus on identifying general risk factors at a population level.
• Primarily target neurodevelopmental conditions, neurodegenerative diseases, or mental health disorders and symptoms outside of the broad categories of anxiety, depression, and/or psychosis. For example, eating disorders or substance abuse are not in scope.
• Be based solely on simulated data.
• Aim to set up entirely new cohorts or longitudinal datasets.
• Focus on exploratory or curiosity-driven mechanistic research that is not directly relevant to the scope of the call and Wellcome’s mental health remit.

You can ask Wellcome to pay for:

See 'Other costs' for costs Wellcome will not pay for.

Information you need to provide

As part of your application, you will need to provide a letter which confirms that, for all the longitudinal datasets you intend to use, the data holder or any relevant representative with a formal affiliation has read the project proposal and is confident that their dataset is appropriate for answering the research question. You will need to: 

• Provide a single A4 letter listing the name, research title and contact address of a relevant contact for each dataset you propose to use.
• Attach this letter to your application as Additional Information. It won’t count towards your two A4 pages limit for additional information. 

Timing considerations for your application

You must leave enough time for: 

• reading everything on this page before applying
• you and your coapplicant(s) to complete the application
• your administering organisation to review, offer feedback and for you to complete any suggested changes
• the authorised organisational approver at your administering organisation has time to approve and submit your application to Wellcome by 17:00 BST on 22 July 2025. 

Getting support with your application

We offer disability-related support for applicants. Read the disability-related support guidance if you: 

• are disabled or have a long-term health condition and you need help applying for funding
• need help completing your project, for example costs for assistive technology 

If you need further support with completing your application or need to request an extension to the deadline, please contact us. 

If this is the administering organisation’s first time applying for Wellcome funding 

If this is the administering organisation’s first time applying for Wellcome funding, they will need to contact us to request an organisation account. 

Email fundingsupport@wellcome.org with the administering organisation’s: 

• name
• address
• country
• team email address for the people who will approve and submit your application (this is usually a research management team) 

We will create the organisation account and provide access to the approvers. Review our guidance for research offices. 

Application process 

Before you apply 

• Make sure you read everything on this page, as well as our guidance on involving lived experience experts.
• You do not need to contact us before you write and submit your application.
• If you are unsure if your proposal is within the scope of this call, you can request a scope check before submitting your full application.
• Register to attend our Information Webinar on 7 May 2025. 

Submit your application to your administering organisation for approval 

• Complete your application form on the Wellcome Funding platform.
• Submit your completed application form to the 'authorised approver' at your administering organisation for approval.
• Make sure you leave enough time for the approver to review and submit your application before the deadline. The approver may ask you to make changes to your application before it is submitted to Wellcome. 

Administering organisation approves and submits your application to Wellcome

Your application must be submitted by 17.00 BST on the deadline day, 22 July 2025. We do not accept late applications. 

Shortlisting 

• We will check your eligibility for the call and that your proposed research is within the call’s remit. If your application is ineligible or not within the remit of the funding call, we will withdraw your application and contact you to explain why.
• A committee will assess eligible and in-remit applications against the assessment criteria, to make shortlisting recommendations to Wellcome.
• Committee membership will be comprised of a diverse range of international members and will take into account Wellcome’s diversity and inclusion priorities.
• If your application is shortlisted, we will invite the lead applicant – accompanied by up to three coapplicants – for a virtual interview. We anticipate shortlisting decisions to be communicated in October 2025.
• We are unable to provide feedback on applications that are not shortlisted.

Written expert interview 

• We will seek external written expert review on shortlisted applications. Reviewers will be selected based on their expertise within the relevant research field and not on their level of seniority.
• Unattributed comments will be sent to shortlisted applicants before the interview. 

Interview 

• The committee will interview shortlisted applicants online and make funding recommendations to Wellcome. Interviews are scheduled to take place 2 - 4 December 2025.
• The lead applicant will attend the interview, accompanied by up to three coapplicants.
• We will contact the lead applicant to ask if interview attendees have any accessibility requirements.
• You will be asked to give a presentation at the start of your interview. Details of the requirements for this presentation, and the date when slides need to be submitted to Wellcome, will be shared in advance.
• We will provide further information on the structure of the interview, room layout and committee membership before the interview.
• The focus of the interview will be on questions and answers. The committee will assess the application against the full set of assessment criteria, rather than one specific aspect of the proposal.
• The committee will consider your application, the expert reviewers’ comments and interview responses when making funding recommendations to Wellcome. 

Funding decision

• Final funding decisions will be made by Wellcome’s Mental Health Team.
• You will receive an email notification of the funding decision soon after the decision has been made in December 2025.
• The reasons for a decision will be provided to unsuccessful applicants in writing.

You must submit your application by 17:00 BST on the deadline day. We cannot accept late applications.

All applications will be evaluated using the same weighted assessment criteria.

Essential criteria and weightings

There are four weighted assessment criteria for applications:

1. Research question and proposed methodology (40%)
2. Suitability and expertise of the team (20%)
3. Suitability of the research location and approach to research environment (20%)
4. Lived experience involvement (20%) 

1. Research question and proposed methodology (40%) 

Potential and impact 

• The proposed research will advance early identification for anxiety, depression and psychosis.
• The project has strong translational potential that can have a significant and measurable impact on early intervention, either directly or in time. 

Rationale and strength of evidence 

• There is a strong rationale for the proposed research approach and the focus on this particular mental health condition or symptom(s).
• The specific longitudinal dataset(s) can offer unique insights into early identification and contains the appropriate information to answer the research question. 

Strength of methodology 

• All proposed data analytic approaches are justified, robust and appropriate given the breadth and depth of the data. The proposed analysis makes best use of the available data while following best practice guidelines for ethical data science.
• The project is well-designed and feasible using the resources and timelines proposed.
• The key risks to delivering the proposal and plans to adopt risk-reducing steps to overcome them have been identified.
• If the project includes research on underrepresented populations, the study design or analysis plan includes approaches to mitigate biases that might disproportionately impact these populations.
• The validation in an independent dataset is well-planned and offers a strong opportunity to test the prediction model.
• The experimental component complements the analysis of the existing longitudinal data and advances mechanistic understanding and/or intervention potential of the early identification model.

2. Suitability and expertise of the team (20%) 

The project features an integrated, collaborative plan of work that includes mental health researchers, data scientists, individuals with lived experience and others as appropriate. 

The lead applicant has (appropriate to their career stage): 

• research experience relevant to the project, as shown through research outputs and/or preliminary data
• the experience needed to drive and lead a collaborative, large-scale research project and/or the necessary support structures in place to enable this
• experience of people and research management 

The coapplicant(s) has/have: 

• the expertise, time and resources needed to deliver the project, with their contribution to the project being significant and justified 

The team: 

• Has the necessary expertise and technical skills, as well as the appropriate variety of disciplines and perspectives, to deliver the proposed project. At a minimum we expect the team to include relevant mental health and data science expertise.
• Includes lived experience experts and/or has the necessary skills to effectively involve and collaborate with people with lived experience of mental health problems in the proposed research.
• Has members who are all necessary to deliver the proposed research and there is proof of concept that the proposed collaboration will be feasible and effective. For example, the team has appropriate management plans in place describing how the collaboration will be equitably organised and managed day-to-day.
• Has contributed towards and is committed to fostering a positive and inclusive research environment, which demonstrates a commitment to equity, diversity and inclusion. 

3. Suitability of the research location and approach to research environment (20%)

Research location 

• The administering organisation is supportive of the research project. For example, it aligns with the organisation’s strategy and it provides in-kind or financial support in the form of PhD students, administrative or technical support, and training opportunities.
• The applicants have access to the necessary research infrastructure. 

Research environment 

• The application provides a detailed description of how the team will foster a positive and inclusive research culture. This could include, but is not limited to, information about:
  • career development
  • research practices
  • leadership
  • team composition and partnership
  • appropriate safeguarding measures for team members and collaborators, including people with lived experience
• There is a clear plan on how to manage an integrated collaborative project. 

Ethical, open, equitable and engaged research conduct 

• There is an implementation plan with details about appropriate oversight, governance, monitoring, standard operating procedures and methods for course correction (as needed).
• The team has outlined a detailed description of a suitable outputs management plan.
• There is sufficient information about how the research outputs will be made available to those who need them (for example, policymakers, communities and industry) and in which formats.
• The proposal has details about the relevant ethical, social and cultural implications of the proposed work, and how the study team plans to manage these issues, both in the conduct and oversight of the study and in the communication of its findings. 

4. Lived experience involvement (20%) 

• People with lived experience are meaningfully involved at multiple stages, including the conception, planning, design, delivery and dissemination of the project. There is a clear rationale for their inclusion at each stage. You can access guidance on embedding lived experience expertise in your research.
• Lived experience perspectives are represented across the project, including in leadership and governance roles.
• Lived experience experts have relevant experience and expertise applicable to the research, including being representative of the research location.
• People with lived experience are compensated appropriately for their time.

Information webinar 

We are hosting a webinar on Wednesday 7 May, 13.30 BST. 

Wellcome’s Mental Health team will explain the rationale, objectives and eligibility for this funding call, and answer some attendee questions. You can already submit and upvote questions ahead of the webinar. The webinar will be recorded.

Panel discussion: Longitudinal Datasets in low- and middle-income countries

We recently hosted a panel discussion exploring opportunities for longitudinal mental health research in low- and middle-income countries. Our expert panel discussed advice on approaching mental health research in contexts where it's still taboo, values and challenges of mental health research in low- and middle-income countries and how to encourage building on existing datasets in low- and middle-income countries.

Get involved 

Neuromatch 

To discover potential collaborators for this funding call, we have partnered with Neuromatch which offers free matchmaking services specifically for this call. Using artificial intelligence and a bespoke algorithm, Neuromatch will connect mental health researchers, data scientists and data holders around the world who work in compatible areas and wish to collaborate. Once matched you will be able to contact the matched expert(s) and explore whether a collaboration would be possible. 

The use of Neuromatch is not mandatory for applicants but provides another route to identifying new collaboration opportunities. The deadline to register for the free matchmaking services of Neuromatch is Wednesday 14 May, 23:59 BST. 

Register for Neuromatch matchmaking. 

Scope check 

If you are unclear about whether your proposed idea would be in scope for this call, you can send a very brief summary of your idea (no more than 200 words) by Tuesday 8 July 17.00 BST to mentalhealth@wellcome.org. 

Please include the title of the call (Mental Health Award: Leveraging longitudinal data to transform early intervention in mental health) in the subject line. Use the following format when emailing us your scope question: 

• Early identification objective: [no more than a sentence]
• Longitudinal dataset(s): [no more than a sentence]
• Independent dataset(s) for validation: [no more than a sentence]
• Experimental component(s): [no more than a sentence]
• Mental health condition(s)/symptom(s): [no more than a sentence]
• Summary: [no more than 200 words] 

We will aim to reply to your email within one week, with an 'in scope' or 'out of scope' response based on the information provided. If your summary is more than 200 words we will ask you to reduce the word count. 

Please note that this is not a requirement and will not impact your likelihood of being funded. The confirmation that a proposed idea is in scope does not constitute an active invitation to apply for the call. 

Available resources 

Atlas of Longitudinal Datasets 

The Atlas of Longitudinal Datasets is a free to use, searchable online platform that maps over 1,600 longitudinal datasets from around the world. The Atlas includes data from different sources, including biobanks, cohort studies, registries, and community, village and household panels. You can use it to search for suitable longitudinal datasets. 

Framework for ethical governance of mental health databanks 

Wellcome commissioned and published a report on a framework for ethical governance of mental health databanks. This resource is intended to help data holders and scientists working with databanks to identify and mitigate key ethical considerations related to their use. 

Applicants can use the guidelines of this framework to shape, plan and carry out their work in a way that strives towards more equitable and community-focused outcomes. We encourage all applicants to engage with the section on data analysis, page 38 onwards. 

Guidance and resources on ethical and equitable partnerships 

Applicants should frame their approach to ethical and equitable partnerships as it applies to their research. This could mean partnerships between members of the research team, between researchers in different countries, between researchers and data holders and/or between researchers and research participants. 

The following resources provide guidance on how to approach equitable partnerships in different aspects of a research project: 

• the UKCDR & ESSENCE Equitable Partnerships Resource Hub
• the TRUST Code:
  • A Global Code of Conduct for Equitable Research Partnerships
  • Learning Materials
• consensus statement on measures to promote equitable authorship in the publication of research from international partnerships