Wellcome Mental Health Data Prize

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The Wellcome Data Prize in Mental Health is an opportunity for collaborative approaches for research into anxiety and depression in young people. The Prize supports multi-disciplinary teams to produce a digital tool to enable future research. 

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The Wellcome Data Prize in Mental Health is an opportunity for collaborative approaches for research into anxiety and depression in young people. The Prize supports multi-disciplinary teams to produce a digital tool to enable future research. 

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About this prize

The Prize aims to generate tangible and scalable outputs that support the mental health research community. The overarching question for the Data Prize is:

What are the ‘active ingredients’ that make a difference in preventing, treating, and managing anxiety and depression in young people? What works, for whom, in what contexts, and why?

'Active ingredients' are those aspects most likely to make a difference in preventing, treating or managing mental health difficulties. This means they:

  • drive clinical effect
  • are conceptually well-defined, and
  • link to specific, hypothesised mechanisms of action.
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Scope of proposals

Applicants must submit a research question in an area of their interest. Then, the successful awardees will explore existing datasets to help answer that question while developing their analysis tool.

Proposals will be evaluated on impact, innovation and feasibility. Key considerations also include the breadth of skills within teams and how teams plan to involve lived experience of youth anxiety and depression throughout their work.

Analysis does not need to be limited to the 46 active ingredients where we have previously commissioned research and can be on aspects of any intervention most likely to be contributing to making the difference in preventing, treating, or managing ongoing mental health difficulties.

Primary research is out of scope and proposals should not intend to perform primary data collection.

By the end of the award, teams will have produced:

  • a digital tool to facilitate data analysis in the mental health research community, and
  • the analysis of the datasets they explored.

Prize structure

There are three phases to the prize, with only a subset of teams from each phase progressing to the next:

1. Discovery Phase (10 teams)

  • Participants will be directed to core longitudinal datasets from the UK and South Africa, and can bring their own data where relevant.
  • Teams will produce an analysis of existing data to answer a research question.
  • Teams will be supported with data acquisition, and refining use cases (further examination of how, why and where the digital tool they develop could be used) as well as lived experience involvement approaches.

2. Prototyping Phase (5 teams)

  • Teams will create a prototype of a digital tool, and they will also refine and disseminate their research from the discovery phase.
  • Teams will be supported with further developing use cases, lived experience involvement approaches and workshops on agile principles and prototyping.

3. Sustainability Phase (3 teams)

  • Support includes data science and product design expertise, support on planning user testing and lived experience involvement approaches and continuous feedback sessions.

What do we mean by digital tools?

Tools will build on insights formed in the Discovery phase.

The primary users of these tools will be mental health researchers with the purpose of enabling research into active ingredients, those aspects of an intervention that drive a clinical effect.

Many types of tools could be developed in the prize and we will accept prototypes as an output.

Below are the types of tools that are considered in scope for the Prize.

  • Tools helping researchers to perform data analysis, for example a tool that can identify clusters of individuals who respond to specific interventions or active ingredients, or a tool that determines which factors can predict relapses.
  • Tools used to replicate data analysis, by making available the mechanism by which data is translated into research insights, for example, a new application of a machine learning algorithm that can be used on other datasets.
  • Tools that share the insights from data analysis, in a format accessible and digestible for multiple audiences, for example, a triaging tool for researchers that can highlight the active ingredients that work for different groups of young people.
  • Tools that facilitate data analysis by addressing barriers to conducting research, for example, tools that support data cleaning and manipulation or automatically extract relevant data from longitudinal datasets.

Please note this list is not exhaustive and serves only as a guideline for what may be developed.

Tools considered out of scope would be:

  • Tools based on insights from data but not directly linked to data itself, for example, analysis shows that certain interventions are effective leading to a tool connecting individuals that use that intervention.
  • Apps aimed at individuals, for example, condition management, mood tracking, sleep/exercise monitoring apps or a digital tool that supports people directly with navigating existing services for themselves.

Teams do not necessarily need to pursue the same digital tool as proposed in the application, particularly if the need for the tool evolves as a result of the analysis performed. We encourage teams to incorporate their learnings from the discovery phase into the digital tool they ultimately develop.  

Data

Teams can propose their own datasets as research data, with the potential gain of opening them for analysis from a range of expertise after the prize.

Participating teams can bring their own data, so long as they meet the following criteria:

  • data is longitudinal (minimum three waves)
  • cohorts are children and young people (CYP) below the age of thirty and from the UK or South Africa
  • datasets must include data from at least one validated and age-appropriate measure of depression and/or anxiety, or a related construct (e.g. internalising symptoms), used in individuals under 30 in at least 3 longitudinal waves of data collection
  • includes variables that provide information on active ingredients across multiple categories (for example, this would include categories like behaviours and activities; brain and body functions; socioeconomic factors)
  • they have been given access to the data from data holders before the prize application deadline.

In addition to this, a selection of longitudinal datasets from the UK and South Africa will be proposed as appropriate ‘core’ research data to participants, with streamlined access to these datasets facilitated where appropriate.

These core datasets are longitudinal research studies and have been selected as they contain rich data that has the potential to provide new insights on active ingredients. Examples of these datasets are the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Millennium Cohort Study.

Within their proposals, participants must be able to demonstrate both that their dataset is:

  • appropriate for their research question and/or tool
  • and that they have gained appropriate access to use this data within the prize.

If applicants have access to a dataset that does not meet all of the criteria above but provides other added value to address the research question set out, please contact us at dataprize@socialfinance.org.uk so we can assess on a case-by-case basis.

Teams that bring their own data must be prepared to share the insights they have found along with relevant data, in line with Wellcome’s open access policy

Intellectual property (IP)

The IP developed with Wellcome’s funding should be owned by the organisation with principal responsibility for administering the grant. That notwithstanding, the IP should be made available publicly on an appropriate open-source software licence in line with Wellcome’s grant conditions.

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About you

A key aim of this prize is to build a multidisciplinary mental health data community by bringing together people with mental health research backgrounds and data expertise.  By mental health science we mean any discipline that uses evidence in rigorous and transparent ways, whether based on observation or experimentation. This could include:

  • psychiatry
  • psychology
  • neuroscience
  • disciplines within the humanities, social sciences and computer sciences, among others.

We also welcome early career researchers.

We understand that groups may want to apply but feel they require additional skillsets, and we will actively support the formation of teams where possible by connecting expertise to those with similar interests and aims across organisations.

For applicants who do not yet have a full multi-disciplinary team, Social Finance will be coordinating opportunities to form connections with other interested organisations. Please sign up to the mailing list to find out more about these events. 

Please see the eligibility criteria below for further information on who can apply.

Eligibility Criteria

Lead applicants:

  • must be based in the UK or South Africa.
  • may be at any career stage but must have a permanent, open-ended or long-term rolling contract, or the guarantee of one for the full duration of the award.

Lead applicants must be based at an eligible host organisation that can sign up to our grant conditions.

Only the lead applicant from each team needs to be based in the UK or South Africa

Lead applicant organisations should be either:

  • a higher education institution
  • a research institute
  • a non-academic healthcare organisation
  • a not-for-profit organisation.

Co-applicants:

  • can be at any career stage and based anywhere in the world, apart from mainland China.
  • can be self-employed, e.g. a freelance data scientist (as well as employed by the usual range of host organisations below).

Co-applicants must be based at an eligible organisation that can sign up to our grant conditions.

Co-applicants organisations should be either:

  • higher education institution
  • research institute
  • non-academic healthcare organisation
  • not-for-profit organisation
  • commercial organisation.
  • freelancers – such as data scientists

All applicants must agree to our standard grant conditions.

All applicants must make a significant and essential contribution to the work.

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There are three phases to the prize, each six months long and with different levels of funding and support on offer:

  • Discovery Phase: an initial 10 teams will be selected to receive £40,000 of funding.
  • Prototyping Phase: five teams from the Discovery Phase will receive £100,000.
  • Sustainability Phase: three winning teams will receive £500,000.

Throughout the prize, teams will be supported with data access, analysis and use case development as well as support on planning lived experience involvement approaches.

There will also be regular group activities such as problem-solving sessions and theory of change workshops.

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Teams will apply with a written proposal and shortlisted teams will be asked to present their proposals to a panel.

The full details on how to apply will be added here when the prize opens in April 2022. Applications will be open until June.

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Wellcome Data Prizes
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Anxiety and depression in young people: finding the next generation of treatments and approaches
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Report: What science has shown can help young people with anxiety and depression
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Wellcome Mental Health Data Prize | Wellcome
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The Wellcome Data Prize in Mental Health is an opportunity for collaborative approaches for research into anxiety and depression in young people. The Prize supports multi-disciplinary teams to produce a digital tool to enable future research. 
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Funding amount

There are three phases to the prize, each six months long and with different levels of funding and support on offer:

  • Discovery phase: 10 teams will be selected to receive £40,000 of funding 
  • Prototyping phase: 5 teams will be selected to receive £100,000 of funding 
  • Sustainability phase: £500,000 will be allocated across 3 winning teams
Funding duration

6-18 months

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