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Related Concept Videos

Case Studies01:22

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Related Experiment Video

Updated: Apr 3, 2026

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Co-producing data-intensive research with an underserved group: a case study and evaluation identifying pathways to

Sarah McKenna1, Ash Salem2,3, Esla Ibrahim2

  • 1Administrative Data Research Centre Northern Ireland (ADRC NI), Centre for Public Health, Queen's University Belfast, Institute of Clinical Sciences B, Royal Hospitals Site, Belfast, BT12 6BJ.

International Journal of Population Data Science
|April 2, 2026
PubMed
Summary
This summary is machine-generated.

Co-production in data research with care-experienced youth improved outcomes. Genuine power-sharing and valuing diverse knowledge were key enablers, highlighting the need for tailored support and systemic changes for inclusive research.

Keywords:
administrative dataco-productionunderserved groups

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Area of Science:

  • Social Sciences
  • Public Health
  • Data Science

Background:

  • Co-production enhances research quality and relevance by involving experts by experience as equal partners.
  • Limited evidence exists on successful co-production methods in data-intensive research, particularly with underserved populations.

Purpose of the Study:

  • To report the impact of a co-production approach in a pilot study using linked administrative data.
  • To assess the mechanisms of co-production against established principles.
  • To determine if co-production in this context requires bespoke guidance.

Main Methods:

  • A case study evaluated a co-production pilot involving care-experienced young people and administrative data.
  • Data were collected via participatory workshops and semi-structured interviews.
  • Deductive thematic analysis and mapping against NIHR principles were used.

Main Results:

  • Co-production yielded positive impacts for individuals, research, and organizations.
  • Barriers included representativeness and resource constraints, with unique challenges in data-intensive research (e.g., power-sharing vs. data access).
  • Enablers were genuine power sharing, valuing diverse knowledge, and partnership working.

Conclusions:

  • The case study offers a model for co-production with underserved groups in data-intensive research.
  • Successful embedding requires systemic changes: tailored guidance, resources, and flexible funding models.
  • Partnerships with voluntary organizations foster inclusive, trauma-informed approaches.