Evaluating Participatory Research: How to Show Process, Outcomes and Impact

Co-production & impact · By the Common Inquiry editorial team · Published 2026-10-26

Illustration of a clipboard with a checklist in which every box is ticked, and a blue pen — Evaluation is more than ticking boxes, but a clear checklist helps. Illustration: CC0, via Wikimedia Commons.

Participatory projects are often asked to prove their worth twice: once as research, and once as participation. Funders want impact, communities want change, universities want publications, and everyone wants to know whether the partnership itself was fair. Evaluation can serve all of these purposes if it is planned early and done with partners, not to them.

What to evaluate

The partnership process

Was power shared as intended? Did community partners influence the key decisions? Were meetings accessible, payments timely and disagreements handled fairly? Process matters because participatory research claims that how knowledge is produced affects its validity and its usefulness. Questions can be drawn from the principles the partnership signed up to, such as the principles of co-production or the nine principles of community-based participatory research.

Research quality

Were the methods appropriate and rigorously applied? Are conclusions supported by evidence? Did community involvement improve the questions, recruitment, instruments or interpretation? Reporting tools such as the GRIPP2 checklist, discussed in our article on public involvement in health research, help describe what involvement changed in the research itself.

Outcomes and impact

What changed as a result? Outcomes can be individual (new skills, confidence, employment for community researchers), organisational (a community group's capacity to use data, new services), relational (trust between a community and a university) or policy-level (a council decision, a regulation, funding).

Frameworks that help

The CBPR conceptual model

Nina Wallerstein, Bonnie Duran and colleagues at the University of New Mexico developed a conceptual model of community-based participatory research linking four domains: context, partnership dynamics, research and intervention, and outcomes. Through national studies of partnerships, including the Engage for Equity project, they developed survey instruments that partnerships can use to assess their own dynamics and outcomes. The model is useful because it connects process measures (such as shared decision-making) to outcomes, rather than treating them separately.

Research impact

In the UK, the Research Excellence Framework (REF) assesses university research partly through impact case studies. REF defines impact as an effect on, change or benefit to the economy, society, culture, public policy or services, health, the environment or quality of life, beyond academia. Impact accounted for 20 per cent of the overall assessment in REF 2014 and 25 per cent in REF 2021. Participatory projects often generate strong case studies because partners are, by design, the people who use the research. They also face a difficulty: change often results from many contributions, so attributing it to a single study is hard.

Theory of change

A theory of change sets out, step by step, how the project's activities are expected to lead to outcomes, and the assumptions behind each step. Developing it with community partners at the start makes the evaluation questions explicit and shared.

Practical methods

Method	What it involves	Best for
Partnership self-assessment surveys	Partners rate statements about trust, decision-making and communication, repeated over time	Tracking process and spotting problems early
Most significant change	Collecting stories of change from participants and selecting the most significant ones in group discussion	Unexpected outcomes, community perspectives
Ripple effects mapping	A group session that maps, on a large sheet, the chain of effects that followed from a project	Visualising wider impacts, involving many stakeholders
Outcome harvesting	Working backwards from observed changes in behaviour, policy or practice to assess how the project contributed	Complex settings where outcomes cannot be planned in advance
Realist evaluation	Asking what works, for whom, in what circumstances and why, by testing mechanisms in context	Understanding why similar projects succeed in one place and fail in another
Simple monitoring records	Attendance, payments made, outputs produced, meetings with decision-makers, media coverage	Basic accountability; often neglected

Most significant change was described in a 2005 guide by Rick Davies and Jess Dart; ripple effects mapping was developed in US cooperative extension programmes and described in the Journal of Extension in 2012; outcome harvesting was developed by Ricardo Wilson-Grau and colleagues; realist evaluation by Ray Pawson and Nick Tilley in their 1997 book Realistic Evaluation.

Making evaluation participatory

Agree success criteria together. Community partners may value outcomes, such as a stronger organisation or a changed relationship with the council, that researchers would not think to measure.
Build evaluation into the budget and timetable. Retrospective evaluation, rushed at the end of a grant, misses process data.
Train community members as evaluators. They can collect stories and run sessions, as in the research itself.
Look beyond the grant period. Policy and organisational changes often happen years later. Plan a short follow-up if possible.
Report failures honestly. What did not work is as useful to other partnerships as what did.

Common pitfalls

Counting outputs (reports, events, papers) and calling them impact.
Asking only the academic partners whether the partnership was equitable.
Claiming credit for change that had many causes, which damages trust with partners who did the campaigning.
Using evaluation forms so long that community members stop filling them in.

Small and informal initiatives, such as science shops, need proportionate evaluation: a handful of follow-up conversations with the groups served can tell more than a complex framework.

Sources

Nina Wallerstein et al., "Engage for Equity: a long-term study of community-based participatory research and community-engaged research practices and outcomes", Health Education & Behavior, vol. 47, no. 3, 2020.
Research Excellence Framework, REF 2021 Guidance on submissions, definition of impact.
Rick Davies and Jess Dart, The 'Most Significant Change' (MSC) Technique: A Guide to Its Use, 2005.
Debra Hansen Kollock et al., "Ripple effect mapping: a 'radiant' way to capture program impacts", Journal of Extension, vol. 50, no. 5, 2012.
Ricardo Wilson-Grau, Outcome Harvesting: Principles, Steps, and Evaluation Applications, Information Age Publishing, 2018.
Ray Pawson and Nick Tilley, Realistic Evaluation, Sage, 1997.