ArticleHealth expectations : an international journal of public participation in health care and health policy2025
Co-Production and Implementation of 'Count Me In': A Bottom-Up Approach to Inclusive Research and Participation in a National Health Service in England.
Article in Health expectations : an international journal of public participation in health care and health policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Co-Production With Mental Health Family Carers: The Value, Outcomes and Benefits for Family Carers and Academic Researchers.Health expectations : an international journal of public participation in health care and health policy · 2026Article
- Challenges and solutions to participation in mental health clinical trials: Count Me In 2.0.BMJ mental health · 2026Article
- Telehealth to reduce compound pressures on the National Health Service and social care: a multi-methods study protocol.Oxford open digital health · 2026Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundResearch-active National Health Service (NHS) services are linked to better care quality and health outcomes. However, traditional research participant recruitment methods, such as 'opt-in' strategies, often face challenges in reaching diverse populations. The 'Count Me In' (CMI) system was introduced to address these barriers through an 'opt-out' model, aiming to normalise research participation and promote inclusivity. At Mersey Care NHS Foundation Trust, a bottom-up approach was employed to adapt CMI, ensuring meaningful engagement with service users, carers and communities in its design and implementation.
methodsCMI was co-produced with stakeholders through a series of workshops, discussion groups and consultations with over 300 participants, including service users, carers and NHS staff. Key activities included listening exercises to understand concerns, co-designing campaign materials and forming a Patient and Public Involvement and Engagement (PPIE) Advisory Group. The group provided ongoing guidance to ensure that the system aligned with the needs of underserved communities and upheld ethical and cultural sensitivity.
findingsStakeholders widely supported the 'opt-out' approach, recognising its potential to improve research inclusivity. Participants highlighted the importance of clear communication, cultural sensitivity and robust data protection measures. Specific research priorities, such as mental health and social isolation, were identified. Co-produced materials, including plain-language guides and culturally appropriate visuals, addressed concerns about privacy, stigma and accessibility, fostering trust and confidence in the system.
conclusionThe CMI system is an acceptable and scalable model for inclusive research recruitment, embedding research into routine care. The bottom-up approach ensured the system was tailored to local needs, promoting equity and accessibility. PATIENT AND PUBLIC CONTRIBUTION: A partnership approach working with PPIE leads at the Mental Health Research for Innovation Centre (M-RIC) ensured that service users, carers and community members shaped the CMI system through extensive co-production activities. The development of the system, therefore, reflected their lived experiences and priorities, thereby enhancing its inclusivity and impact.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.