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Added: May 26, 2026
Updated: June 1, 2026
The NIHR is committed to FAIR (Findability, Accessibility, Interoperability, and Reusability) data practices. In order to support this from March 2023, NIHR applicants and award holders are required to submit and update Data Access Management Plans (DAMPs) as part of contract set up and monitoring. The aim of completing a DAMP is to encourage greater attention to data integrity, management and accessibility: how data is collected, organised, secured and shared for long-term reuse across NIHR and beyond. The aim of this project was to explore the usability and effectiveness of NIHR DAMPs. To do this we undertook an analysis and process evaluation of 968 DAMPs which involved descriptive and qualitative content analysis of sections on the form. Overall completion of form sections was high (79%) providing helpful insights into NIHR funded data; however responses were inconsistent and repetitive (see added abstracts). Overall, DAMPs effectively help researchers plan for and maintain FAIR data practices. The form can be improved by replacing some open questions with standard responses and by providing more guidance on completing specified questions. This work represents the continuous efforts of NIHR to promote open research while reducing bureaucracy and improving researcher support.
Added: January 15, 2026
Updated: January 16, 2026
The effective distribution of funds to sustain a productive and healthy research system is a key concern of funders and institutions. To achieve this, governments and research funders commission reviews and set out strategies examining micro- and macro-determinants of research productivity. An important yet often overlooked factor in these reviews is research group structure. Large-scale quantitative bibliometric studies and small-scale qualitative studies of research collaborations and research group characteristics support the idea that organisational structure can affect the research produced.
However, while bibliometric approaches are powerful for exploring academic collaboration patterns based on authorship lists, authorship lists may deviate from actual research group membership. Conversely, although this problem may be less present in qualitative studies, qualitative studies are unable to cover a wide and diverse range of groups and to scale their insights.
In our research, we develop a unique approach to exploring the relationship between organisational structure and research output, by combining administrative, bibliometric, and qualitative data, covering both macro- (across entire institutions) and micro- (individual researchers’ experiences) level information, across two research institutions (the University of Cambridge and Université de Montréal). Unlike previous studies, we will use institutional administrative data to accurately define research groups and their composition and supplement it with bibliometric data to explore how the organisational structure of research groups (devolved/hierarchical, networked/isolated, small/large), structural dynamics (churn and growth rates) and demographics mixtures, relate to the groups’ research outputs, impact, and productivity.
Added: December 18, 2025
Updated: December 19, 2025
TBC
Added: November 18, 2025
Updated: December 12, 2025
Background: Editorial board members of leading orthopaedic journals play a key role in shaping scientific standards and publication decisions. However, little is known about the quality and characteristics of their own research output.
Objective: To evaluate the scientific productivity and publication quality of editors and editors-in-chief from major orthopaedic and traumatology journals.
Methods: We manually identified editorial board members from high-impact orthopaedic journals and retrieved their publication records from Web of Science. Bibliometric indicators—including total publications, citations, h-index, and journal impact—were extracted and analyzed.
Expected Outcomes: This meta-research study will provide an overview of the evidence base generated by those who influence editorial decisions, offering insight into research quality, potential disparities, and publication patterns within the orthopaedic community.
Added: November 7, 2025
Updated: December 12, 2025
A search for clinical trials was conducted in four different registries in a retrospective cohort study. Nontherapeutic studies, trials based on rehabilitation or anesthesia, or studies that had not completed recruitment and analysis before 2022 were excluded. The studies were classified according to their topic of interest, status in the registry, and funding. The sample size and study methods were also documented.
The existence of an indexed publication in PubMed and EMBASE was verified, along with the final sample size included and the type of study. The corresponding authors of unpublished studies were contacted to explore the fate of the research project. The reasons for trial discontinuation were registered.
Added: October 7, 2025
Updated: February 20, 2026
The project consists of 5 different phases in which we ultimately aim to develop an internal Large Language Model.
These 5 different phases consist of:
1. Setup & Scope - Define the classification criteria, validate keywords, select project summaries
2. Baseline - label projects to create a diverse gold standard
3. Pilot Runs in Azure AI Foundry that are run on selected summaries and validated against the gold standard
4. Evaluation & Iteration - Compare Foundry output vs. baseline
5. Scaling & Reporting - Apply to full dataset. If succesful, test generalizability
Added: August 26, 2025
Updated: February 20, 2026
Obstructive sleep apnea (OSA) is highly prevalent and associated with adverse cardiovascular and metabolic outcomes. CPAP therapy is effective but long-term adherence is poor. While standard coaching improves outcomes, sustained adherence remains a challenge. Remote patient monitoring (RPM) platforms may provide an innovative method to improve adherence through continuous feedback, patient engagement, and structured escalation pathways. This randomized controlled trial will evaluate whether adding the MonitAir RPM platform to the standard-of-care program provided by BetterNight improves CPAP adherence and patient satisfaction over 90 days.
Added: April 7, 2025
Updated: December 12, 2025
The NIHR Reviewer Development Scheme (RevDS) and Committee Member Development Scheme (CMDS) are for early career researchers and health and social care professionals who are new to reviewing or want to develop their skills further. The RevDS offers the opportunity to gain experience of peer reviewing full research applications for NIHR funding programmes. In addition, each year, all scheme members are invited to apply for a limited number of one- year mentored NIHR CMDS roles. This opportunity provides experience of NIHR funding committees and research funding allocation decision making.
The aim of this project was to evaluate the schemes to better understand the benefits and impacts, facilitators and barriers and key areas of improvement, as well as to determine what data should be routinely collected to demonstrate the benefits of the schemes.
This project had three connected stages: (1) analysis of existing monitoring and feedback data; (2) collection of new data from a survey with current NIHR committee members; and (3) development of a programme theory.
Analysis of existing data and development of programme theories demonstrated that the Reviewer and Committee Member Development schemes have a number of outcomes that benefit scheme members, NIHR committee members, and the NIHR. However, it also identified some areas of improvement that need to be addressed to ensure the schemes meet their full potential.
Added: April 4, 2024
Updated: December 12, 2025
As part of the implementation of the NIHR Research Inclusion strategy 2022-2027 , the NIHR has developed a Disability Framework to guide the organisation in ensuring that disabled people are empowered to fully engage with the NIHR across all of its research funding activities (e.g., application, decision-making, reporting, administration and management). To inform the framework, and to avoid assumptions relating to barriers individuals are facing, we conducted a study to understand the experiences of disabled people when engaging with NIHR, and the challenges that may have hindered or prevented successful engagement. Engaging with a wide range of NIHR stakeholders through an anonymous online survey and focus groups, we identified good practice as well as barriers at NIHR, leading to recommendations for improvement to access and inclusion. These recommendations were incorporated into the NIHR Disability Framework which was published in March 2024.
Added: March 20, 2024
Updated: December 12, 2025
Last year, the education department of Hasselt University published the first version of the UHasselt Framework on using Generative Artificial Intelligence (GenAI). Along with an update of this initial framework, we want to expand the generic guidelines with an overview of GenAI tools for specific research purposes used at the institution.