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Added: December 18, 2025
Updated: December 18, 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 The corresponding authors of unpublished studies were contacted to explore the fate of the research project.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: October 7, 2025
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: December 11, 2025
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.
Added: March 10, 2024
Updated: December 12, 2025
The frequency and cognizance of withdrawals and retractions (WAR) have been increasing across science. However, no work so far has evaluated the frequency and causes of WAR of Cochrane systematic reviews, which impact policy and practice globally. A retrospective meta-scientific study of Cochrane systematic reviews, published during 1996-2023, that were marked as WAR, was retrieved from PubMed. Data was extracted with independent review and validation related to year of publication, country, editorial group, World Bank income classification of country of co-authors, and listed reasons for WAR. Protocols were excluded. We found that outdated articles and authors' unavailability for updates were common reasons for WAR. This research sheds light on maintaining the reliability of evidence in healthcare.
Added: March 2, 2024
Updated: December 12, 2025
Purpose
Bar charts of numerical data, often known as dynamite plots, are unnecessary and misleading. Their tendency to alter the perception of mean’s position through the within-the-bar bias and their lack of information on the distribution of the data are two of numerous reasons. The machine learning tool, Barzooka, can be used to rapidly screen for different graph types in journal articles.
We aim to determine the proportion of original research articles using dynamite plots to visualize data, and whether there has been a change in their use over time.
Methods
Original research articles in nine surgical fields of research were sampled based on MeSH terms and then harvested using the Python-based biblio-glutton-harvester tool. After harvesting, they were analysed using Barzooka. Over 40 000 original research articles were included in the final analysis. The results were adjusted based on previous validation data with 95% confidence bounds. Kendall τ coefficient with the Mann–Kendall test for significance was used to determine the trend of dynamite plot use over time.
Results
Eight surgical fields of research showed a statistically significant decrease in use of dynamite plots over 10 years. Oral and maxillofacial surgery showed no significant trend in either direction. In 2022, use of dynamite plots, dependent on field and 95% confidence bounds, ranges from ~30% to 70%.
Conclusion
Our results show that the use of dynamite plots in surgical research has decreased over time; however, use remains high. More must be done to understand this phenomenon and educate surgical researchers on data visualization practices.