ArticlePloS one2026
A peer-review decision support tool for research funding decision-making using the analytic hierarchy process.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundResearch funding is a crucial driver of healthcare innovation and improved patient outcomes. However, the peer-review process utilised during funding allocation is often subjective, inconsistent, and prone to reviewer biases, leading to inefficiencies in selecting high-impact projects. This study aimed to develop an objective, transparent, and structured scoring system to improve research funding decisions.
methodsA mixed-methods approach was used, incorporating a scoping review, surveys, Delphi methodology, and the analytic hierarchy process (AHP). The scoping review identified funding criteria used by national and international agencies. A survey of researchers and decision-makers at the Royal Hospital in Muscat, Oman, gathered insights into funding priorities. Experts refined and validated criteria using the Delphi method, while weighted importance to each criterion as per the AHP was assigned through pairwise comparisons.
resultsThe study identified 10 key criteria for funding decisions: scientific merit, ethical standards, novelty and innovation, significance and strategic alignment, feasibility, impact and knowledge transfer, budget and cost-efficiency, team expertise and collaboration, sustainability, and partnerships in funding. Based on AHP weighting, the final model prioritised Ethical Standards (21.7%), Scientific Merit (19.1%), and Novelty and Innovation (16.7%) as the highest-weighted criteria, together accounting for more than half of the overall decision weight.
conclusionThe proposed scoring model provides a structured, evidence-based framework to enhance research funding decisions by enhancing consistency and transparency during peer review. It ensures alignment with institutional and national research priorities, while the inclusion of impact, feasibility, and sustainability criteria reflects a shift towards funding research that yields tangible societal and healthcare benefits. Future studies should evaluate implementation of the model in real-world settings and explore the role of artificial intelligence-driven decision-support tools to further refine research funding processes.
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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.