Background. Health guidelines play a central role in informing clinical practice, public health measures and health policy. But their trustworthiness may be undermined by factors such as insufficient methodological rigour, lack of transparency, conflicts of interest (COI), and inconsistent application of established standards. Existing appraisal tools address selected aspects of guideline quality but do not comprehensively assess the trustworthiness of individual recommendations, nor do they adequately reflect recent advances in guideline methodology, including living guidelines, GRADE, adaptation, and the use of artificial intelligence (AI). This study aims to develop and validate TRUSTGUIDES, a globally applicable, flexible tool to assess the trustworthiness of health guideline recommendations.
Methods. TRUSTGUIDES will be developed through a multi-step, mixed-methods process. First, a scoping review and expert consultation will identify existing guideline appraisal tools and inform domain and item generation. Using deductive and inductive approaches, domains and items will be generated, and may be refined through focus groups and selected through iterative Delphi surveys involving an international, multidisciplinary working group. The tool will be validated by assessing internal consistency, inter-rater reliability, content validity, and construct validity, including comparisons with established instruments such as the GRADE certainty domains, AGREE II and PANELVIEW. Psychometric properties will be examined using factor analysis and item response theory models as necessary. AI will be integrated both as an object of assessment and as methodological support for tool application, with large language models evaluated against a human reference standard.
Discussion. The TRUSTGUIDES tool will be designed to evaluate the trustworthiness of individual guideline recommendations across key factors, including transparency and independence, and address relevant domains such as the certainty of evidence, strength of recommendations, COI, applicability, adaptability, currency, certification and appropriate use of AI. Validation analyses are expected to demonstrate acceptable reliability, strong content validity, and meaningful correlations with existing appraisal instruments, while enabling scalable, AI-assisted assessments. TRUSTGUIDES addresses critical gaps in current guideline appraisal by offering a comprehensive, recommendation-level assessment of trustworthiness aligned with World Health Organisation criteria. Its integration of AI positions the tool to support efficient, transparent, and future-ready guideline evaluation in an evolving health evidence ecosystem.
ARIENTI Chiara;
NEUMANN Ignacio;
AKL Elie;
SOUSA-PINTO Bernardo;
MARQUES CRUZ Manuel;
BOUTRON Isabelle;
DECLAN Devane;
WHALEY Paul;
PARMELLI Elena;
SAULLE Rosella;
CINQUINI Michela;
LAZZARINI Stefano Giuseppe;
WIERCIOCH Wojtek;
ALONSO-COELLO Pablo;
ALPER Brian;
AZZAM Muayad;
AWAH Noella;
BALA Malgorzata;
BARKER Tim;
KEBEDE BARTOLOMEOS Kidist;
BOGNANNI Antonio;
BRENNAN Sue S;
BRUNO Velia;
BRUSCHETTINI Matteo;
CAPOBUSSI Matteo;
CARRASCO Alonso;
CHANG Stephanie;
CHOI Miyoung;
COCLITE Daniela;
CRUCIANI Fabio;
CUELLO Carlos;
DHAM Philipp;
DARZI Andrea;
DEWIDAR Omar;
FEI Yutong;
FELLER Daniel;
GARTLENHER Gerald;
GERMINI Federico;
GLICK Michael;
GONZALO-LORENZO Marien;
HASSAN Cesare;
KHAN Haya;
KLUGAR Miloslav;
KREDO Tamara;
LANGENDAM Miranda;
LIANG Chang-Hao;
MEERPHOL Joerg J.;
MINOZZI Silvia;
MITROVA Zuzana;
MOJA Lorenzo;
MORGANO Gian Paolo;
MUNN Zachary;
MUSTAFA Reem;
NAPOLETANO Antonello;
NGEH Etienne;
NIEUWLAAT Robby;
NONINO Francesco;
YEPES NUNEZ Juan Jose;
OCAGLI Honoraria;
OKWEN Patrick;
OKWEN Tetamyaka;
PETRI Davide;
PIGGOTT Thomas;
PIOVANI Daniele;
POKLEVIC Tina;
POLLOCK Danielle;
PUNZO Ornella;
QASEEM Amir;
HAJIKHANI Arash;
REINAP Marge;
RINGSTEN Martin;
RODIN Rachel;
RUSPI Alessandra;
SAIF-UR-RAHMAN Km;
SONG Yang;
STERN Cindy;
SUPERCHI Cecilia;
THOMAS Rebeka;
SUSAN Van Wyk;
JOSÉ VIEIRA Rafael;
WANG Rui;
XIA Jun;
YAO Xiaomei;
XIE Yijing;
DAVOLI Marina;
SCHUNEMANN Holger;
CLYNE Barbara;
2026-09-24
ELSEVIER SCIENCE INC
JRC145444
1878-5921 (online),
https://www.sciencedirect.com/science/article/pii/S0895435626002234,
https://publications.jrc.ec.europa.eu/repository/handle/JRC145444,
10.1016/j.jclinepi.2026.112348 (online),
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