Assessing the trustworthiness of health guidelines recommendations: the transparent, rigorous, useable, standardized, and trustworthy guide (TRUSTGUIDES) tools development

Background and Objectives 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 rigor, lack of transparency, conflicts of interest, 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, Grading of Recommendations, Assessment, Development, and Evaluation, adaptation, and the use of artificial intelligence (AI). This study aims to develop and validate Transparent, Rigorous, Useable, Standardized, and Trustworthy Guide (TRUSTGUIDES), a globally applicable, flexible set of tools to assess the trustworthiness of health guideline recommendations. We define trustworthiness as distinct from methodological quality: it encompasses not only rigorous methods but also transparency, independence, and applicability, which together determine whether a recommendation merits user confidence. Methods TRUSTGUIDES will be developed through a multistep, mixed-methods process. First, a scoping review and expert consultation will identify existing guideline appraisal tools and inform domains and items 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. TRUSTGUIDES will be validated by assessing internal consistency, inter-rater reliability, content validity, and construct validity, including comparisons with established instruments such as the Grading of Recommendations, Assessment, Development, and Evaluation certainty domains, AGREE II, and PANELVIEW. Psychometric properties will be examined using factor analysis and, as necessary, item response theory models. 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. Conclusion TRUSTGUIDES will be designed to evaluate the trustworthiness of individual guideline recommendations across key factors, including transparency and credibility, and to address relevant domains such as the certainty of evidence, strength of recommendations, conflicts of interest, applicability, adaptability, currency, certification, and the appropriate use of AI. TRUSTGUIDES addresses critical gaps in current guideline appraisal by offering a comprehensive, recommendation-level assessment of trustworthiness aligned with the World Health Organization guideline standard methodology. By integrating AI, our tools will support efficient, transparent, and future-ready guideline evaluation within an evolving health evidence ecosystem.