m+Medelevator.RU
← Поиск публикаций
Journal of clinical epidemiology · 2026

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

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Arienti Chiara, Neumann Ignacio, Akl Elie A, Pinto Bernardo Sousa, Cruz Manuel Marques, Boutron Isabelle, Devane Declan, Whaley Paul, Parmelli Elena, Saulle Rosella, Cinquini Michela, Lazzarini Stefano Giuseppe, Wiercioch Wojtek, Alonso-Coello Pablo, Alper Brian S, Azzam Muayad, Awah Noella, Bala Malgorzata M, Barker Timothy Hugh, Bartolomeos Kidist Kebede, Bognanni Antonio, Brennan Sue S, Bruno Velia, Bruschettini Matteo, Capobussi Matteo, Carrasco-Labra Alonso, Chang Stephanie, Choi Miyoung, Clyne Barbara, Coclite Daniela, Cruciani Fabio, Cuello Carlos, Dahm Philip, Darzi Andrea J, Dewidar Omar, Fei Yutong, Feller Daniel, Gartlehner Gerald, Germini Federico, Glick Michael, Gonzalez-Lorenzo Marien, Hassan Cesare, Khan Haya, Klugar Miloslav, Kredo Tamara, Langendam Miranda, Liang Changhao, Meerpohl Joerg, Minozzi Silvia, Mitrova Zuzana, Moja Lorenzo, Morgano Gian Paolo, Munn Zachary, Mustafa Reem A, Napoletano Antonello, Ngeh Etienne, Nieuwlaat Robby, Nonino Francesco, Yepes-Nuñez Juan José, Ocagli Honoria, Okwen Patrick, Okwen Tetamiyaka, Petri Davide, Piggott Thomas, Piovani Daniele, Poklepovic Tina, Pollock Danielle, Punzo Ornella, Qaseem Amir, Rashidian Arash, Reinap Marge, Ringsten Martin, Rodin Rachel, Ruspi Alessandra, Saif-Ur-Rahman K M, Song Yang, Stern Cindy, Superchi Cecilia, Thomas Rebekah, Van Wyk Susan S, Vieira Rafael J, Wang Rui, Xia Jun, Yao Xiaomei, Xie Yijing, Davoli Marina, Schünemann Holger J, TRUSTGUIDES Collaborative

Аннотация

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.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты