IMPORTANCE: To ensure that youths can make informed decisions about their health, it is important that health recommendations be presented for understanding by youths. OBJECTIVE: To compare understanding, accessibility, usability, satisfaction, intention to implement, and preference of youths provided with a digital plain language recommendation (PLR) format vs the original standard language version (SLV) of a health recommendation. DESIGN, SETTING, AND PARTICIPANTS: This pragmatic, allocation-concealed, blinded, superiority randomized clinical trial included individuals from any country who were 15 to 24 years of age, had internet access, and could read and understand English. The trial was conducted from May 27 to July 6, 2022, and included a qualitative component. INTERVENTIONS: An online platform was used to randomize youths in a 1:1 ratio to an optimized digital PLR or SLV format of 1 of 2 health recommendations related to the COVID-19 vaccine; youth-friendly PLRs were developed in collaboration with youth partners and advisors. MAIN OUTCOMES AND MEASURES: The primary outcome was understanding, measured as the proportion of correct responses to 7 comprehension questions. Secondary outcomes were accessibility, usability, satisfaction, preference, and intended behavior. After completion of the survey, participants indicated their interest in completing a 1-on-1 semistructured interview to reflect on their preferred digital format (PLR or SLV) and their outcome assessment survey response. RESULTS: Of the 268 participants included in the final analysis, 137 were in the PLR group (48.4% female) and 131 were in the SLV group (53.4% female). Most participants (233 [86.9%]) were from North and South America. No significant difference was found in understanding scores between the PLR and SLV groups (mean difference, 5.2%; 95% CI, -1.2% to 11.6%; P = .11). Participants found the PLR to be more accessible and usable (mean difference, 0.34; 95% CI, 0.05-0.63) and satisfying (mean difference, 0.39; 95% CI, 0.06-0.73) and had a stronger preference toward the PLR (mean difference, 4.8; 95% CI, 4.5-5.1 [4.0 indicated a neutral response]) compared with the SLV. No significant difference was found in intended behavior (mean difference, 0.22 (95% CI, -0.20 to 0.74). Interviewees (n = 14) agreed that the PLR was easier to understand and generated constructive feedback to further improve the digital PLR. CONCLUSIONS AND RELEVANCE: In this randomized clinical trial, compared with the SLV, the PLR did not produce statistically significant findings in terms of understanding scores. Youths ranked it higher in terms of accessibility, usability, and satisfaction, suggesting that the PLR may be preferred for communicating health recommendations to youths. The interviews provided suggestions for further improving PLR formats. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05358990.

• MeSH
• COVID-19 * prevence a kontrola   MeSH
• hodnocení výsledků zdravotní péče MeSH
• konstruktivní zpětná vazba MeSH
• lidé MeSH
• mladiství MeSH
• průzkumy a dotazníky MeSH
• vakcíny proti COVID-19 MeSH
• Check Tag
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• vakcíny proti COVID-19 MeSH

An evidence-based approach is considered the gold standard for health decision-making. Sometimes, a guideline panel might judge the certainty that the desirable effects of an intervention clearly outweigh its undesirable effects as high, but the body of supportive evidence is indirect. In such cases, the application of the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach for grading the strength of recommendations is inappropriate. Instead, the GRADE Working Group has recommended developing ungraded best or good practice statement (GPS) and developed guidance under which circumsances they would be appropriate.Through an evaluation of COVID-1- related recommendations on the eCOVID Recommendation Map (COVID-19.recmap.org), we found that recommendations qualifying a GPS were widespread. However, guideline developers failed to label them as GPS or transparently report justifications for their development. We identified ways to improve and facilitate the operationalisation and implementation of the GRADE guidance for GPS.Herein, we propose a structured process for the development of GPSs that includes applying a sequential order for the GRADE guidance for developing GPS. This operationalisation considers relevant evidence-to-decision criteria when assessing the net consequences of implementing the statement, and reporting information supporting judgments for each criterion. We also propose a standardised table to facilitate the identification of GPS and reporting of their development. This operationalised guidance, if endorsed by guideline developers, may palliate some of the shortcomings identified. Our proposal may also inform future updates of the GRADE guidance for GPS.

• Klíčová slova
• COVID-19, Evidence-Based Practice,
• MeSH
• COVID-19 * MeSH
• lidé MeSH
• medicína založená na důkazech * MeSH
• výzkumný projekt MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

INTRODUCTION: The COVID-19 pandemic underlined that guidelines and recommendations must be made more accessible and more understandable to the general public to improve health outcomes. The objective of this study is to evaluate, quantify, and compare the public's understanding, usability, satisfaction, intention to implement, and preference for different ways of presenting COVID-19 health recommendations derived from the COVID-19 Living Map of Recommendations and Gateway to Contextualization (RecMap). METHODS AND ANALYSIS: This is a protocol for a multi-method study. Through an online survey, we will conduct pragmatic allocation-concealed, blinded superiority randomized controlled trials (RCTs) in three populations to test alternative formats of presenting health recommendations: adults, parents, and youth, with at least 240 participants in each population. Prior to initiating the RCT, our interventions will have been refined with relevant stakeholder input. The intervention arm will receive a plain language recommendation (PLR) format while the control arm will receive the corresponding original recommendation format as originally published by the guideline organizations (standard language version). Our primary outcome is understanding, and our secondary outcomes are accessibility and usability, satisfaction, intended behavior, and preference for the recommendation formats. Each population's results will be analyzed separately. However, we are planning a meta-analysis of the results across populations. At the end of each survey, participants will be invited to participate in an optional one-on-one, virtual semi-structured interview to explore their user experience. All interviews will be transcribed and analyzed using the principles of thematic analysis and a hybrid inductive and deductive approach. ETHICS AND DISSEMINATION: Through Clinical Trials Ontario, the Hamilton Integrated Research Ethics Board has reviewed and approved this protocol (Project ID: 3856). The University of Alberta has approved the parent portion of the trial (Project ID:00114894). Findings from this study will be disseminated through open-access publications in peer-reviewed journals and using social media. TRIAL REGISTRATION: Clinicaltrials.gov NCT05358990 . Registered on May 3, 2022.

• Klíčová slova
• COVID-19, Knowledge mobilization, Plain language recommendation, Public engagement, Randomized controlled trial, Standard language versions, eCOVID RecMap,
• MeSH
• COVID-19 * MeSH
• dospělí MeSH
• lidé MeSH
• metaanalýza jako téma MeSH
• mladiství MeSH
• průzkumy a dotazníky MeSH
• randomizované kontrolované studie jako téma MeSH
• SARS-CoV-2 MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladiství MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Ontario MeSH

BACKGROUND: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future.

• Klíčová slova
• descriptive epidemiology, methodology, populations/contexts, statistical issues,
• MeSH
• celosvětové zdraví * MeSH
• globální zátěž nemocemi * MeSH
• incidence MeSH
• kvalitativně upravené roky života MeSH
• lidé MeSH
• morbidita MeSH
• naděje dožití MeSH
• rány a poranění * mortalita   MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, N.I.H., Intramural MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH