Cochrane Evidence Synthesis and Methods最新文献

{"title":"A scoping review: Screening questionnaires for identifying tanning addiction","authors":"John Meisenheimer,&nbsp;Michelle Sobotka,&nbsp;Ronald Yang,&nbsp;Robert P. Dellavalle","doi":"10.1002/cesm.12092","DOIUrl":"https://doi.org/10.1002/cesm.12092","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>There is a growing body of evidence that ultraviolet (UV) tanning, whether practiced in indoor tanning salons or outdoors in the sun, is not only linked to detrimental health outcomes but is also addictive through both psychological and physiological mechanisms. In clinical practice, it can be challenging to determine which patients will continue tanning despite being at high risk for developing skin cancer. Our study seeks to identify all available screening questionnaires for tanning addiction that could be used in clinical practice and report on published measures of validity for each screening questionnaire.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An exhaustive literature search of EMBASE, PubMed, PsycINFO, and Scopus was performed using search criteria including the concepts “UV” and “Addiction.” The most recent search was performed in March 2024 and included all articles from database inception to the time of the search. Studies were included if they reported on screening questionnaires for UV addiction. Articles were excluded from the study if they did not report primary data or did not report on measures of questionnaire validity. Methodology was created using best practices for scoping reviews.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>After identifying 171 articles, 106 articles underwent full-text review, and 26 were included in data extraction. We identified nine questionnaires for tanning addiction, with the modified Cut-down, Annoyed, Guilty, Eye-opener (mCAGE), and modified Diagnostic and Statistical Manual of Mental Disorders (mDSM) being most frequently reported on, and the Behavioral Addiction Indoor Tanning Screener (BAITS) being the most promising for future use.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This information should be used to choose questionnaires to be studied against a “gold-standard” of a panel of psychologists. After defining accuracy of diagnostic tests, studies can be designed to examine interventions for treating tanning addiction, so at-risk patients can receive specialized therapy, reducing the overall burden of skin cancers.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141488519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world evaluation of interconsensus agreement of risk of bias tools: A case study using risk of bias in nonrandomized studies-of interventions (ROBINS-I)","authors":"Samer Saadi,&nbsp;Bashar Hasan,&nbsp;Adel Kanaan,&nbsp;Mohamed Abusalih,&nbsp;Zin Tarakji,&nbsp;Mustafa Sadek,&nbsp;Ayla Shamsi Basha,&nbsp;Mohammed Firwana,&nbsp;Zhen Wang,&nbsp;M. Hassan Murad","doi":"10.1002/cesm.12094","DOIUrl":"https://doi.org/10.1002/cesm.12094","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Risk of bias (RoB) tools are critical in systematic reviews and affect subsequent decision-making. RoB tools should have adequate interrater reliability and interconsensus agreement. We present an approach of post hoc evaluation of RoB tools using duplicated studies that overlap systematic reviews.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using a back-citation approach, we identified systematic reviews that used the Risk Of Bias In Nonrandomized Studies-of Interventions (ROBINS-I) tool and retrieved all the included primary studies. We selected studies that were appraised by more than one systematic review and calculated observed agreement and unweighted kappa comparing the different systematic reviews' assessments.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified 903 systematic reviews that used the tool with 51,676 cited references, from which we eventually analyzed 171 duplicated studies assessed using ROBINS-I by different systematic reviewers. The observed agreement on ROBINS-I domains ranged from 54.9% (missing data domain) to 70.3% (deviations from intended interventions domain), and was 63.0% for overall RoB assessment of the study. Kappa coefficient ranged from 0.131 (measurement of outcome domain) to 0.396 (domains of confounding and deviations from intended interventions), and was 0.404 for overall RoB assessment of the study.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>A post hoc evaluation of RoB tools is feasible by focusing on duplicated studies that overlap systematic review. ROBINS-I assessments demonstrated considerable variation in interconsensus agreement among various systematic reviewes that assessed the same study and outcome, suggesting the need for more intensive upfront work to calibrate systematic reviewers on how to identify context-specific information and agree on how to judge it.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12094","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141488174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to present an informative summary of findings table for systematic reviews of interventions: A tutorial","authors":"Jennifer Hilgart,&nbsp;Clare Miles,&nbsp;Jo-Ana Chase","doi":"10.1002/cesm.12093","DOIUrl":"https://doi.org/10.1002/cesm.12093","url":null,"abstract":"<p>This tutorial provides guidance on creating clear and informative summary of findings tables for systematic reviews of interventions.</p>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141435607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equity in evidence synthesis: You can't play on broken strings","authors":"Tamara Lotfi,&nbsp;Vivian Welch,&nbsp;Jordi P. Pardo,&nbsp;Jennifer Petkovic,&nbsp;Shaun Treweek,&nbsp;Andrea J. Darzi,&nbsp;Rebecca Glover,&nbsp;Declan Devane,&nbsp;Meera Viswanathan,&nbsp;Lawrence Mbuagbaw,&nbsp;Kevin Pottie,&nbsp;Elizabeth Kristjansson,&nbsp;Shahab Sayfi,&nbsp;Lara Maxwell,&nbsp;Olivia Magwood,&nbsp;Damian Francis,&nbsp;Dru Riddle,&nbsp;Beverly Shea,&nbsp;Peter Tugwell","doi":"10.1002/cesm.12091","DOIUrl":"https://doi.org/10.1002/cesm.12091","url":null,"abstract":"<p>In the 2022 Cochrane Lecture [<span>1</span>], Jimmy Volmink, recognized as a pioneer of evidence-based medicine in Africa, challenged Cochrane to enhance its equity efforts and suggested five ways to do so. We, as members of the Campbell and Cochrane Health Equity Thematic group*, fully agree with his suggestions and have developed an actionable plan, described below. We invite the global community to join us in our efforts to meet the equity gaps in research and practice.</p><p>Population health and healthcare delivery should be equitable and the research that guides it equity sensitive. By this, we mean that we need to focus on the distribution of health outcomes in the population not just overall health. That is, people should have equal opportunities for health and are not subjected to systemic discrimination or structural barriers to health. It is an ambitious goal and one that many of us who work in healthcare delivery and health research are striving for.</p><p>This includes those of us who work in evidence synthesis. Synthesizers of other researchers' evidence may think that our handling of equity cannot be better than the handling of equity in the research we synthesize. We, as members of the Campbell and Cochrane Health Equity Thematic Group, disagree. To truly address inequity, evidence synthesis must take into account equity considerations in a systematic and explicit manner, regardless of how equity was addressed in the original research. We believe that evidence synthesis should lead the way in promoting equity, rather than simply reflecting the approaches taken in the primary research that is included in our reviews (Box 1).</p><p>We fully agree that Cochrane cannot succeed in better addressing health equity in systematic reviews without also addressing inequities in its own organization and governance. As members of the Campbell and Cochrane Health Equity Thematic group, we commit to the following actions.</p><p><b>Tamara Lotfi</b>: Conceptualization, writing—original draft, reviewing and editing. <b>Vivian Welch</b>: Conceptualization, writing—original draft, review &amp; editing. <b>Jordi P. Pardo</b>: Conceptualization, writing—original draft, review &amp; editing. <b>Jennifer Petkovic</b>: Conceptualization, writing—original draft, review &amp; editing. <b>Shaun Treweek</b>: Writing—review &amp; editing. <b>Andrea Darzi</b>: Writing—review &amp; editing. <b>Rebecca Glover</b>: Writing—review &amp; editing. <b>Declan Devane</b>: Writing—review &amp; editing. <b>Meera Viswanathan</b>: Writing—review &amp; editing. <b>Lawrence Mbuagbaw</b>: Writing—review &amp; editing. <b>Kevin Pottie</b>: Writing—review &amp; editing. <b>Elizabeth Kristjansson</b>: Writing—review &amp; editing. <b>Shahab Sayfi</b>: Writing—review &amp; editing. <b>Lara Maxwell</b>: Writing—review &amp; editing. <b>Olivia Magwood</b>: Writing—review &amp; editing. <b>Damian Francis</b>: Writing—review &amp; editing. <b>Dru Riddle</b>: Writing—review &amp; ed","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141425124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advisory groups in realist reviews: Systematically mapping current research and recommendations for practice","authors":"Jessica Power,&nbsp;Sara Dada,&nbsp;Andrew Booth,&nbsp;Aoife De Brún,&nbsp;Brynne Gilmore","doi":"10.1002/cesm.12073","DOIUrl":"https://doi.org/10.1002/cesm.12073","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Realist reviews may involve groups or panels external to the research team who provide external and independent perspectives informing the review based on their experience of the topic area. These panels or groups are termed in this study as an “advisory group.” This study aims to map current practice of advisory groups in realist reviews and provide guidance for planning and reporting.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A “best-fit” framework synthesis methodology was used by first searching for a best-fit framework and then conducting a systematic search to identify a sample of realist reviews and rapid realist reviews (RRRs) from the most recent year, 2021. Nine databases were searched: CINAHL Complete, Cochrane, Embase, ERIC, MEDLINE, PsycInfo, Social Services Abstracts, Sociological Abstracts, and Web of Science Core Collection. Screening and data extraction was conducted by two researchers. The chosen best-fit framework (ACTIVE framework) informed the data extraction tool.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>One hundred and seven reviews (93 realist reviews, 14 RRRs) were identified for inclusion. Of these, 40% (<i>n</i> = 37) of realist reviews and 71.5% (<i>n</i> = 10) of RRRs mentioned use of an advisory group, though there was considerable variation in terminology used. Individuals in advisory groups were involved at varying stages of the review and tended to bring experience in the topic area from the perspective of (i) a lived experience, that is, patients, carers, family members (<i>n</i> = 15 realist reviews; <i>n</i> = 4 RRRs); (ii) professional experience, such as healthcare professionals (<i>n</i> = 20 realist reviews; <i>n</i> = 6 RRRs); or (iii) policy or research experience in the topic area (<i>n</i> = 19 realist reviews; <i>n</i> = 7 RRRs).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study proposes a  definition of advisory groups, considerations for advisory group use, and suggested items for reporting. The purpose of the advisory group should be carefully considered when deciding on their use in a realist review.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The searchbuildR shiny app: A new implementation of the objective approach for search strategy development in systematic reviews","authors":"Claudia Kapp,&nbsp;Naomi Fujita-Rohwerder,&nbsp;Jona Lilienthal,&nbsp;Wiebke Sieben,&nbsp;Siw Waffenschmidt,&nbsp;Elke Hausner","doi":"10.1002/cesm.12078","DOIUrl":"https://doi.org/10.1002/cesm.12078","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>One of the main tasks in information retrieval is the development of Boolean search strategies for systematic searches in bibliographic databases. This includes the identification of free-text terms and controlled vocabulary. IQWiG has previously implemented its objective approach for search strategy development using a fee-based text analysis software. However, this implementation is not fully automated, due to a lack of technical options. The aim of our project was to develop a text analysis tool for the development of Boolean search strategies using R.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We adopt an incremental approach to software development, with the first goal being to develop a minimum viable product for the previously defined use cases. To create an interactive user interface, we use the shiny framework.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our newly developed shiny app searchbuildR is a text analysis tool with a point-and-click user interface, that automatically extracts and ranks terms from titles, abstracts, and MeSH terms of a given test set of PubMed records. It returns searchable, interactive tables of free-text and MeSH terms. Each free-text term can also be viewed within its original context in the full titles and abstracts or in a user-defined word window. In addition, 2-word combinations are extracted and also provided as an interactive table to help the user identify free-text term combinations, that can be searched with proximity operators in Boolean searches. The results can be exported to a CSV file. The new implementation with searchbuildR was evaluated by validating the text analysis results against the results of the previously used fee-based software.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>QWiG has developed the shiny app searchbuildR to support the development of search strategies in systematic reviews. It is open source and can be used by researchers and other information specialists without extensive R or programming skills. The package code is openly available on GitHub at www.github.com/IQWiG/searchbuildR.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141304225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing CAMELOT for assessing methodological limitations of qualitative research for inclusion in qualitative evidence syntheses","authors":"Heather M. Munthe-Kaas,&nbsp;Andrew Booth,&nbsp;Isolde Sommer,&nbsp;Sara Cooper,&nbsp;Ruth Garside,&nbsp;Karin Hannes,&nbsp;Jane Noyes,&nbsp;The CAMELOT Development Group","doi":"10.1002/cesm.12058","DOIUrl":"https://doi.org/10.1002/cesm.12058","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Qualitative evidence is increasingly incorporated into decision-making processes. Assessing the methodological limitations of primary studies is critical to making an overall assessment of confidence in findings from qualitative evidence syntheses (QES) using GRADE-CERQual. Current critical appraisal tools were not developed specifically for use in Cochrane reviews or GRADE-CERQual, and few are evidence-based. The aim of CochrAne qualitative Methodological LimitatiOns Tool (CAMELOT) was to address this gap.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We undertook this project in four stages: (1) systematic literature search to identify existing tools, (2) identification of evidence to support inclusion of potential CAMELOT domains (3) consensus survey to agree on the inclusion and definition of CAMELOT domains, and (4) human-centered design approach to develop and refine CAMELOT by exploring user experience.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>CAMELOT is a new evidence-based tool for assessing the methodological strengths and limitations of primary qualitative research studies in a QES. CAMELOT is comprised of 12 domains: four <i>Meta domains</i> that encourage review authors to consider those characteristics of the primary study that are beyond how the study was carried out, but which inform the conduct and design of the study, and eight <i>Method domains</i> which encourage review authors to consider how the study was designed, planned and/or conducted, and how study conduct and design fits with the information provided in the four meta domains. Review authors make an assessment by identifying any concerns regarding the methods used in the study and considering the appropriateness of fit between the <i>Meta</i> and <i>Method domains</i>.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>CAMELOT provides review authors with a transparent and systematic method to assess methodological limitations of primary qualitative studies. CAMELOT incorporates qualitative principles and focuses on appropriateness of fit between <i>Meta</i> and <i>Method domains</i>. In line with iterative tool development approach, CAMELOT will continue to be revised over time following extensive user testing and piloting.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141294962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to “Standardized mean differences in meta-analysis: A tutorial”","authors":"","doi":"10.1002/cesm.12076","DOIUrl":"https://doi.org/10.1002/cesm.12076","url":null,"abstract":"<p>In Equation 4 (computation of the standard error [SE] of the mean difference [MD] at posttreatment time point), we wrote SD instead of SE, which is the correct one (see attached figure below).</p><p></p><p>We apologize for this error.</p>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12076","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141245517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adherence to PRISMA 2020 statement assessed through the expanded checklist in systematic reviews of interventions: A meta-epidemiological study","authors":"Diego Ivaldi,&nbsp;Mariana Burgos,&nbsp;Gisela Oltra,&nbsp;Camila E. Liquitay,&nbsp;Luis Garegnani","doi":"10.1002/cesm.12074","DOIUrl":"https://doi.org/10.1002/cesm.12074","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>The preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement was developed to improve the reporting of systematic reviews (SRs) and meta-analyses. Due to the suboptimal reporting of the 2009 version, an update was performed and published in 2021. Despite having been evaluated in studies published before its publication, its adherence in SRs of interventions published after 2021 remains unclear.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objective</h3>\u0000 \u0000 <p>To assess PRISMA 2020 statement adherence and its uptake in SRs of interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We conducted a prospective cross-sectional study searching MEDLINE (PubMed), including a 10% random sample of all SRs involving human interventions published since January 2022 retrieved by our search process. We did not apply any restrictions. We assessed PRISMA 2020 statement uptake and its adherence using its expanded checklist.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We included 222 out of 945 studies. 67 (30.18%) used PRISMA 2020 statement. None adhered completely, with an average adherence of 42.64% (Min–Max: 14.29%–76.19%). Results and Methods sections had low adherence, with 40.57% (Min–Max: 10.45%–98.51%) and 25.55% (Min–Max: 7.46%–55.22%) respectively. The items with the least adherence were: certainty and reporting bias assessment, excluded studies characteristics and search strategy with 7.46% (5/67), 8.96% (6/67), 10.45% (7/67), and 11.94% (8/67) respectively.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>As in previous studies, our study showed low adherence, mainly to the methods and results sections. However, our study showed a lower adherence, probably due to the use of the expanded checklist to assessed the tools adherence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>We found a low adherence rate to the PRISMA 2020 expanded checklist. Further PRISMA dissemination and targeted audience training are needed to improve SR reporting and quality.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12074","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141085071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intention-to-treat analyses and missing outcome data: A tutorial","authors":"Marty Chaplin,&nbsp;Kerry Dwan","doi":"10.1002/cesm.12075","DOIUrl":"https://doi.org/10.1002/cesm.12075","url":null,"abstract":"<p>This tutorial focuses on “intention-to-treat” analyses and missing outcome data in systematic reviews. There is a lack of consensus on the definition of the ITT approach. We will explain the principles of an intention-to-treat analysis, and outline the key issues you need to consider when planning, conducting and writing up your systematic review.</p><p>The authors of studies included in systematic reviews may use the term “intention-to-treat” or “intent-to-treat” (ITT) to describe the approach taken when reporting and analyzing outcome data. The ITT approach has two principles.</p><p><i>Principle A: Outcome data are reported and/or analysed according to the participant's assigned intervention, regardless of the intervention they actually received or their adherence to their assigned intervention. For randomised controlled trials, this approach is sometimes referred to as an “as-randomised” analysis</i>.</p><p>Study authors make decisions about which approach to take based on whether they are interested in determining the effect of allocation to an intervention (regardless of whether the intervention was received as intended), the effect of receiving an intervention, or the effect of adhering to an intervention (as specified in the trial protocol).</p><p><i>Principle B: Outcome data are measured for all randomised participants</i>.</p><p>If some participants do not contribute data for the outcome of interest at the required follow-up time (i.e., there are missing outcome data), data may be imputed. Various imputation methods are available, from simply assuming that all participants with missing data had a particular outcome (e.g., study authors may assume that all participants with missing data experienced a poor outcome, such as treatment failure), to more complex methods such as multiple imputation.</p><p>This principle is not met if study authors report and/or analyze outcome data only for participants with nonmissing outcome data (this approach is sometimes referred to as a “complete-case analysis”).</p><p>When choosing whether to ignore or impute missing data, and when selecting an imputation method, study authors should consider whether missing data are likely to be “missing at random” or not. Data are “missing at random” if the fact that the data are missing is unrelated to the true data values. Complete-case analyses, and some imputation methods, may lead to biased results if the missing data is “missing not at random.” Table 1 provides examples of data that are “missing at random” and data that are “missing not at random.”</p><p>There is no consensus on the definition of the ITT approach [<span>1, 2</span>]. Some study authors use the term ITT when applying both principles; others use the term when applying just one principle. Study authors may use the term “modified ITT” approach, which also has no consistent definition. The estimated intervention effect in a study may be impacted by the study author's choice of ITT approach. If this","PeriodicalId":100286,"journal":{"name":"Cochrane Evidence Synthesis and Methods","volume":"2 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cesm.12075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141078933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}