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      School closures during COVID-19: an overview of systematic reviews

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      BMJ Evidence-Based Medicine
      BMJ

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          Abstract

          Objectives

          To assess the benefits and drawbacks of school closures and in-school mitigations during the COVID-19 pandemic.

          Design

          Overview of systematic reviews (SRs).

          Search methods

          We searched six databases and additional resources on 29 July 2022: MEDLINE, Embase, Google Scholar, Cochrane Library, COVID-END inventory of evidence synthesis, and Epistemonikos.

          Eligibility criteria

          We selected SRs written in English that answered at least one of four specific questions concerning the efficacy and drawbacks of school closures. Their primary studies were conducted in primary and secondary schools, including pupils aged 5–18. Interventions included school closures or mitigations (such as mask usage) introduced in schools.

          Data collection and analysis

          We used AMSTAR 2 to assess confidence in the included SRs, and GRADE was used to assess certainty of evidence. We performed a narrative synthesis of the results, prioritising higher-quality SRs, those which performed GRADE assessments and those with more unique primary studies. We also assessed the overlap between primary studies included in the SRs.

          Main outcome measures

          Our framework for summarising outcome data was guided by the following questions: (1) What is the impact of school closures on COVID-19 transmission, morbidity or mortality in the community? (2) What is the impact of COVID-19 school closures on mental health (eg, anxiety), physical health (eg, obesity, domestic violence, sleep) and learning/achievement of primary and secondary pupils? (3) What is the impact of mitigations in schools on COVID-19 transmission, morbidity or mortality in the community? and (4) What is the impact of COVID-19 mitigations in schools on mental health, physical health and learning/achievement of primary and secondary pupils?

          Results

          We identified 578 reports, 26 of which were included. One SR was of high confidence, 0 moderate, 10 low and 15 critically low confidence. We identified 132 unique primary studies on the effects of school closures on transmission/morbidity/mortality, 123 on learning, 164 on mental health, 22 on physical health, 16 on sleep, 7 on domestic violence and 69 on effects of in-school mitigations on transmission/morbidity/mortality.

          Both school closures and in-school mitigations were associated with reduced COVID-19 transmission, morbidity and mortality in the community. School closures were also associated with reduced learning, increased anxiety and increased obesity in pupils. We found no SRs that assessed potential drawbacks of in-school mitigations on pupils. The certainty of evidence according to GRADE was mostly very low.

          Conclusions

          School closures during COVID-19 had both positive and negative impacts. We found a large number of SRs and primary studies. However, confidence in the SRs was mostly low to very low, and the certainty of evidence was also mostly very low. We found no SRs assessing the potential drawbacks of in-school mitigations on children, which could be addressed moving forward. This overview provides evidence that could inform policy makers on school closures during future potential waves of COVID-19.

          Related collections

          Most cited references45

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          Is Open Access

          Rayyan—a web and mobile app for systematic reviews

          Background Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Results Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.
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            GRADE: an emerging consensus on rating quality of evidence and strength of recommendations.

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              AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both

              The number of published systematic reviews of studies of healthcare interventions has increased rapidly and these are used extensively for clinical and policy decisions. Systematic reviews are subject to a range of biases and increasingly include non-randomised studies of interventions. It is important that users can distinguish high quality reviews. Many instruments have been designed to evaluate different aspects of reviews, but there are few comprehensive critical appraisal instruments. AMSTAR was developed to evaluate systematic reviews of randomised trials. In this paper, we report on the updating of AMSTAR and its adaptation to enable more detailed assessment of systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. With moves to base more decisions on real world observational evidence we believe that AMSTAR 2 will assist decision makers in the identification of high quality systematic reviews, including those based on non-randomised studies of healthcare interventions.
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                Author and article information

                Contributors
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                Journal
                BMJ Evidence-Based Medicine
                BMJ EBM
                BMJ
                2515-446X
                2515-4478
                March 31 2023
                : bmjebm-2022-112085
                Article
                10.1136/bmjebm-2022-112085
                37001966
                528f8c86-0498-4839-9798-3edc0df960d6
                © 2023

                Free to read

                https://bmj.com/coronavirus/usage

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