Use Of Search Filters Research Articles

The effect of cannabidiol in the treatment of behavioral symptoms in children and adolescents with autism: an integrative review

Objective: to conduct an integrative review which seeks to analyze the effects of cannabidiol in children and adolescents with Autism Spectrum Disorder (ASD). Method: an integrative review was conducted following several methodological steps, including identifying the topic and formulating the research question using the PICO strategy. The guiding question was: "What is the effect of Cannabidiol (CBD) in the treatment of autism spectrum disorder (ASD) in children and adolescents?" Inclusion criteria were defined for selecting relevant articles, followed by the search and selection of articles in scientific databases Portal Capes and PubMed, with no use of search filters. The studies were evaluated and analyzed; the results were then interpreted. Finally, the integrative review consolidated knowledge about the possible effects of CBD as an intervention for ASD. Conclusion: the integrative review highlights the possible effects of cannabidiol (CBD) in the treatment of autism, showing significant improvement of symptoms with minimal side effects. Although still not widely disseminated, CBD appears to be a functional therapy for ASD.

PP113 Common Methodological Issues In Systematic Reviews Supporting Single Technology Appraisal Submissions To The National Institute for Health and Care Excellence

IntroductionThis project aimed to identify methodological issues reported by Evidence Review Groups (ERGs) in the systematic reviews (SR) supporting single technology appraisal (STA) submissions to the National Institute for Health and Care Excellence (NICE). STA submissions contain SRs related to the clinical and cost-effectiveness of the proposed intervention and NICE require the methods for these reviews to be clearly detailed in the submission. The intention of this project was to identify methodological aspects of submissions where companies may need additional guidance or support to provide the evidence required for efficient and effective decision-making and in turn facilitate timely access to clinical innovation.MethodsFrom 2019, 61 STAs were identified from the NICE website, of which 46 were included. We extracted information about the data requests or clarification questions raised by the ERG in relation to the methodological section of both the clinical and cost effectiveness SRs reported in the STA. We then categorized these data and grouped by theme to determine the most common methodological issues faced by companies. We did not assess whether comments made by the ERG were accurate or justified.ResultsFor both clinical and cost-effectiveness SRs, the most frequent clarification questions arose from the search methods section, specifically seeking information about missing intervention or comparator terms, the use of search filters and search platforms. Clarification questions were also commonly asked about the appropriateness of interventions and comparators. There were very few clarification questions asked about screening, data extraction or risk of bias assessment.ConclusionsCompanies looking to submit an STA should align their submission methodology to established best practice guidance for systematic reviewing to ensure their methods are fit for purpose and avoid unnecessary delays to the STA process. Consistency with the PRISMA reporting standards would help ensure that the ERG is provided with the information needed to assess the appropriateness of the STA methodology and is likely to reduce the need for clarification questions.

Respiratory syncytial virus tracking using internet search engine data

BackgroundRespiratory Syncytial Virus (RSV) is the leading cause of hospitalization in children less than 1 year of age in the United States. Internet search engine queries may provide high resolution temporal and spatial data to estimate and predict disease activity.MethodsAfter filtering an initial list of 613 symptoms using high-resolution Bing search logs, we used Google Trends data between 2004 and 2016 for a smaller list of 50 terms to build predictive models of RSV incidence for five states where long-term surveillance data was available. We then used domain adaptation to model RSV incidence for the 45 remaining US states.ResultsSurveillance data sources (hospitalization and laboratory reports) were highly correlated, as were laboratory reports with search engine data. The four terms which were most often statistically significantly correlated as time series with the surveillance data in the five state models were RSV, flu, pneumonia, and bronchiolitis. Using our models, we tracked the spread of RSV by observing the time of peak use of the search term in different states. In general, the RSV peak moved from south-east (Florida) to the north-west US.ConclusionsOur study represents the first time that RSV has been tracked using Internet data results and highlights successful use of search filters and domain adaptation techniques, using data at multiple resolutions. Our approach may assist in identifying spread of both local and more widespread RSV transmission and may be applicable to other seasonal conditions where comprehensive epidemiological data is difficult to collect or obtain.

OP71 Evidence-Based Searching For Health Technology Assessment – Keeping Up-to-Date With Summarized Research In Information Retrieval (SuRe Info)

INTRODUCTION:Increasing numbers of research papers about information retrieval for Health Technology Assessments (HTA), systematic reviews and other evidence syntheses are being published. It is time-consuming for information specialists to keep up-to-date with the latest developments in the field. To help searchers with this challenge, the Interest Group on Information Retrieval (IRG) of Health Technology Assessment International (HTAi) has compiled the best available research evidence on information retrieval aspects into an open-access web resource: Summarized Research in Information Retrieval for HTA (SuRe Info). The resource can be accessed at http://www.sure-info.orgMETHODS:The Sure Info team run topic-specific search strategies in selected relevant databases to identify information retrieval methods publications that fulfil the SuRe Info inclusion criteria. Eligible publications receive a structured abstract containing a brief critical appraisal. Key messages for search practice based on the appraisals and accepted best practice are summarized into topic-specific chapters.RESULTS:SuRe Info currently offers fourteen chapters, with more in development. SuRe Info chapters fall into two categories: (i) chapters about general search methods that are used across all types of research, such as how to develop search strategies and the availability and use of search filters, and (ii) chapters summarizing the methods to use when searching for specific aspects of HTA (as defined in the European Network for HTA (EUnetHTA) HTA Core Model®), including searching for evidence on clinical effectiveness and safety, and identifying economic evaluations. References at the end of each chapter are linked to appraisals of publications that have been used to develop each chapter. Links to the full-text of the publications are provided when freely available. The SuRe Info chapters are reviewed every six months and updated if new evidence is identified or if resources change.CONCLUSIONS:SuRe Info is a unique resource, identifying and summarizing current best research evidence on information retrieval aspects for HTA. It supports the timely uptake of potential efficiencies arising from new evidence that may be incorporated into the evidence identification processes of HTA organizations.

VP195 Using The ISSG Search Filter Resource In Health Technology Assessment

INTRODUCTION:Information specialists and others searching for Health Technology Assessments (HTAs) can use the ISSG Search Filter resource (SFR) to identify filters to incorporate into search strategies. This can save time and effort when designing searches and create more efficient searches that retrieve fewer and possibly more relevant database records (link available here: https://sites.google.com/a/york.ac.uk/issg-search-filters-resource/home).What are search filters? Search filters are collections of search terms designed to retrieve selections of records from bibliographic databases. Some filters are designed to retrieve records of specific study designs such as randomized controlled trials (RCTs) or systematic reviews; others aim to retrieve records relating to other features or topics such as the age or gender of study participants.Search filters may be designed to be sensitive, precise or balanced between sensitivity and precision.METHODS:When would you use a search filter in HTA? Search filters can be added to search strategies to limit to specific study types, for example, RCTs, mixed methods studies, systematic reviews. They can also be used when searching for other aspects of HTA such as patient views or specific age groups.The ISSG SFR includes sections listing search filters to help identify adverse effects, aetiology, economic evaluations, health state utility values, public views, and quality of life.RESULTS:How are filters used? A search filter is often used in combination with a topic search to restrict the search results to a specific type of record, for example, records reporting health state utility values or records of randomized controlled trials.CONCLUSIONS:Further guidance on the use of search filters can be found in the SuRe Info Search Filters chapter.

Choosing and using methodological search filters: searchers' views.

Search filters or hedges are search strategies developed to assist information specialists and librarians to retrieve different types of evidence from bibliographic databases. The objectives of this project were to learn about searchers' filter use, how searchers choose search filters and what information they would like to receive to inform their choices. Interviews with information specialists working in, or for, the National Institute for Health and Care Excellence (NICE) were conducted. An online questionnaire survey was also conducted and advertised via a range of email lists. Sixteen interviews were undertaken and 90 completed questionnaires were received. The use of search filters tends to be linked to reducing a large amount of literature, introducing focus and assisting with searches that are based on a single study type. Respondents use numerous ways to identify search filters and can find choosing between different filters problematic because of knowledge gaps and lack of time. Search filters are used mainly for reducing large result sets (introducing focus) and assisting with searches focused on a single study type. Features that would help with choosing filters include making information about filters less technical, offering ratings and providing more detail about filter validation strategies and filter provenance.

Impact of PubMed search filters on the retrieval of evidence by physicians

Physicians face challenges when searching PubMed for research evidence, and they may miss relevant articles while retrieving too many nonrelevant articles. We investigated whether the use of search filters in PubMed improves searching by physicians. We asked a random sample of Canadian nephrologists to answer unique clinical questions derived from 100 systematic reviews of renal therapy. Physicians provided the search terms that they would type into PubMed to locate articles to answer these questions. We entered the physician-provided search terms into PubMed and applied two types of search filters alone or in combination: a methods-based filter designed to identify high-quality studies about treatment (clinical queries "therapy") and a topic-based filter designed to identify studies with renal content. We evaluated the comprehensiveness (proportion of relevant articles found) and efficiency (ratio of relevant to nonrelevant articles) of the filtered and nonfiltered searches. Primary studies included in the systematic reviews served as the reference standard for relevant articles. The average physician-provided search terms retrieved 46% of the relevant articles, while 6% of the retrieved articles were relevant (corrected) (the ratio of relevant to nonrelevant articles was 1:16). The use of both filters together produced a marked improvement in efficiency, resulting in a ratio of relevant to nonrelevant articles of 1:5 (16 percentage point improvement; 99% confidence interval 9% to 22%; p < 0.003) with no substantive change in comprehensiveness (44% of relevant articles found; p = 0.55). The use of PubMed search filters improves the efficiency of physician searches. Improved search performance may enhance the transfer of research into practice and improve patient care.

An overview of the design and methods for retrieving high-quality studies for clinical care

BackgroundWith the information explosion, the retrieval of the best clinical evidence from large, general purpose, bibliographic databases such as MEDLINE can be difficult. Both researchers conducting systematic reviews and clinicians faced with a patient care question are confronted with the daunting task of searching for the best medical literature in electronic databases. Many have advocated the use of search filters or "hedges" to assist with the searching process. The purpose of this report is to describe the design and methods of a study that set out to develop optimal search strategies for retrieving sound clinical studies of health disorders in large electronics databases.ObjectiveTo describe the design and methods of a study that set out to develop optimal search strategies for retrieving sound clinical studies of health disorders in large electronic databases.DesignAn analytic survey comparing hand searches of 170 journals in the year 2000 with retrievals from MEDLINE, EMBASE, CINAHL, and PsycINFO for candidate search terms and combinations. The sensitivity, specificity, precision, and accuracy of unique search terms and combinations of search terms were calculated.ConclusionA study design modeled after a diagnostic testing procedure with a gold standard (the hand search of the literature) and a test (the search terms) is an effective way of developing, testing, and validating search strategies for use in large electronic databases.