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Grey literature

About: Grey literature is a(n) research topic. Over the lifetime, 1187 publication(s) have been published within this topic receiving 20549 citation(s). The topic is also known as: gray literature.
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Journal ArticleDOI
30 Nov 2002-BMJ
TL;DR: Evidence supports the notion that involving patients has contributed to changes in the provision of services across a range of different settings, and an evidence base for the effects on use of services, quality of care, satisfaction, or health of patients does not exist.
Abstract: Objective To examine the effects of involving patients in the planning and development of health care. Data sources Published and grey literature. Study selection Systematic search for worldwide reports written in English between January 1966 and October 2000. Data extraction Qualitative review of papers describing the effects of involving patients in the planning and development of health care. Results Of 42 papers identified, 31 (74%) were case studies. Papers often described changes to services that were attributed to involving patients, including attempts to make services more accessible and producing information leaflets for patients. Changes in the attitudes of organisations to involving patients and positive responses from patients who took part in initiatives were also reported. Conclusions Evidence supports the notion that involving patients has contributed to changes in the provision of services across a range of different settings. An evidence base for the effects on use of services, quality of care, satisfaction, or health of patients does not exist.

870 citations


Journal ArticleDOI
Laura McAuley1, Ba' Pham1, Peter Tugwell2, David Moher2  +1 moreInstitutions (2)
TL;DR: Whether exclusion of grey literature, compared with its inclusion in meta-analysis, provides different estimates of the effectiveness of interventions assessed in randomised trials is examined.
Abstract: Summary Background The inclusion of only a subset of all available evidence in a meta-analysis may introduce biases and threaten its validity; this is particularly likely if the subset of included studies differ from those not included, which may be the case for published and grey literature (unpublished studies, with limited distribution). We set out to examine whether exclusion of grey literature, compared with its inclusion in meta-analysis, provides different estimates of the effectiveness of interventions assessed in randomised trials. Methods From a random sample of 135 meta-analyses, we identified and retrieved 33 publications that included both grey and published primary studies. The 33 publications contributed 41 separate meta-analyses from several disease areas. General characteristics of the meta-analyses and associated studies and outcome data at the trial level were collected. We explored the effects of the inclusion of grey literature on the quantitative results using logistic-regression analyses. Findings 33% of the meta-analyses were found to include some form of grey literature. The grey literature, when included, accounts for between 4·5% and 75% of the studies in a meta-analysis. On average, published work, compared with grey literature, yielded significantly larger estimates of the intervention effect by 15% (ratio of odds ratios=1·15 [95% CI 1·04—1·28]). Excluding abstracts from the analysis further compounded the exaggeration (1·33 [1·10–1·60]). Interpretation The exclusion of grey literature from metaanalyses can lead to exaggerated estimates of intervention effectiveness. In general, meta-analysts should attempt to identify, retrieve, and include all reports, grey and published, that meet predefined inclusion criteria.

650 citations


Journal ArticleDOI
TL;DR: A comprehensive classification of blockchain-enabled applications across diverse sectors such as supply chain, business, healthcare, IoT, privacy, and data management is presented, and key themes, trends and emerging areas for research are established.
Abstract: This work provides a systematic literature review of blockchain-based applications across multiple domains. The aim is to investigate the current state of blockchain technology and its applications and to highlight how specific characteristics of this disruptive technology can revolutionise “business-as-usual” practices. To this end, the theoretical underpinnings of numerous research papers published in high ranked scientific journals during the last decade, along with several reports from grey literature as a means of streamlining our assessment and capturing the continuously expanding blockchain domain, are included in this review. Based on a structured, systematic review and thematic content analysis of the discovered literature, we present a comprehensive classification of blockchain-enabled applications across diverse sectors such as supply chain, business, healthcare, IoT, privacy, and data management, and we establish key themes, trends and emerging areas for research. We also point to the shortcomings identified in the relevant literature, particularly limitations the blockchain technology presents and how these limitations spawn across different sectors and industries. Building on these findings, we identify various research gaps and future exploratory directions that are anticipated to be of significant value both for academics and practitioners.

639 citations


Journal ArticleDOI
17 Sep 2015-PLOS ONE
TL;DR: It is concluded that whilst Google Scholar can find much grey literature and specific, known studies, it should not be used alone for systematic review searches, rather, it forms a powerful addition to other traditional search methods.
Abstract: Google Scholar (GS), a commonly used web-based academic search engine, catalogues between 2 and 100 million records of both academic and grey literature (articles not formally published by commercial academic publishers). Google Scholar collates results from across the internet and is free to use. As a result it has received considerable attention as a method for searching for literature, particularly in searches for grey literature, as required by systematic reviews. The reliance on GS as a standalone resource has been greatly debated, however, and its efficacy in grey literature searching has not yet been investigated. Using systematic review case studies from environmental science, we investigated the utility of GS in systematic reviews and in searches for grey literature. Our findings show that GS results contain moderate amounts of grey literature, with the majority found on average at page 80. We also found that, when searched for specifically, the majority of literature identified using Web of Science was also found using GS. However, our findings showed moderate/poor overlap in results when similar search strings were used in Web of Science and GS (10–67%), and that GS missed some important literature in five of six case studies. Furthermore, a general GS search failed to find any grey literature from a case study that involved manual searching of organisations’ websites. If used in systematic reviews for grey literature, we recommend that searches of article titles focus on the first 200 to 300 results. We conclude that whilst Google Scholar can find much grey literature and specific, known studies, it should not be used alone for systematic review searches. Rather, it forms a powerful addition to other traditional search methods. In addition, we advocate the use of tools to transparently document and catalogue GS search results to maintain high levels of transparency and the ability to be updated, critical to systematic reviews.

531 citations


Journal ArticleDOI
TL;DR: This review shows that published trials tend to be larger and show an overall greater treatment effect than grey trials, which has important implications for reviewers who need to ensure they identify grey trials in order to minimise the risk of introducing bias into their review.
Abstract: BACKGROUND: The inclusion of grey literature (i.e. literature that has not been formally published) in systematic reviews may help to overcome some of the problems of publication bias, which can arise due to the selective availability of data. OBJECTIVES: To review systematically research studies, which have investigated the impact of grey literature in meta-analyses of randomized trials of health care interventions. SEARCH STRATEGY: We searched the Cochrane Methodology Register (The Cochrane Library Issue 3, 2005), MEDLINE (1966 to 20 May 2005), the Science Citation Index (June 2005) and contacted researchers who may have carried out relevant studies. SELECTION CRITERIA: A study was considered eligible for this review if it compared the effect of the inclusion and exclusion of grey literature on the results of a cohort of meta-analyses of randomized trials. DATA COLLECTION AND ANALYSIS: Data were extracted from each report independently by two reviewers. The main outcome measure was an estimate of the impact of trials from the grey literature on the pooled effect estimates of the meta-analyses. Information was also collected on the area of health care, the number of meta-analyses, the number of trials, the number of trial participants, the year of publication of the trials, the language and country of publication of the trials, the number and type of grey and published literature, and methodological quality. MAIN RESULTS: Five studies met the inclusion criteria. All five studies showed that published trials showed an overall greater treatment effect than grey trials. This difference was statistically significant in one of the five studies. Data could be combined for three of the five studies. This showed that, on average, published trials showed a 9% greater treatment effect than grey trials (ratio of odds ratios for grey versus published trials 1.09; 95% CI 1.03-1.16). Overall there were more published trials included in the meta-analyses than grey trials (median 224 (IQR 108-365) versus 45(IQR 40-102)). Published trials had more participants on average. The most common types of grey literature were abstracts (55%) and unpublished data (30%). There is limited evidence to show whether grey trials are of poorer methodological quality than published trials. AUTHORS' CONCLUSIONS: This review shows that published trials tend to be larger and show an overall greater treatment effect than grey trials. This has important implications for reviewers who need to ensure they identify grey trials, in order to minimise the risk of introducing bias into their review.

471 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20223
2021109
202099
201985
201853
201772