scholarly journals Applying the Narrow Forms of PubMed Methods-based and Topic-based Filters Increases Nephrologists’ Search Efficiency

2012 ◽  
Vol 7 (3) ◽  
pp. 95
Author(s):  
Kate Kelly
Keyword(s):  
Systematic Reviews ◽  
Citation Count ◽  
Type I ◽  
Search Performance ◽  
Clinical Question ◽  
Search Query ◽  
Search Filters ◽  
Clinical Queries ◽  
Highly Cited Articles ◽  
Highly Cited

Objective – To determine whether the use of PubMed methods-based filters and topic-based filters, alone or in combination, improves physician searching. Design – Mixed methods, survey questionnaire, comparative. Setting – Canada. Subjects – Random sample of Canadian nephrologists (n=153), responses (n=115), excluded (n=15), total (n=100). Methods – The methods are described in detail in a previously published study protocol by a subset of the authors (Shariff et al., 2010). One hundred systematic reviews on renal therapy were identified using the EvidenceUpdates service (http://plus.mcmaster.ca/EvidenceUpdates) and a clinical question was derived from each review. Randomly-selected Canadian nephrologists were randomly assigned a unique clinical question derived from the reviews and asked, by survey, to provide the search query they would use to search PubMed. The survey was administered until one valid search query for each of the one hundred questions was received. The physician search was re-executed and compared to searches where either or both methods-based and topic-based filters were applied. Nine searches for each question were conducted: the original physician search, a broad and narrow form of the clinical queries therapy filter, a broad and narrow form of the nephrology topic filter and combinations of broad and narrow forms of both filters. Significance tests of comprehensiveness (proportion of relevant articles found) and efficiency (ratio of relevant to non-relevant articles) of the filtered and unfiltered searches were conducted. The primary studies included in the systematic reviews were set as the reference standard for relevant articles. As physicians indicated they did not scan beyond two pages of default PubMed results, primary analysis was also repeated on search results restricted to the first 40 records. The ability of the filters to retrieve highly-relevant or highly-cited articles was also tested, with an article being considered highly-relevant if referenced by UpToDate and highly-cited if its citation count was greater than the median citation count of all relevant articles for that question – there was an average of eight highly-cited articles per question. To reduce the risk of type I error, the conservative method of Bonferroni was applied so that tests with a p less than 0.003 were interpreted as statistically significant. Main Results – Response rate 75%. Physician-provided search terms retrieved 46% of relevant articles and a ratio of relevant to non-relevant articles of 1:16 (p less than 0.003). Applying the narrow forms of both the nephrology and clinical queries filters together produced the greatest overall improvement, with efficiency improving by 16% and comprehensiveness remaining unchanged. Applying a narrow form of the clinical queries filter increased efficiency by 17% (p less than 0.003) but decreased comprehensiveness by 8% (p less than 0.003). No combination of search filters produced improvements in both comprehensiveness and efficiency. When results were restricted to the first 40 citations, the use of the narrow form of the clinical queries filter alone improved overall search performance – comprehensiveness improved from 13% to 26 % and efficiency from 5.5% to 23%. For highly-cited or highly-relevant articles the combined use of the narrow forms of both filters produced the greatest overall improvement in efficiency but no significant change in comprehensiveness. Conclusion – The use of PubMed search filters improves the efficiency of physician searches and saves time and frustration. Applying clinical filters for quick clinical searches can significantly improve the efficiency of physician searching. Improved search performance has the potential to enhance the transfer of research into practice and improve patient care.

scholarly journals Examination of the Clinical Queries and Systematic Review “hedges” in EMBASE and MEDLINE

2014 ◽  
Vol 31 (2) ◽  
pp. 27 ◽  
Author(s):  
Susan M. Bradley
Keyword(s):  
Systematic Review ◽  
Systematic Reviews ◽  
Major Error ◽  
National Library ◽  
Search Queries ◽  
Search Results ◽  
Quality Control Testing ◽  
Search Filters ◽  
The One ◽  
Clinical Queries

Introduction – This investigation sought to determine whether the methodological search filters in place as Clinical Queries limits in OvidSP EMBASE and OvidSP MEDLINE had been modified from those written by Haynes et al. and whether the translations of these in PubMed and EBSCO MEDLINE were reliable. The translated National Library of Medicine (NLM) Systematic Reviews hedges in place in OvidSP MEDLINE and EBSCO MEDLINE were also examined. Methods – Search queries were run using the Clinical Queries and Systematic Reviews hedges incorporated into OvidSP EMBASE, OvidSP MEDLINE, PubMed, and EBSCO MEDLINE to determine the reliability of these limits in comparison with the published hedge search strings. Results – Five of the OvidSP EMBASE Clinical Queries hedges produced results that were different from the published search strings. Three of the EBSCO MEDLINE and five of the PubMed translated Clinical Queries hedges yielded markedly different results (>10% difference) than those obtained using the OvidSP MEDLINE hedge counterparts. The OvidSP MEDLINE Systematic Reviews subject subset hedge was found to have a major error, which has been corrected. Discussion – Translations of hedges to appropriate syntax for other database platforms may result in significantly different search results. The platform searched should ideally be the one for which the hedges were written and tested. Regardless, the hedges in place may not be the same as the published hedge search strings. Quality control testing is needed to ensure that the hedges in place as limits are the same as those that have been published.

scholarly journals A Bayesian Hurdle Quantile Regression Model for Citation Analysis with Mass Points at Lower Values

2021 ◽  
pp. 1-29
Author(s):  
Marzieh Shahmandi ◽  
Paul Wilson ◽  
Mike Thelwall
Keyword(s):  
Quantile Regression ◽  
Regression Model ◽  
Regression Discontinuity ◽  
Citation Count ◽  
Mass Point ◽  
Quantile Regression Model ◽  
The Mean ◽  
Citation Counts ◽  
Highly Cited Articles ◽  
Highly Cited

Abstract Quantile regression presents a complete picture of the effects on the location, scale, and shape of the dependent variable at all points, not just the mean. We focus on two challenges for citation count analysis by quantile regression: discontinuity and substantial mass points at lower counts. A Bayesian hurdle quantile regression model for count data with a substantial mass point at zero was proposed by King and Song (2019). It uses quantile regression for modeling the nonzero data and logistic regression for modeling the probability of zeros versus nonzeros. We show that substantial mass points for low citation counts will nearly certainly also affect parameter estimation in the quantile regression part of the model, similar to a mass point at zero. We update the King and Song model by shifting the hurdle point past the main mass points. This model delivers more accurate quantile regression for moderately to highly cited articles, especially at quantiles corresponding to values just beyond the mass points, and enables estimates of the extent to which factors influence the chances that an article will be low cited. To illustrate the potential of this method, it is applied to simulated citation counts and data from Scopus. Peer Review https://publons.com/publon/10.1162/qss_a_00147

scholarly journals A Decade of Social Media Influence on Foot and Ankle Literature

2020 ◽  
Vol 5 (4) ◽  
pp. 2473011420S0037
Author(s):  
James M. Parrish ◽  
Jonathan R. Kaplan ◽  
Amiethab A. Aiyer
Keyword(s):  
Social Media ◽  
Citation Count ◽  
Future Research ◽  
Foot And Ankle ◽  
Level Of Evidence ◽  
Orthopaedic Literature ◽  
Ankle Research ◽  
Study Designs ◽  
Highly Cited Articles ◽  
Highly Cited

Category: Ankle; Ankle Arthritis; Arthroscopy; Basic Sciences/Biologics; Bunion; Diabetes; Hindfoot; Lesser Toes; Midfoot/Forefoot; Sports; Trauma; Other Introduction/Purpose: The topics, articles and discussions that arise within Foot and Ankle Orthopaedic literature are increasingly determined by their presence on social media outlets. The influence of social media mentions on Foot and Ankle Orthopaedic literature has not yet been investigated. The primary purpose of this study is to identify the social media outlets that were most associated with the Altmetric attention score (AAS). The secondary aim is to characterize the top 100 most highly cited articles within Foot and Ankle literature with the top 100 scoring Altmetric articles. Methods: We conducted a query of the Altmetric database for all journal titles containing the words ‘Foot’ and ‘Ankle.’ In accordance with other investigations, articles were only included after 2010, since this was beginning of academic social media participation. We assessed the frequency and percent of articles by journal, collecting variables including impact factor, AAS, along with average mentions within news, blogs, policy, patents, Twitter, peer review, Weibo, Facebook, Wikipedia, Google+, LinkedIn, Reddit, Pinterest, F1000, Q&A, online video, Syllabi, and traditional metrics such as number of Mendeley readers and citations (Table 1). We used a Spearman, semi-partial, and partial correlation test to detect the association between AAS and media outlet mentions, Mendeley readers or Dimensions citations. Finally, we ranked one article list with the 100 most popular articles on social media and one with the 100 most cited articles. Articles were examined for overlap, topic, article type, and level of evidence. Results: Our search returned 4,365 articles. Foot and Ankle International had the highest frequency of articles, though the Journal of Foot and Ankle Research had the highest AAS (Table 1). News and Twitter mentions had the greatest association with AAS. The top study designs for the AAS articles were prospective (n=35), retrospective (n=25), and systematic reviews (n=17), compared to the most highly cited articles which had retrospective (n=32), review (n=31), and observational studies (n=26) (p<0.001). When examining the top 100 highest AAS scoring articles with the 100 most cited, there was only one article in both groups. Compared to the most highly cited articles, the highest ranked AAS articles had a better average level of evidence (Cited: 3.4 vs. AAS: 2.9, p=0.001). Conclusion: Twitter and mentions within news are the most correlated with AAS. Although traditional metrics for article influence often reference an article’s citation count, attaining social media relevance is becoming more important than before. There is currently very little overlap among the most highly cited and the most mentioned articles on social media. Future research is needed to address whether citation counts or social media presence have more influence on actual clinical practice. [Table: see text]

scholarly journals Defining publication bias: protocol for a systematic review of highly cited articles and proposal for a new framework

2013 ◽  
Vol 2 (1) ◽  
Author(s):  
Katharina Felicitas Müller ◽  
Matthias Briel ◽  
Alexandra D’Amario ◽  
Jos Kleijnen ◽  
Ana Marusic ◽  
...  
Keyword(s):  
Systematic Review ◽  
Publication Bias ◽  
New Framework ◽  
Highly Cited Articles ◽  
Highly Cited

scholarly journals Usage Count: A New Indicator to Detect Research Fronts

2017 ◽  
Vol 2 (1) ◽  
pp. 89-104 ◽  
Author(s):  
Guoqiang Liang ◽  
Haiyan Hou ◽  
Zhigang Hu ◽  
Fu Huang ◽  
Yajie Wang ◽  
...  
Keyword(s):  
Regenerative Medicine ◽  
Citation Count ◽  
Time Lag ◽  
Research Front ◽  
Research Fronts ◽  
The Mean ◽  
New Perspective ◽  
Practical Implications ◽  
Traditional Indicator ◽  
Highly Cited

Abstract Purpose Research fronts build on recent work, but using times cited as a traditional indicator to detect research fronts will inevitably result in a certain time lag. This study attempts to explore the effects of usage count as a new indicator to detect research fronts in shortening the time lag of classic indicators in research fronts detection. Design/methodology/approach An exploratory study was conducted where the new indicator “usage count” was compared to the traditional citation count, “times cited,” in detecting research fronts of the regenerative medicine domain. An initial topic search of the term “regenerative medicine” returned 10,553 records published between 2000 and 2015 in the Web of Science (WoS). We first ranked these records with usage count and times cited, respectively, and selected the top 2,000 records for each. We then performed a co-citation analysis in order to obtain the citing papers of the co-citation clusters as the research fronts. Finally, we compared the average publication year of the citing papers as well as the mean cited year of the co-citation clusters. Findings The citing articles detected by usage count tend to be published more recently compared with times cited within the same research front. Moreover, research fronts detected by usage count tend to be within the last two years, which presents a higher immediacy and real-time feature compared to times cited. There is approximately a three-year time span among the mean cited years (known as “intellectual base”) of all clusters generated by usage count and this figure is about four years in the network of times cited. In comparison to times cited, usage count is a dynamic and instant indicator. Research limitations We are trying to find the cutting-edge research fronts, but those generated based on co-citations may refer to the hot research fronts. The usage count of older highly cited papers was not taken into consideration, because the usage count indicator released by WoS only reflects usage logs after February 2013. Practical implications The article provides a new perspective on using usage count as a new indicator to detect research fronts. Originality/value Usage count can greatly shorten the time lag in research fronts detection, which would be a promising complementary indicator in detection of the latest research fronts.

scholarly journals High-cited favorable studies for COVID-19 treatments ineffective in large trials

2022 ◽  
Author(s):  
John P.A. Ioannidis
Keyword(s):  
Clinical Trials ◽  
Randomized Controlled Trials ◽  
Clinical Studies ◽  
Observational Studies ◽  
Randomized Trials ◽  
Controlled Trials ◽  
Randomized Controlled ◽  
Wide Dissemination ◽  
Highly Cited Articles ◽  
Highly Cited

Importance. COVID-19 has resulted in massive production, publication and wide dissemination of clinical studies trying to identify effective treatments. However, several widely touted treatments failed to show effectiveness in large well-done randomized controlled trials (RCTs). Objective. To evaluate for COVID-19 treatments that showed no benefits in subsequent large RCTs how many of their most-cited clinical studies had declared favorable results for these interventions. Methods. Scopus (last update December 23, 2021) identified articles on lopinavir-ritonavir, hydroxycholoroquine/azithromycin, remdesivir, convalescent plasma, colchicine or interferon (index interventions) that represented clinical trials and that had received >150 citations. Their conclusions were assessed and correlated with study design features. The ten most recent citations for the most-cited article on each index intervention were examined on whether they were critical to the highly-cited study. Altmetric scores were also obtained. Findings. 40 articles of clinical studies on these index interventions had received >150 citations (7 exceeded 1,000 citations). 20/40 (50%) had favorable conclusions and 4 were equivocal. Highly-cited articles with favorable conclusions were rarely RCTs while those without favorable conclusions were mostly RCTs (3/20 vs 15/20, p=0.0003). Only 1 RCT with favorable conclusions had sample size >160. Citation counts correlated strongly with Altmetric scores, in particular news items. Only 9 (15%) of 60 recent citations to the most highly-cited studies with favorable or equivocal conclusions were critical to the highly-cited study. Conclusion. Many clinical studies with favorable conclusions for largely ineffective COVID-19 treatments are uncritically heavily cited and disseminated. Early observational studies and small randomized trials may cause spurious claims of effectiveness that get perpetuated.

scholarly journals Bibliometric Analysis of Interventional Literature on Mobile Health: The Most Highly Cited Articles

2021 ◽  
Vol 10 (1) ◽  
pp. 66
Author(s):  
Arefeh Ameri ◽  
Farzad Salmanizadeh ◽  
Kambiz Bahaadinbeigy
Keyword(s):  
Mental Health ◽  
Treatment Adherence ◽  
Mobile Health ◽  
Text Messaging ◽  
Mental Health Disorders ◽  
Mobile Technologies ◽  
Health Disorders ◽  
Number Of Citations ◽  
Highly Cited Articles ◽  
Highly Cited

Introduction: Advances in mobile health have led to numerous relevant studies in diagnosis, treatment, and controlling of various diseases. One of the criteria indicating the quality of the previously published studies is the number of citations. Therefore, investigating the features of highly cited articles and identifying the most frequently used mobile technological interventions can affect future research ideas. This study aimed at identifying 100 highly cited interventional studies on mobile health, type of used mobile technologies, and effect of these technologies in various diseases in top-cited articles.Methods: The database employed in this study was the Web of Science, which without limitations was analysed in April 2020 to identify 100 highly cited interventional studies in the field of mobile health. The identified studies were classified based on the number of citations, year of publication, country of the first author, type of disease, and use of mobile technology.Results: A great majority of the studies in the field of interventional mobile health focused on obesity (n=18), addiction (n=15), diabetes (n=13) and mental health disorders (n=12), respectively. Many studies employed mobile technologies to promote lifestyle (weight loss and increased physical activity) (n=20), disease controls (n=20), and treatment adherence (n=18). The mean number of citations per study was 146±97. The most cited study was in the category of viral disease treatment adherence (n=703), and the most cited articles were published in 2012.Conclusions: Among the reviewed 100 studies, many of the interventional studies regarding mobile health focused on obesity, addiction, diabetes and mental health disorders. Promotion of lifestyle, disease controls, and treatment adherence were effects of mobile technologies in top-cited articles. Text messaging service was used as intervention in most of the studies. Thus, future studies may focus on the use of various mobile applications on different diseases’ prevention, control, and treatment.

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