1,721,145 research outputs found
Design, analysis and presentation of factorial randomised controlled trials
Full text linkBackgroundThe evaluation of more than one intervention in the same randomised controlled trial can be achieved using a parallel group design. However this requires increased sample size and can be inefficient, especially if there is also interest in considering combinations of the interventions. An alternative may be a factorial trial, where for two interventions participants are allocated to receive neither intervention, one or the other, or both. Factorial trials require special considerations, however, particularly at the design and analysis stages.DiscussionUsing a 2 × 2 factorial trial as an example, we present a number of issues that should be considered when planning a factorial trial. The main design issue is that of sample size. Factorial trials are most often powered to detect the main effects of interventions, since adequate power to detect plausible interactions requires greatly increased sample sizes. The main analytical issues relate to the investigation of main effects and the interaction between the interventions in appropriate regression models. Presentation of results should reflect the analytical strategy with an emphasis on the principal research questions. We also give an example of how baseline and follow-up data should be presented. Lastly, we discuss the implications of the design, analytical and presentational issues covered.SummaryDifficulties in interpreting the results of factorial trials if an influential interaction is observed is the cost of the potential for efficient, simultaneous consideration of two or more interventions. Factorial trials can in principle be designed to have adequate power to detect realistic interactions, and in any case they are the only design that allows such effects to be investigated
How well do structured abstracts reflect the articles they summerize?
No full textBackground: evidence-based medicine requires
critical appraisal of published research. This is often
done by reading the abstracts alone of published
papers. This study examined how well structured
abstracts reflect the articles they summarize in
medical journals.Methods: a total of 20 papers reporting original
randomized trials were obtained from four general
medical journals. Key study details, results, and
conclusions were extracted from the full articles.
Abstracts were examined to see what information
from the article was included, and they were
scrutinized for inaccuracies, data not presented in
the main body, and ambiguous statements.Results: nineteen abstracts (95%; 95% CI 75 to 100%)
correctly stated the primary outcome. Eight abstracts
(40%; 19% to 64%) were deficient in some way. Three
(15%; 3% to 38%) contained incorrect or inconsistent
figures or data. Six abstracts (30%; 12% to 54%)
contained data not present in the full article.Discussion: almost half of the abstracts studied
contained some data inconsistent with the full article,
or missing altogether. Authors and editors need
to ensure that abstracts are of a high quality and
accurately reflect the papers they are summarizing.
CONSORT guidelines provide helpful indications as
to what should be included in abstracts reporting
clinical trial
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Public views of coronavirus science and scientists: findings from a cross-sectional survey
No full textBackground: Throughout the coronavirus pandemic, references to scientific findings have permeated public-facing communications. Understanding how members of the public view science, scientists and scientific uncertainty should enhance approaches to communication and individuals’ decisions to engage with public health measures, including restrictions and vaccination programmes.Methods: A survey was conducted on our behalf by YouGov in November 2020. The survey asked about: level of public trust in scientists and scientific information; changes in trust between March and November 2020; views about communication of scientific uncertainty; confidence in the accuracy of scientific findings; and views about whether public information is an accurate representation of coronavirus science.Results: The sample comprised 2,025 individuals living in England; 40.5% were ≥55 years old, 51.1% were female, and 12.3% identified as members of an ethnic minority/mixed ethnicity. Here, we present descriptive statistics across six key variables: age, gender, ethnicity, keyworker status, shielding status, and coronavirus exposure. Trust was highest among older respondents and those who identified as of white ethnicity. The concurrent (November 2020) levels of reported trust in scientific information about coronavirus were generally lower than those reported retrospectively for the start of the pandemic (March 2020). There was higher trust and positivity about science among people who had been shielding and among those who had not contracted coronavirus. Around half of respondents did not think that the uncertainty in science was conveyed much or at all, most were confident in the accuracy of coronavirus science, and around half thought that public information was a true representation of the science.Conclusions: Our study indicates that there is room to improve trust and communication in science. As well as detailed analyses to account for inter-relationships, further research could examine reasons behind change in trust over time and any persisting patterns by age, ethnicity, and shielding status
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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