News coverage of medical research is followed closely by many Americans and affects the practice of medicine and influence of scientific research. Prior work has examined the quality of media coverage, but no investigation has characterized the choice of stories covered in a controlled manner. We examined whether the media systematically covers stories of weaker study design.
Gongylonema pulchrum Infection in a Resident of Williamsburg, Virginia, Verified by Genetic Analysis
- The American journal of tropical medicine and hygiene
- Published about 5 years ago
We describe the thirteenth reported case of human infection with Gongylonema spp. in the United States and the first to be confirmed as Gongylonema pulchrum. The parasite described was isolated from the oral cavity of a resident of Williamsburg, Virginia. The identity of the parasite was verified through morphologic and genetic approaches, and provided the first genetic confirmation of a Gongylonema sp. in humans.
The last few years have seen the proliferation of measures that quantify the scientific output of researchers. Yet, most of these measures focus on productivity, thus fostering the “publish or perish” paradigm. This article proposes a measure that aims at quantifying the impact of research de-emphasizing productivity, thus providing scientists an alternative, conceivably fairer, evaluation of their work. The measure builds from a published manuscript, the literature’s most basic building block. The impact of an article is defined as the number of lead authors that have been influenced by it. Thus, the measure aims at quantifying the manuscript’s reach, putting emphasis on scientists rather than on raw citations. The measure is then extrapolated to researchers and institutions.
The concepts of ‘sex’ and ‘gender’ are both of vital importance in medicine and health sciences. However, the meaning of these concepts has seldom been discussed in the medical literature. The aim of this study was to explore what the concepts of ‘sex’ and ‘gender’ meant for gender researchers based in a medical faculty.
Despite the rapid global movement towards electronic health records, clinical letters written in unstructured natural languages are still the preferred form of inter-practitioner communication about patients. These letters, when archived over a long period of time, provide invaluable longitudinal clinical details on individual and populations of patients. In this paper we present three unsupervised approaches, sequential pattern mining (PrefixSpan); frequency linguistic based C-Value; and keyphrase extraction from co-occurrence graphs (TextRank), to automatically extract single and multi-word medical terms without domain-specific knowledge. Because each of the three approaches focuses on different aspects of the language feature space, we propose a genetic algorithm to learn the best parameters of linearly integrating the three extractors for optimal performance against domain expert annotations. Around 30,000 clinical letters sent over the past decade from ophthalmology specialists to general practitioners at an eye clinic are anonymised as the corpus to evaluate the effectiveness of the ensemble against individual extractors. With minimal annotation, the ensemble achieves an average F-measure of 65.65 % when considering only complex medical terms, and a F-measure of 72.47 % if we take single word terms (i.e. unigrams) into consideration, markedly better than the three term extraction techniques when used alone.
[This corrects the article DOI: 10.1186/s40425-016-0157-6.].
In 2011, football quarterback Peyton Manning went on the road to seek out stem-cell “treatment” for his neck. He wasn’t alone: many high-profile athletes and desperate (but less famous) patients left the United States seeking interventions available in countries with less rigorous regulation. They didn’t necessarily know what kind of cells they were getting, whether there was any evidence the intervention worked, or whether anyone understood the risks they were taking. So why did they do it? Part of the answer may lie in the Latin phrase argumentum ad novitatem, the appeal to the new. A powerful force in . . .
This meta-analysis, spanning 5 decades of Draw-A-Scientist studies, examined U.S. children’s gender-science stereotypes linking science with men. These stereotypes should have weakened over time because women’s representation in science has risen substantially in the United States, and mass media increasingly depict female scientists. Based on 78 studies (N = 20,860; grades K-12), children’s drawings of scientists depicted female scientists more often in later decades, but less often among older children. Children’s depictions of scientists therefore have become more gender diverse over time, but children still associate science with men as they grow older. These results may reflect that children observe more male than female scientists in their environments, even though women’s representation in science has increased over time.
Among 29 industrialized countries, the United States ranks high in patients' satisfaction with their own care but low in public trust in the country’s physicians. If the U.S. medical profession wants to influence health policy decisions, it must improve public trust.
In the 10 years since the inception of Implementation Science, we have witnessed a continued rise in the number of submissions received, reflecting the continued global interest in methods to enhance the uptake of research findings into healthcare practice and policy. We receive over 750 submissions annually, and there is now a large gap between what is submitted and what gets published. In this editorial, we restate the journal scope and current boundaries. We also identify some specific reporting issues that if addressed will help enhance the scientific reporting quality and transparency of the manuscripts we receive. We hope that this editorial acts as a further guide to researchers seeking to publish their work in Implementation Science.