This Formal Comment presents an update to citation databases of top-cited scientists across all scientific fields, including more granular information on diverse indicators.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Recalibrating the Use of Race in Medical Research Ioannidis, John P. A; Powe, Neil R; Yancy, Clyde
JAMA : the journal of the American Medical Association,
02/2021, Letnik:
325, Številka:
7
Journal Article
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This Viewpoint reviews the way race has been used and misused in medical research and urges careful consideration by investigators of how its use might ameliorate or worsen health inequalities.
Highlights • Publication and other reporting biases can have major detrimental effects on the credibility and value of research evidence. • There is substantial empirical evidence of publication and ...reporting biases in cognitive science disciplines. • Common types of bias are discussed and potential solutions are proposed.
A study with low statistical power has a reduced chance of detecting a true effect, but it is less well appreciated that low power also reduces the likelihood that a statistically significant result ...reflects a true effect. Here, we show that the average statistical power of studies in the neurosciences is very low. The consequences of this include overestimates of effect size and low reproducibility of results. There are also ethical dimensions to this problem, as unreliable research is inefficient and wasteful. Improving reproducibility in neuroscience is a key priority and requires attention to well-established but often ignored methodological principles.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
As of October 2020, there are >1 million documented deaths with COVID‐19. Excess deaths can be caused by both COVID‐19 and the measures taken. COVID‐19 shows extremely strong risk stratification ...across age, socioeconomic factors, and clinical factors. Calculation of years‐of‐life‐lost from COVID‐19 is methodologically challenging and can yield misleading over‐estimates. Many early deaths may have been due to suboptimal management, malfunctional health systems, hydroxychloroquine, sending COVID‐19 patients to nursing homes, and nosocomial infections; such deaths are partially avoidable moving forward. About 10% of the global population may be infected by October 2020. Global infection fatality rate is 0.15‐0.20% (0.03‐0.04% in those <70 years), with large variability across locations with different age‐structure, institutionalization rates, socioeconomic inequalities, population‐level clinical risk profile, public health measures, and health care. There is debate on whether at least 60% of the global population must be infected for herd immunity, or, conversely, mixing heterogeneity and pre‐existing cross‐immunity may allow substantially lower thresholds. Simulations are presented with a total of 1.58‐8.76 million COVID‐19 deaths over 5‐years (1/2020‐12/2024) globally (0.5‐2.9% of total global deaths). The most favorable figures in that range would be feasible if high risk groups can be preferentially protected with lower infection rates than the remaining population. Death toll may also be further affected by potential availability of effective vaccines and treatments, optimal management and measures taken, COVID‐19 interplay with influenza and other health problems, reinfection potential, and any chronic COVID‐19 consequences. Targeted, precise management of the pandemic and avoiding past mistakes would help minimize mortality.
Mental disorders represent a worldwide public health concern. Psychotherapies and pharmacotherapies are recommended as first line treatments. However, evidence has emerged that their efficacy may be ...overestimated, due to a variety of shortcomings in clinical trials (e.g., publication bias, weak control conditions such as waiting list). We performed an umbrella review of recent meta‐analyses of randomized controlled trials (RCTs) of psychotherapies and pharmacotherapies for the main mental disorders in adults. We selected meta‐analyses that formally assessed risk of bias or quality of studies, excluded weak comparators, and used effect sizes for target symptoms as primary outcome. We searched PubMed and PsycINFO and individual records of the Cochrane Library for meta‐analyses published between January 2014 and March 2021 comparing psychotherapies or pharmacotherapies with placebo or treatment‐as‐usual (TAU), or psychotherapies vs. pharmacotherapies head‐to‐head, or the combination of psychotherapy with pharmacotherapy to either monotherapy. One hundred and two meta‐analyses, encompassing 3,782 RCTs and 650,514 patients, were included, covering depressive disorders, anxiety disorders, post‐traumatic stress disorder, obsessive‐compulsive disorder, somatoform disorders, eating disorders, attention‐deficit/hyperactivity disorder, substance use disorders, insomnia, schizophrenia spectrum disorders, and bipolar disorder. Across disorders and treatments, the majority of effect sizes for target symptoms were small. A random effect meta‐analytic evaluation of the effect sizes reported by the largest meta‐analyses per disorder yielded a standardized mean difference (SMD) of 0.34 (95% CI: 0.26‐0.42) for psychotherapies and 0.36 (95% CI: 0.32‐0.41) for pharmacotherapies compared with placebo or TAU. The SMD for head‐to‐head comparisons of psychotherapies vs. pharmacotherapies was 0.11 (95% CI: –0.05 to 0.26). The SMD for the combined treatment compared with either monotherapy was 0.31 (95% CI: 0.19‐0.44). Risk of bias was often high. After more than half a century of research, thousands of RCTs and millions of invested funds, the effect sizes of psychotherapies and pharmacotherapies for mental disorders are limited, suggesting a ceiling effect for treatment research as presently conducted. A paradigm shift in research seems to be required to achieve further progress.
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on ...the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Assessment of researchers is necessary for decisions of hiring, promotion, and tenure. A burgeoning number of scientific leaders believe the current system of faculty incentives and rewards is ...misaligned with the needs of society and disconnected from the evidence about the causes of the reproducibility crisis and suboptimal quality of the scientific publication record. To address this issue, particularly for the clinical and life sciences, we convened a 22-member expert panel workshop in Washington, DC, in January 2017. Twenty-two academic leaders, funders, and scientists participated in the meeting. As background for the meeting, we completed a selective literature review of 22 key documents critiquing the current incentive system. From each document, we extracted how the authors perceived the problems of assessing science and scientists, the unintended consequences of maintaining the status quo for assessing scientists, and details of their proposed solutions. The resulting table was used as a seed for participant discussion. This resulted in six principles for assessing scientists and associated research and policy implications. We hope the content of this paper will serve as a basis for establishing best practices and redesigning the current approaches to assessing scientists by the many players involved in that process.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract Objective To present some simple graphical and quantitative ways to assist interpretation and improve presentation of results from multiple-treatment meta-analysis (MTM). Study Design and ...Setting We reanalyze a published network of trials comparing various antiplatelet interventions regarding the incidence of serious vascular events using Bayesian approaches for random effects MTM, and we explore the advantages and drawbacks of various traditional and new forms of quantitative displays and graphical presentations of results. Results We present the results under various forms, conventionally based on the mean of the distribution of the effect sizes; based on predictions; based on ranking probabilities; and finally, based on probabilities to be within an acceptable range from a reference. We show how to obtain and present results on ranking of all treatments and how to appraise the overall ranks. Conclusions Bayesian methodology offers a multitude of ways to present results from MTM models, as it enables a natural and easy estimation of all measures based on probabilities, ranks, or predictions.
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