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Metascience (also known as meta-research or evidence-based research) is the use of scientific methodology to study science itself. Metascience seeks to increase the quality of scientific research while reducing waste. It is also known as "research on research" and "the science of science", as it uses research methods to study how research is done and where improvements can be made. Metascience concerns itself with all fields of research and has been described as "a bird's eye view of science."[1] In the words of John Ioannidis, "Science is the best thing that has happened to human beings ... but we can do it better."[2]

Contents

HistoryEdit

in 1966, an early meta-research paper examined the statistical methods of 295 papers published in ten high-profile medical journals. It found that, "in almost 73% of the reports read [...] conclusions were drawn when the justification for these conclusions was invalid."[3] Later meta-research identified widespread difficulty in replicating results in many scientific fields, including psychology and medicine. This problem was termed "the replication crisis". Metascience has grown as a reaction to the replication crisis and to concerns about waste in research.[4]

Many prominent publishers are interested in meta-research and in improving the quality of their publications. Top journals such as Science, The Lancet, and Nature, provide ongoing coverage of meta-research and problems with reproducibility.[5] In 2012 PLOS ONE launched a Reproducibility Initiative. In 2015 Biomed Central introduced a minimum-standards-of-reporting checklist to four titles.

The first international conference in the broad area of meta-research was the Research Waste/EQUATOR conference held in Edinburgh in 2015; the first international conference on peer review was the Peer Review Congress held in 1989.[6] In 2016, Research Integrity and Peer Review was launched. The journal's opening editorial called for "research that will increase our understanding and suggest potential solutions to issues related to peer review, study reporting, and research and publication ethics".[7]

Areas of meta-researchEdit

Metascience can be categorize into five major areas of interest: Methods, Reporting, Reproducibility, Evaluation, and Incentives. These correspond, respectively, with how to perform, communicate, verify, evaluate, and reward research.[8]

MethodsEdit

Metascience seeks to identify poor research practices, including biases in research, poor study design, abuse of statistics, and to find methods to reduce these practices.[8] Meta-research has identified numerous biases in scientific literature.[9] Of particular note is the widespread misuse of p-values and abuse of statistical significance.[10]

ReportingEdit

Meta-research has identified poor practices in reporting, explaining, disseminating and popularizing research, particularly withing the social and health sciences. Poor reporting makes it difficult to accurately interpret the results of scientific studies and to identify biases and conflicts of interest in the authors. It is thought to contribute to problems in reproducability. Solutions include study registration, implementation of reporting standards, and greater transparency in scientific studies (including better requirements for disclosure of conflicts of interest).[8]

ReproducabilityEdit

The replication crisis is an ongoing methodological crisis in which it has been found that many scientific studies are difficult or impossible to replicate or reproduce.[11][12] While the crisis has roots in the meta-research of the mid to late 1900s, the phrase "replication crisis" was coined in the early 2010s[13] as part of a growing awareness of the problem.[8]

EvaluationEdit

Metascience seeks to create a scientific foundation for peer review. Meta-research evalutes peer review systems including pre-publication peer review, post-publication peer review, and open peer review. It also seeks to develop better research funding criteria.[8]

IncentivesEdit

Metascience seeks to promote better research through better incentive systems. This includes an evaluation of the accuracy, effectiveness, costs, and benefits of old and new approaches to ranking and evaluating the performance, quality, value of research, individuals, teams, and institutions.[8]

ApplicationsEdit

MedicineEdit

Clinical research in medicine is often of low quality, and many studies cannot be replicated.[14][15] An estimated 85% of research funding is wasted.[16] Additionally, the presence of bias affects research quality.[17] The pharmaceutical industry exerts substantial influence on the design and execution of medical research. Conflicts of interest are common among authors of medical literature[18] and among editors of medical journals. While almost all medical journals require their authors to disclose conflicts of interest, editors are not required to do so.[19] Financial conflicts of interest have been linked to higher rates of positive study results. In antidepressant trials, pharmaceutical sponsorship is the best predictor of trial outcome.[20]

Blinding is another focus of meta-research, as error caused by poor blinding is a source of experimental bias. Blinding is not well reported in medical literature, and widespread misunderstanding of the subject has resulted in poor implementation of blinding in clinical trials.[21] Furthermore, the success or failure of a blind is rarely measured or reported.[22] Research showing the failure of blinding in antidepressant trials has led some scientists to argue that antidepressants are no better than placebo.[23][24] In light of meta-research showing failures of blinding, CONSORT standards recommend that all clinical trials assess and report the quality of blinding.[25]

Studies have shown that systematic reviews of existing research evidence are sub-optimally used in planning a new research or summarizing the results.[26] Cumulative meta-analyses of studies evaluating the effectiveness of medical interventions have shown that many clinical trials could have been avoided if a systematic review of existing evidence was done prior to conducting a new trial.[27][28][29] For example, Lau et al.[27] analyzed 33 clinical trials (involving 36974 patients) evaluating the effectiveness of intravenous streptokinase for acute myocardial infarction. Their cumulative meta-analysis demonstrated that 25 of 33 trials could have been avoided if a systematic review was conducted prior to conducting a new trial. In other words, randomizing 34542 patients was potentially unnecessary.

One study found that only 2 of 25 randomized clinical trials published in five major general medical journals during May 1997 included an updated systematic review in the discussion of results. Subsequent reports showed confirmed this result.[30][31][32][33] These reports also showed that the majority of randomized clinical trials published in five major general medical journals did not present any systematic reviews of existing evidence to justify the research.[31][32][33] Robinson et al.[34] analyzed 1523 clinical trials included in 227 meta-analyses and concluded that "less than one quarter of relevant prior studies" were cited. They also confirmed the earlier findings that clinical trial reports do not present systematic review to justify the research or summarize the results.[34]

PsychologyEdit

Metascience has revealed significant problems in psychological research. The field suffers from high bias, low reproducibility, and widespread misuse of statistics.[35][36][37] The replication crisis affects psychology more strongly than any other field; as many as two-thirds of highly publicized findings may be impossible to replicate.[38] Meta-research finds that 80-95% of psychological studies support their initial hypotheses, which strongly implies the existence of publication bias.[39]

The replication crisis has led to renewed efforts to re-test important findings.[40][41] In response to concerns about publication bias and p-hacking, more than 140 psychology journals have adopted result-blind peer review, in which studies are pre-registered and published without regard for their outcome.[42] An analysis of these reforms estimated that 61 percent of result-blind studies produce null results, in contrast with 5 to 20 percent in earlier research. This analysis shows that result-blind peer review substantially reduces publication bias.[39]

Psychologists routinely confuse statistical significance with practical importance, enthusiastically reporting great certainty in unimportant facts.[43] Some psychologists have responded with an increased use of effect size statistics, rather than sole reliance on the p values.[citation needed]

PhysicsEdit

Richard Feynman noted that estimates of physical constants were closer to published values than would be expected by chance. This was believed to be the result of confirmation bias: results that agreed with existing literature were more likely to be believed, and therefore published. Physicists now implement blinding to prevent this kind of bias.[44]

Associated fieldsEdit

ScientometricsEdit

Scientometrics concerns itself with measuring bibliographic data in scientific publications. Major research issues include the measurement of the impact of research papers and academic journals, the understanding of scientific citations, and the use of such measurements in policy and management contexts.[45]

Scientific data scienceEdit

Scientific data science is the use of data science to analyse research papers. It encompasses both qualitative and quantitative methods. Research in scientific data science includes fraud detection[46] and citation network analysis.[47]

See alsoEdit

ReferencesEdit

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Further readingEdit

External linksEdit