Why is this important? (Important Because)
From The Embassy of Good Science
A description to provide more focus to the theme/resource (max. 200 words)
- ⧼SA Foundation Data Type⧽: Text
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A successful career for researchers is often equivalent to the production and acceptance of peer-reviewed manuscripts. In fact, the number of publications a researcher has is commonly used as a parameter for career progression or funding acquisition.
Authorship matters because the entire research and publication process relies on trust. Authorship conveys significant privileges, responsibilities, and legal rights, and it is fair that only those who have actively participated in the work should benefit from the positive aspects of being an author and being accountable for all aspects of the research.
Although the general guidelines on authorship are common sense, the pressure to be a productive scholar and problems resulting from different interpretations of the general guidelines have encouraged a number of questionable research practices. These include honorary authorship, gift authorship, prestige authorship, plagiarism, self-plagiarism, citation amnesia, multiple submissions and duplicate publication. +
When submitting an article to a journal, author’s consent for publication must be attached. Written formal consent ensures that the publisher has the author’s permission to publish research findings.'"`UNIQ--ref-00000015-QINU`"' With the consent, the author gives the publisher license of the copyright which provides the publisher with the exclusive right to publish and sell the research findings in all languages, in whole or in part.'"`UNIQ--ref-00000016-QINU`"' All authors guarantee that the research findings have not been previously published. If they were published, the authors should obtain permission necessary to publish it.'"`UNIQ--ref-00000017-QINU`"''"`UNIQ--ref-00000018-QINU`"'
However, scenarios with multiple authors can present difficulties for obtaining consent: One or more authors can refuse to give their consent, some authors cannot be tracked down,'"`UNIQ--ref-00000019-QINU`"' whereas sometimes authors withdraw the consent.'"`UNIQ--ref-0000001A-QINU`"' In case when not all authors give the consent, the article can be retracted.'"`UNIQ--ref-0000001B-QINU`"'
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Publishing certain research data, obtained in circumstances of confidentiality between researcher and participant, can be made accessible to the rest of the world'"`UNIQ--ref-00000011-QINU`"' and this can mean breaching of that confidentiality. This is why research participants need to know which data will be revealed to the public. In order to submit and subsequently publish case reports, authors have to obtain participant’s consent for publication. For example, in the case of unusual diagnosis in medical research or some details regarding the participant’s history (age, sex or occupation) along with the author’s name and affiliation that can reveal the participant’s identity, the participant’s consent is indispensable.'"`UNIQ--ref-00000012-QINU`"' Some of the examples of identifying information are descriptions of individual case histories, photographs, videos, x-rays or genetic pedigrees.'"`UNIQ--ref-00000013-QINU`"'
Researchers should inform participants that anyone who has access to Internet would be able to view the published article.'"`UNIQ--ref-00000014-QINU`"' Consent for publication should be obtained from participants or their legal guardians if the participants are under 16. In case of deceased persons, consent should be obtained by the deceased family or relatives.'"`UNIQ--ref-00000015-QINU`"' Consent is voluntarily and participant is free to withdraw it before the publication.'"`UNIQ--ref-00000016-QINU`"' +
Although SSH have embraced the practice of open access publishing, there is still a lot of room for progress, particularly regarding the access to the research monographs, one of the main dissemination outputs of these disciplines. Therefore, the main goal of HIRMEOS is to integrate the open access monographs into “open science ecosystem”'"`UNIQ--ref-0000000D-QINU`"' and to help increase the visibility and value of the SSH work.'"`UNIQ--ref-0000000E-QINU`"'
HIRMEOS also plans to contribute to dissemination of open access monographs by implementing advanced tools for researchers and publishers'"`UNIQ--ref-0000000F-QINU`"' and developing a set of services on the current platforms for open access monographs: identification service, annotation service, peer-review certification system, named entity recognition and metrics service.'"`UNIQ--ref-00000010-QINU`"' For example, identification service refers to developing tools which allow the unique identifiers for content (DOI) and authors (ORCID) automatically validate the published content via the Directory of Open Access Books ([https://www.doabooks.org/ DOAB]). Open annotation will add open peer-review and open commentary to the documents and link them through unique identification, which will enhance interactions with users. Finally, the usage metrics service will standardize usage measures on the documents and add usage indicators such as downloads and social media impact.'"`UNIQ--ref-00000011-QINU`"'
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Although many abstracts are available in different bibliographic databases, their use is limited in a number of ways. For example, they require a subscription, they are not machine-accessible, or are restricted to a one specific discipline.'"`UNIQ--ref-00000009-QINU`"' The most important benefits of open abstracts are their visibility, and easier use of text mining,'"`UNIQ--ref-0000000A-QINU`"' especially for researchers in developing countries who perhaps do not have the means for subscription to expensive journals.'"`UNIQ--ref-0000000B-QINU`"'
The initiative recommends scholarly publishers to make their abstracts more visible and easily accessible by depositing them to Crossref, a non-profit open repository that publishers use to register and share Digital Object Identifiers (DOIs) for their publications.'"`UNIQ--ref-0000000C-QINU`"' Through Crossref, research abstracts across disciplines will become easily searchable and machine-readable.'"`UNIQ--ref-0000000D-QINU`"' +
Citations are indispensable part of scholarly publications because they direct readers to sources, acknowledge other works in bibliographic references, help researchers avoid misconduct such as plagiarism, and enable the evaluation of publications.'"`UNIQ--ref-0000000F-QINU`"''"`UNIQ--ref-00000010-QINU`"'
Usually citation data are not freely accessible or machine-readable, which makes them unavailable to a great number of independent scholars.'"`UNIQ--ref-00000011-QINU`"''"`UNIQ--ref-00000012-QINU`"' To enhance their use, they should be available to everyone. They should also be structured (expressed in a machine-readable format), separable (available without the need to go to the source, such as articles or books), and open (freely accessible and reusable without restrictions).'"`UNIQ--ref-00000013-QINU`"''"`UNIQ--ref-00000014-QINU`"' Achieving this aim would be beneficial to independent researchers, publishers, funding agencies, academic institutions and the public in general.'"`UNIQ--ref-00000015-QINU`"'
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Whether access to scientific literature should be open or behind paywalls is a prominent topic of debate in the research community. In a 2018 analysis on open access publishing, it was estimated that 28% of all current journal articles are freely available online. '"`UNIQ--ref-00000005-QINU`"'This proportion has been growing over the last 20 years. In 2015, the most recent year that was examined, 45% of all articles were reported to be open access .'"`UNIQ--ref-00000006-QINU`"' The adoption of open access practices however differs between publishers and research fields.
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Journal editors often need to make difficult decisions about allegations of misconduct, authorship disputes, conflicts of interest, lack of ethical oversight of a submission, and so on. The COPE “Principles of Transparency and Best Practice in Scholarly Publishing” and “Core Practices” consist of guidelines and tools to assist editors, publishers and other stakeholders to “preserve and promote the integrity of the scholarly record through policies and practices that reflect the current best principles of transparency and integrity”. '"`UNIQ--ref-00000002-QINU`"'
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The integrity of the scientific record is important because published research serves as a basis for new research or application in practice. If the published report on research results is not correct, it may waste future research effort and, what is more dangerous, have direct adverse effects on the public. This is particularly relevant for health research because incorrect health research results may cause harm to patients or the general population. After publication, when it becomes apparent that the results and/or interpretations of an article are seriously flawed, an article can be retracted. Retraction differs from correction, where an article is corrected after publication. Retraction is more serious as a retracted paper should no longer be considered as a source of scientific knowledge. It is also a signal to alert other scholars of the errors. Main reasons for retraction are honest research errors, plagiarism, redundant publication, fabrication, falsification, experimental artefacts and unexplained irreproducibility. '"`UNIQ--ref-0000000A-QINU`"''"`UNIQ--ref-0000000B-QINU`"' The COPE guidelines state that retractions are not to punish the authors. In addition, authors of a paper, as well as others, can call for a retraction upon discovering errors. COPE guidelines state that retracted papers should be labelled as retracted and be accessible (both offline and online). Most journals have their own retraction guidelines. Over the years an increase in the percentage of retracted papers is observed. '"`UNIQ--ref-0000000C-QINU`"' The two possible explanations for this are 1) an increase in pressure to publish flawed papers or 2) an increase in detection of such flaws. '"`UNIQ--ref-0000000D-QINU`"' Nonetheless, retractions have an impact on the scientific community. First, it is a waste of resources, both in financial terms, time and participants. Second, when unnoticed, authors implicitly or explicitly use retracted sources as valid scientific results leading to decreasing trustworthiness of science. '"`UNIQ--ref-0000000E-QINU`"'
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Collaborations are becoming more frequent and gather anever increasing number of researcher. At the same time publications remain a key source of academic credit and career advancement. It is important to allocate credit for research contributions in a fair and transparent way.
The UK Research Integrity Office outlines why authorship standards matter:
“Correct authorship of research publications matters because authorship confers credit, carries responsibility, and readers should know who has done the research. Denying authorship to somebody who deserves it denies recognition and academic credit since publications are used to assess academic productivity. Including an undeserving author is unfair since this person gets credit for work they have not done. Omitting a deserving author from an author also list misleads readers (including journal editors) and may mask conflicts of interest.” '"`UNIQ--ref-00000005-QINU`"'
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Although the use of pre-print servers has been rising over the past decade, the COVID-19 pandemic has witnessed an unprecedented surge in the number of pre-prints. Fraser et al.<sup>5</sup> found that 25% or all articles on COVID-19 in the first 10 months of the pandemic (more than 30,000 manuscripts) were first posted as pre-prints. Besides attracting the attention of the scientific community, these manuscripts have also received substantial coverage in social media, news outlets and from the general public. <sup>6</sup> They have also played a crucial role in shaping the standard of care for COVID-19. In case of the RECOVERY trial, which studied the use of the steroid drug dexamethasone in critically ill COVID patients, the pre-publication of the benefits of the drug led to its prompt incorporation into treatment guidelines, and possibly benefited many gravely ill patients. <sup>7,8</sup>
On the other hand, disseminating information prior to peer review has also had negative consequences during the pandemic. A study that reported beneficial effects of a combination therapy of hydroxychloroquine and azithromycin was published in May 2020 on MedRxiv. <sup>9</sup> It was later withdrawn due to its questionable methodology, but not before it was widely publicized as being a “game-changer in the history of medicine” by a prominent political figure, leading to huge demands, severe shortages and indiscriminate use of these drugs. <sup>10</sup> Another paper that received widespread attention prior to its retraction reported an “uncanny similarity” between the protein structures or the COVID-19 virus and HIV, and concluded that this similarity was “unlikely to be fortuitous”, leading many to speculate that the pandemic was the result of a bioengineered weaponized virus. <sup>11,12</sup> Although the above examples are clear-cut and have been cited often, it is very likely that less evident instances of the misuse of non-peer reviewed information exist, making it a difficult challenge to address.
HARKing can increase the chance of falsely rejecting the null hypothesis, or type I error. '"`UNIQ--ref-00000002-QINU`"' Each time when a statistical analysis is being done, theories or hypotheses are formalized in terms of mathematical models. '"`UNIQ--ref-00000003-QINU`"' Models are built from main outcome measure and factors that are supposed to influence the main outcome measure. '"`UNIQ--ref-00000004-QINU`"' Factors that are supposed to determine the outcome measure are usually derived either from published research or data gathered in experiments or surveys. Once a model with satisfactory explanatory or predictive properties is built, it needs to be externally validated i.e. tested on a new, similar dataset. '"`UNIQ--ref-00000005-QINU`"' This is needed because model might be so well suited for the data on which it was built that it becomes too specific, and thus loses ability to be generalized on somewhat similar datasets. '"`UNIQ--ref-00000006-QINU`"' If we put this in more technical terms, some of explanatory or predictive factors in the model might correlate with real causes of effect only in our dataset but not in the other similar datasets.
Replication of studies is the way through HARKing can be recognized, '"`UNIQ--ref-00000007-QINU`"' but that’s only after the damage has been done. Pre-registration of studies, with clearly stated hypotheses and planned statistical analysis, is how we can hope to prevent HARKing.
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Duplicate publications are redundant because they present the same data. As readers are not made aware of this fact, they could consider the two (or more) publications to be separate studies. This may be harmful when such studies are included in evidence synthesis, such as systematic reviews and meta-analyses about health interventions, because they may skew the evidence.'"`UNIQ--ref-00000005-QINU`"' This can lead to erroneous recommendations for health practice, which may result in increased risk for patients.
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The term “funding effect” was formed in the 1980s, when it was discovered that researchers do not always report their results and conclusions honestly, but distort the findings to support the aims of the funding sources.'"`UNIQ--ref-0000000B-QINU`"' It has also shown that industry sponsored studies are more likely to publish positive results than those sponsored by not-for-profit and independent organisations.'"`UNIQ--ref-0000000C-QINU`"' One of the reasons is that funders may prevent publishing of the manuscript containing unfavourable results or even take some legal acts against researchers.'"`UNIQ--ref-0000000D-QINU`"' For example, in one case a sponsor sued a haematologist for breach of contract because she reported “concerns over the safety of a drug she was evaluating”.'"`UNIQ--ref-0000000E-QINU`"'
This distortion of reporting of the study results and conclusions occurs more often in studies funded by the pharmaceutical industry.'"`UNIQ--ref-0000000F-QINU`"' This can cause serious consequences because it directly affects the practice of medicine.'"`UNIQ--ref-00000010-QINU`"' Nevertheless, every researcher with a funded study could be pressured to report results and conclusions that are more favourable to the funders, regardless of the topic or research area of the study.
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In recent years, several academic disciplines – perhaps most strongly psychology – have witnessed a replication crisis, casting doubt on the validity of seemingly well-established findings and theories. The prevalence of HARKing, evidenced by empirical studies of research misconduct and research misbehavior, is considered one of several driving factors behind the replication crisis. This is due to two reasons: Firstly, data that were used to generate a hypothesis cannot be used to test that same hypothesis in any meaningful way. Portraying an empirically inspired post hoc hypothesis as a priori violates the falsification principle crucial for hypothesis-driven (that is, confirmatory) empirical research. Secondly, suppressing unsupported a priori hypotheses and the attendant failure to report null effects throws away opportunities to cast doubt on the validity of hypotheses derived from extant knowledge. Consequently, multiple disconfirmations of a hypothesis may go unnoticed when researchers HARK because disconfirmations are not reported.
While pure HARKing is unquestionably a detrimental research practice, the same is not necessarily true for transparent forms of HARKing. Transparent HARKing (THARKing) occurs when researchers develop post hoc hypotheses (that is, hypothesize after the results are known), but do so transparently and based on theory. If done transparently and inspired not only by results but also by theory, post hoc hypothesizing does not misportray the research process because exploratory findings are clearly labeled as such. +
Improper data use undermines the ethos of science and the corresponding misleading results can misguide and distort the production of knowledge.
Examples of improper data use include:
*'''Massaging''': … extensive transformations or other maneuvers to make inconclusive data appear … conclusive
*'''Extrapolating''': … predicting future trends based on unsupported assumptions …
*'''Smoothing''': discarding data points too far removed from expected … values
*'''Slanting''': … selecting certain trends in the data, … discarding others which do not fit …
*'''Fudging''': creating data points to augment incomplete data sets …
*'''Manufacturing''': creating entire data sets de novo, … '"`UNIQ--ref-0000000A-QINU`"'
Data dredging is looking for too many possible associations in a dataset to see of any of them are statistically significant. Data dredging results in false positive results.
“When a large number of associations can be looked at in a dataset where only a few real associations exist, a P value of 0.05 is compatible with the large majority of findings still being false positives.” '"`UNIQ--ref-0000000B-QINU`"'
'''Origin of words'''
There are several terms describing the act of data dredging. These include:
<br />
*"Data Dredging"'"`UNIQ--ref-0000000C-QINU`"'
*"Data Fishing"'"`UNIQ--ref-0000000D-QINU`"'
*“Data Snooping,”
*“P-hacking”
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The media is the most powerful tool for spreading new information about scientific studies. Therefore, researchers and academic institutions place a strong emphasis on communicating research findings to the media '"`UNIQ--ref-00000016-QINU`"'. However, sometimes the media distort research findings, which results in the spreading of misinformation '"`UNIQ--ref-00000017-QINU`"'. Frequent use of oversimplified language, exaggeration, sensationalist reporting and the avoidance of complex issues are some of the main reasons for the misrepresentation of researching findings by the media '"`UNIQ--ref-00000018-QINU`"''"`UNIQ--ref-00000019-QINU`"''"`UNIQ--ref-0000001A-QINU`"'. Furthermore, when follow-up studies undermine the results and conclusions of the initial study, the media usually does not correct or supplement its previous reports or provide a new report altogether '"`UNIQ--ref-0000001B-QINU`"'.
Sensationalist reporting of medical research is not rare and can have serious consequences. It can raise false hopes or generate needless fear '"`UNIQ--ref-0000001C-QINU`"'. However, the media isn’t solely responsible for misleading the public about research findings. In 2014, research showed that the majority of university press-releases, usually approved by the lead researcher, tend to exaggerate research findings. Because reporters rely on these press-releases, inaccurate information is more widely disseminated '"`UNIQ--ref-0000001D-QINU`"'. Therefore, in order to improve reports of research findings and their presentation to the public, close collaboration between researchers and journalists is essential '"`UNIQ--ref-0000001E-QINU`"'.
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In early 20<sup>th</sup> century, the concept of a P-value was introduced, along with a decision rule that stated that if p<0.05, then the null hypothesis should be rejected '"`UNIQ--ref-00000018-QINU`"'. In other words, when a P-value is less than 0.05, the results are regarded as “statistically significant” '"`UNIQ--ref-00000019-QINU`"'.
Journals widely encourage the use of the method of inferring from P-values for publication, which puts researchers under a lot of pressure to publish “statistically significant” results '"`UNIQ--ref-0000001A-QINU`"'. According to recent findings, 96% of abstracts and full-text articles in the biomedical literature from 1990 to 2015 presented p<0.05, which is considered “too good to be true”, and indicates that there is a practice of selective reporting '"`UNIQ--ref-0000001B-QINU`"'.
Developments in decision theory, information theory, mathematical modelling and computing in the second half of the 20<sup>th</sup> century shed a completely different light on the use of P-values and statistical inference in general '"`UNIQ--ref-0000001C-QINU`"'. By 2016, mounting criticisms of the use and interpretation of P-values prompted the ASA to publish a policy statement '"`UNIQ--ref-0000001D-QINU`"'.
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There is no such thing as perfect research. Every study, whether it is experimental or observational, has its limitations and deficiencies that can influence outcomes of the research '"`UNIQ--ref-00000017-QINU`"'. Not reporting them properly is dangerous, because it could lead to over-confidence in flawed findings '"`UNIQ--ref-00000018-QINU`"'. This, consequently, could reflect negatively on trust between scientists and decrease the public trust in science '"`UNIQ--ref-00000019-QINU`"'. Different types of limitations that can occur during the research process in the first place are related to sample size, methodology, lack of resources and time constraints '"`UNIQ--ref-0000001A-QINU`"'.
Since limitations are a natural part of the research process, they should be fully reported and described. Reporting flaws and limitations shows that a researcher fully understands the topic '"`UNIQ--ref-0000001B-QINU`"', informs and gives readers an opportunity to detect existing gaps in research, '"`UNIQ--ref-0000001C-QINU`"' and provides them with a possibility to identify new research questions '"`UNIQ--ref-0000001D-QINU`"'. Finally, presenting study limitations also shows a researcher’s honesty and transparency '"`UNIQ--ref-0000001E-QINU`"''"`UNIQ--ref-0000001F-QINU`"'. Knowing limitations and deficiencies of a certain study is an essential tool which helps to modify every decision based on considerations of risks and benefits.
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Research in biomedical sciences reveals that positive results have a higher chance of being published. Because of that, negative results (for example, the lack of effect of some therapy) might be unavailable to the scientific community. Consequently, when other researchers conduct systematic reviews and meta-analysis, the results are distorted in favor of the positive finding. Clinical trials with negative results, and those with reported serious side effects, often don’t get published, which is dangerous, unfair to participants, and a waste of resources. '"`UNIQ--ref-0000000B-QINU`"' Getting negative results in a costly project and after a lot of hard work can be very demotivating, disappointing and can negatively impact young researchers’ careers. Some supervisors may not be happy to publish negative results, and in that way add to the climate of positive-publications-only.
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