Maintenance:ExportThemes

	Type	Why is this important?
Cognitive dissonance and moral distress	Principles & Aspirations	In participating in the communal practice of science, we have to accept certain standards of excellence (related to values, like truth) and rules to follow (to give an accurate account of the authors’ contributions). Thus, we are likely to experience cognitive dissonance or moral distress, when confronted with conflicting imperatives (for instance the need to give an authorship to one’s superior, even if she did not contribute to the specific paper). Cognitive dissonance theory holds that when we experience cognitive or dissonance or moral distress, we tend to justify our behavior. The more often we engage in justifying our unethical behavior, the more we will perceive this unethical behavior as already justified and the more likely we are to engage in it again. Although we will always be blind to our own ignorance to a certain degree, we can learn to recognize our self-justification strategies as indicators of our (evolving) vices. By recognizing why we engage in self-justification strategies and how they impact our decision-making, we can foster conditions for good research. Virtue ethics emphasizes that we need to develop virtues in order to deal with imperatives that are detrimental to good research.'"`UNIQ--ref-00000000-QINU`"' According to MacIntyre, “virtues serve three functions: to enable individuals to achieve excellence in practice, to protect the practice from threat of corruption by goods of efficiency, and to be constitutive components of the good human life”.'"`UNIQ--ref-00000001-QINU`"' So virtues can be seen as crucial to counter corruptive tendencies in the research system. '"`UNIQ--ref-00000002-QINU`""`UNIQ--ref-00000003-QINU`"' Cultivating sensitivity for cognitive dissonance and moral distress is an important element of research integrity education.'"`UNIQ--ref-00000004-QINU`"' '"`UNIQ--ref-00000005-QINU`"'It may support us in our attempts to find the right middle between being lenient and being too harsh on ourselves. What is the right middle depends on situational factors, as well as individual capabilities of the researcher. Knowing the right middle is not something that we can learn solely by understanding the underlying dynamics. It has to be learned in practice, over and over again. If we keep in sight the goods of excellence to achieve, we can be prepared not to be discouraged if we fail to assess a situation appropriately, but rather use any mistake we make as a means to fine-tune our cognitive strategies and moral behavior. '"`UNIQ--references-00000006-QINU`"'
Collaborative working	Good Practices	A lot of scientific work happens through collaboration. Yet, collaborations can also lead to conflict when there is lack of clarity about the roles of different collaborators, or when expectations are not met. Collaborative work has become more important over the past few decades, partially due to the rise of interdisciplinary research. The number of co-authors on a paper is a potential indifcatar for the rise of collaborations, with the average number of co-authors on research papers for the PNAS rose from 3.9 in 1981 to 8.4 in 2001. '"`UNIQ--ref-00000050-QINU`"' '"`UNIQ--references-00000051-QINU`"'
Conflict of interests	Misconduct & Misbehaviors	Conflict of interests erodes objectivity of science and leads to corruption, and most certainly create a space for bias in decision making. Conflict of interest can happen in a variety of research areas and human activities, but when we take consequences into consideration, in some areas such as science and research it becomes especially important.'"`UNIQ--ref-000002A1-QINU`"' A recent review revealed that industry sponsored studies are more often in favour to the sponsors’ products compared with studies with other sources of funding.'"`UNIQ--ref-000002A2-QINU`"' Because of the effect it can potentially have on research, scientific journals require a separate declaration of conflict of interest when submitting scientific articles.'"`UNIQ--ref-000002A3-QINU`"' '"`UNIQ--references-000002A4-QINU`"'
Data Practices and Management	Good Practices
Development and Value of National Research Integrity Codes	Other	Research integrity and research misconduct are of immense interest to stakeholders both within and outside the scientific community. Integrity in research not only enables good quality research, supports effective collaborations and delivers benefits to the public, but also safeguards the trust of the public in the research community. Research misconduct, on the other hand, can diminish trust in science, affect the quality of research results and misspend public funds. To prevent this, it is crucial that researchers receive guidance on research integrity. National documents are important in laying down specific norms that are to be followed. For instance, the Estonian document provides considerations to be taken into account during different stages of the research, such as planning, conduct and publication 4. In the Danish and Swiss guidelines, the procedures to address a suspected breach of integrity are described in detail 5, 6. The Swiss document, in addition, also provides the legal background and implications of misconduct 6.   Whilst there is a value for countries to have their own RI code or statement, challenges can arise when there are divergences both among national documents and between national level documents and the ECoC regarding the guiding values of research integrity and what constitutes research misconduct. These divergences are important to map and define, for two broad reasons:  firstly, it could mean that in cases of research misconduct in international collaborations, responses to misconduct may vary, depending on the national norms, and secondly, these divergences go against the harmonizing effect envisaged in the ECoC, and could affect the overall coherence of research integrity guidance 4. These considerations are of importance not only to policy makers, but also to research institutions and researchers in general.
Dialogue versus debate	Principles & Aspirations	Research integrity issues often require thorough consideration, as it is not always simple to apply rules and to know what is the right action given a code of conduct. A dialogue can help to find ways to deal with such issues. A dialogue can take place within the research team, or in a group aiming at reflection on research integrity issues. The idea of dialogue is not only being nice and friendly. The aim is to come to a better view of the situation, gaining knowledge and understanding. This requires that one seriously investigates the relevance of the perspective of the other. Being open to the perspective of the other does not mean simply giving up one’s own point of view, but being prepared to learn from the other’s point of view. By exchanging perspectives, dialogue can result in a fusion of horizons.'"`UNIQ--ref-00000027-QINU`"' It is important to distinguish dialogue from debate. In a nutshell, the most relevant differences are the following :'"`UNIQ--ref-00000028-QINU`""`UNIQ--ref-00000029-QINU`"' Dialogue focuses on learning from differences; debate focuses on finding the one right answer Dialogue focuses on understanding the other; debate focuses on convincing the other Dialogue focuses on listening and questioning; debate focuses on speaking and arguing Dialogue focuses on looking for strengths in the position of the other; debate focuses on looking for weaknesses in the position of the other Dialogue focuses on exploring and considering; debate focuses on attacking and defending Dialogue focuses on thinking slow; debate focuses on thinking fast Dialogue focuses on reflection and learning; debate focuses on concluding and deciding '"`UNIQ--references-0000002A-QINU`"'
Dutch National Survey on Research Integrity	Misconduct & Misbehaviors	Many researchers work in environments that stimulate responsible behavior. However, scholarly environments are also complex and full of competition. Competition can stimulate people to work hard, but may also have downsides. What is an optimal research environment? What working conditions are detrimental to good research practices? Fostering responsible research and preventing questionable practices is important. However, the causes behind the variability in engagement in responsible and questionable practices and research misconduct are largely unknown. Once known, strategies to enhance responsible research practices while reducing questionable practices can be developed and evaluated. The NSRI attempts to play an important role in solving this. Watch this two-minute video on why research integrity matters to every one of us in society. To optimally address all 40,000 academic researchers in The Netherlands, a survey instrument was the most fitting choice for this project. While it has its drawbacks, especially when studying a complex topic such as research integrity, the primary goal of this survey was to get concrete estimates of RRP, QRPs, and their associated factors for these practices across disciplines. Balancing time to answer such a survey, while protecting the privacy and the target sample size of about 40,000 researchers, a survey tool was most appropriate. This does not exclude us from exploring themes that will arise from the survey results through more detailed focus group discussions at the next stage of this project. The Dutch National Survey on Research Integrity (NSRI) is unique in a number of ways:  It aims to provide valid disciplinary field-specific estimates on the occurrence of responsible research practices and questionable research practices across the biomedical sciences, the humanities, natural sciences and engineering, and the social and behavioral sciences. It targets the entire population of academic researchers in The Netherlands. The survey employs a technique known as the Randomized Response (RR) which has shown to elicit more honest answers around sensitive topics.  It examines a broad range of factors that may impact scholars engagement in responsible research practices and questionable research practices. How is the privacy of participants joining the NSRI guaranteed? Given the sensitivity of the topic, NSRI has paid very close attention to fully ensuring the protection of the identity of the participants and their research institutions. Our privacy protection measures include: No personal identifying data except disciplinary field and academic rank (PhD, A/Prof, Full Prof) were collected in the survey The use of the Randomized Response (RR) technique for the two most sensitive questions. RR which has been proven in research on doping and social security fraud to reduce the effect of social desirability and thereby elicit a greater sense of trust with respondents. It does so by creating a probabilistic rather than direct association between the answers of respondents and the sensitive question (see also Meta-Analysis of Randomized Response Research- Thirty-Five Years of Validation. Sociological Methods & Research 2005; 33 (3): 319-348) All data was collected by a trusted third party, Kantar Public so the research team never directly received any personal data. IP addresses were not collected. The research team only received anonymized data by disciplinary field and academic rank. Because of these measures, no data was analysed or published that can be traced to individual participants or specific research institutions. You can access the NSRI’s publications here. To find out more about the NSRI, visit our FAQ page here.
Epistemic virtues	Principles & Aspirations	The ultimate goal of science is to seek truth at the realm of material things. Because of that, science itself cannot be practiced without somehow tapping into the field of epistemology. Ideally, researchers should be attentive, careful, thorough, impartial, open, willing to exchange ideas and aware of their own fallibility. '"`UNIQ--ref-00000002-QINU`"' These traits could serve as a preventative measure for research misconduct and other, various practices that are detrimental to science. '"`UNIQ--references-00000003-QINU`"'
Funders	Good Practices	Financial support for research is often obtained from intramural (e.g. from university funds) or extramural (e.g. from funding agencies) sources. Funders have some responsibility for ensuring that the research they fund is conducted in accordance with relevant laws and good research practices. However, funders’ oversight and reporting standards differ greatly. Collaborations, particularly those related to funding, also have the potential to influence the ways in which research questions are defined and the results presented. A particular concern involves collaborations between academia and industry-sponsors. Studies have shown that industry-sponsored research tends to favor the sponsor.'"`UNIQ--ref-00000021-QINU`"' Therefore, funders need to be transparant about their aims, researchers should declare the source of funding, academic autonomy must be ensured, and researchers must be aware that funders can potentially influence research. '"`UNIQ--references-00000022-QINU`"'
How to be a good lab partner	Good Practices	Working in the laboratory can be challenging. Like in every other collective you are stuck with people that you like and do not like, colleagues that work and that are slacking, deadlines are always pressing down, equipment is damaged and you must stay professional. A new study emphasizes the importance of encouraging positive workplace social relationships, particularly male-female friendships'"`UNIQ--ref-00000947-QINU`"'. Thus, this theme helps us to induce all the virtues that one researcher must have to live a productive and fulfilled professional life. '"`UNIQ--references-00000948-QINU`"'
Mertonian norms	Principles & Aspirations	Robert Merton developed his norms as a way to describe what constitutes the ethos of modern science. Since then, research has shown that various practice-based problems still occur, such as research misconduct, falsification, fabrication, plagiarism and questionable research practices. Scientists are still aiming for improvement, and Mertonian norms are still very much relevant.
Moral conflict and moral dilemma	Principles & Aspirations	Research integrity can involve a situation of moral conflict. This means that two courses of action are possible, which exclude one another. If one goes for one action, the alternative cannot be realized. Moreover, one has to choose between both actions; a third option, such as not making a choice, is not possible. An example is the choice between adding a person as an author to an article or not. There is no third option: either the person is made author, or not. A moral conflict implies two conflicting values. In the case of authorship, these values might be gratitude (for a – albeit small - contribution) versus righteousness (acting in line with the authorship guidelines). Sometimes, moral conflicts can be resolved because one of the values clearly overrides the other. Thus, from a research integrity perspective, authorship requirements are more important than gratitude. In order to do justice to the value of gratitude, the person can be mentioned in an acknowledgement. However, there are examples of situations in research where conflicts can be irresolvable, because the person who has to choose feels the obligation to do justice to two incompatible values. In such cases, one is confronted with a moral dilemma .'"`UNIQ--ref-00000035-QINU`"' '"`UNIQ--ref-00000036-QINU`"' A moral dilemma is a conflict situation in which the choice one makes causes a moral harm, which cannot be restlessly repaired. Take the example of how to respond when a fellow researcher needs help, but refuses your assistance. In light of the value of care, you should at least try to convince them that support is needed. On the other hand, the value of autonomy might indicate that you should not impose yourself upon them. Whatever you decide to do, you do harm to one of the two values involved. If you choose to try and get them to accept support, they might feel being treated as an incompetent researcher. If you choose to let go, they might get in serious difficulty with their research. '"`UNIQ--references-00000037-QINU`"'
Peer review	Good Practices	In a scientific journal, the editor is responsible for the quality of published research. Of course, an editor cannot possibly know everything about all areas of research. They must, therefore, seek help from other experts to assess the quality of research. They rely on their knowledge and experience to identify possible weaknesses in research. '"`UNIQ--ref-000000FD-QINU`"' For authors, the peer review process provides thoughtful comments to help them improve their manuscript. Peer review is important in scientific publishing, but also in reviewing project proposals or, sometimes, conference abstracts. '"`UNIQ--references-000000FE-QINU`"'
Poor mentoring or supervision of early career researcherers	Misconduct & Misbehaviors	Both the mentors and the mentees need to be aware of what is expected in their collaboration and professional relationship. Research performing institutions should ensure that they devote more attention to training of both the mentees and mentors about what mentoring means and how to build it for successful outcome of research mentoring.
Preprint servers	Other	Because of the lengthy duration of peer review process and subsequent delay in publication, preprint servers are useful tools for researchers to post full draft of their research papers and immediately get the feedback from their colleagues.'"`UNIQ--ref-000005E3-QINU`"' The articles can be posted at no charge'"`UNIQ--ref-000005E4-QINU`"' and authors have the possibility to submit revised versions to the server at any time.'"`UNIQ--ref-000005E5-QINU`"' Most of the articles are given a digital object identifier (DOI) so they can be cited.'"`UNIQ--ref-000005E6-QINU`""`UNIQ--ref-000005E7-QINU`"' Readers can also upload their comments, which can result in productive discussions.'"`UNIQ--ref-000005E8-QINU`"' This way of sharing research results and communication among researchers has its pros and cons.'"`UNIQ--ref-000005E9-QINU`"' The most obvious benefit would be higher speed of publication, from 7 days to 2-4 mouths'"`UNIQ--ref-000005EA-QINU`"' and evidence of authors’ productivity and accomplishment.'"`UNIQ--ref-000005EB-QINU`"' This would justify financial funds, especially in those disciplines with strong competition for development and limited funding.'"`UNIQ--ref-000005EC-QINU`"' The use of preprint servers would also foster open science, increase visibility and lead to fast feedback and recommendations for improvement in quality.'"`UNIQ--ref-000005ED-QINU`"' Furthermore, it could result in some new collaborations.'"`UNIQ--ref-000005EE-QINU`"' On the other hand, researchers need to consider that not all journals will accept manuscripts that have been submitted to a preprint server.'"`UNIQ--ref-000005EF-QINU`"' Researchers also might “rush out data prematurely” in order to get credit for their work, which could result in posting low quality and irreproducible data.'"`UNIQ--ref-000005F0-QINU`"'   '"`UNIQ--references-000005F1-QINU`"'
Protecting research subjects	Good Practices	In relation to human research, The Belmont report lays down three basic ethical principles which are aimed at protecting research subjects. '"`UNIQ--ref-000004E7-QINU`"'The three ethical principles are: Respect for persons includes acknowledging the autonomy of individuals and protecting those with diminished autonomy. The principle respect for persons is protected in the form of informed consent. Beneficence is understood as minimizing harm and maximizing possible benefits. Systematically assessing the risks and benefits of a research project is needed to ensure the harms are minimized and the benefits of the study are maximized. Justice concerns who receives the benefits of a research study and who carries the cost. Fair procedures to select subjects is one important way to ensure justice in a study. For animal research, guiding principles are to replace, reduce, and refine their use in research - referred to as 3R principles.'"`UNIQ--ref-000004E8-QINU`""`UNIQ--ref-000004E9-QINU`""`UNIQ--references-000004EA-QINU`"'
Publication	Good Practices	Although it is nearly impossible to define 'good academic publishing', scientific gatekeeping must always be pursued'"`UNIQ--ref-0000049E-QINU`"'. '"`UNIQ--references-0000049F-QINU`"'
Qualitative research	Other	Qualitative studies increasingly form the foundation for quantitative research, intervention studies by generating hypotheses as well as further investigating and understanding quantitative data (1). Those researches answer the hows and whys instead of how many or how much thus exploring and providing deeper insights into real-world problems by gathering participants' experiences, perceptions, and behavior. While qualitative and quantitative approaches are different, they are not necessarily opposites, and the results can be complementary.
Questionable Research Practices in Analysis and Reporting	Misconduct & Misbehaviors	Integrity in analysis and reporting of results is important to fully understand your data. Misbehaviors related to analysis and reporting include: Report on data driven hypotheses without disclosure [‘HARKing’ ‐ Hypothesizing After Results are Known ‐ typically with a view to make results appear more spectacular (‘Chrysalis effect’)]    Delete data before performing data analysis without disclosure    Selectively delete data, modify data or add fabricated data after performing initial data‐analyses  [in other words: falsification or fabrication of data]    Perform data‐analyses not stated in the study protocol without disclosure  [or in predefined data‐analysis plan – also called ‘Significance chasing’, ‘P-hacking’, ‘data dredging’,  ‘fishing expedition’ or explorative subgroup analyses]    Report an incorrect downwardly rounded p‐value [e.g. by reporting a p value of .054 as being less than .05]    Not report all study protocol‐stipulated results  [in the aggregate of all published reports on the study at issue]    Not publish a valid ‘negative’ study  [in a form that is publicly available or accessible behind a paywall (article, report, website etc.)]    Report an unexpected finding as having been hypothesized from the start    Conceal results that contradict your earlier findings or convictions    Not report clearly relevant details of study methods   Not report replication problems    Selectively cite to enhance your own findings or convictions    Selectively cite to please editors, reviewers or colleagues    Selectively cite or cite your own work to improve citation metrics  [e.g. Impact Factor, H‐index]    Let your convictions influence the conclusions substantially    Insufficiently report study flaws and limitations    Spread study results over more papers than needed [‘salami slicing’]    Duplicate publication without disclosure    Re‐use of previously published data without disclosure [which may lead to double counting in meta‐analyses]    Modify the results or conclusions of a study due to pressure of a sponsor  [commercial or not‐for‐profit funder of the study]    Failure to disclose a sponsor of the study    Failure to disclose a relevant financial or intellectual conflict of interest  [in publications, when reviewing grant proposals, or evaluating persons or institutions]   Handle existing conflicts of interest inadequately    Communicate results to the general public before a peer reviewed publication is available   Deliberately communicate findings inaccurately in the media or during presentations    Make no clear distinction between personal views and professional comments (List from Bouter et al 2016'"`UNIQ--ref-00000587-QINU`"') '"`UNIQ--references-00000588-QINU`"'
Questionable Research Practices in Collaboration	Misconduct & Misbehaviors	Good collaboration is not just about building networks and beneficial relationships, it also entails taking responsibility for research conduct, treating colleagues and collaborators with respect, and giving collaborators full credit for their work. Misbehaviors related to collaborations identifiedby research integrity experts include: Take no full responsibility for the integrity of the research project and its reports Refuse to share data with bona fide colleagues Turn a blind eye to putative breaches of research integrity by others Refuse to respond to an allegation of a breach of research integrity Use unpublished ideas or phrases of others without their permission [e.g. from reviewing manuscripts or grant applications, or from conference presentations ‐ this is one of the forms plagiarism can take]    Use published ideas or phrases of others without referencing [this is one of the forms plagiarism can take]   Re‐use parts of your own publications without referencing [‘self‐plagiarism’] Unfairly review papers, grant applications or colleagues applying for promotion Review your own papers Demand, accept or offer substantial gifts for doing a favor [e.g. authorship, promotion, access to data, favorable review or recommendation] Insufficiently supervise or mentor junior coworkers Be grossly unfair to your collaborators [e.g. in terms of a just balance of benefits and burdens, including giving those who deserve the opportunity to qualify as author] Add an author who doesn’t qualify for authorship [‘honorary or gift authorship’] Demand or accept an authorship for which you don’t qualify [‘honorary or gift authorship’] Omit a contributor who deserves authorship [‘ghost authorship’] Not acknowledge contributors who do not qualify for authorship Not ask permission from contributors for the wording of the acknowledgement Not share reviewers’ comments with all co‐authors Submit or resubmit a paper or grant application without consent from all authors
Questionable Research Practices in Data Collection	Misconduct & Misbehaviors	The importance of the data collection phase cannot be overemphasized. For research results to be trustworthy, the underlying data needs to be of a high quality. ‘Misbehaviors’ related to data collection identified by research integrity experts'"`UNIQ--ref-00000581-QINU`"' include: Collect more data after noticing that the results are almost statistically significant  [unless specified in a predefined adequate plan for interim analysis –  also called ‘peeking’]    Fabricate data* Stop data collection earlier than planned because the results are already statistically significant  [unless predefined stopping rules are implemented appropriately ‐ also called ‘peeking’] Not adhere to pertinent laws and regulations  [including the laws and regulations for human and animal studies, safety regulations, good clinical  practice, good laboratory practice etc.]    Inadequately handle or store data or (bio)materials  [including archiving for an appropriate period]    Keep inadequate notes of the research process  [with (digital) lab journals or its equivalent in other types of research]    Ignore basic principles of quality assurance (From Bouter et al 2016'"`UNIQ--ref-00000582-QINU`"'). '"`UNIQ--nowiki-00000583-QINU`"'Included in a separate misconduct section in The Embassy categorisation.'"`UNIQ--references-00000584-QINU`"'
Questionable Research Practices in Study Design	Misconduct & Misbehaviors	An appropriate, transparent, and meticulous study design is the foundation on which to build trustworthy, high quality research. Questionable practices related to study design include: 1.      Propose study questions which are clearly irrelevant [including questions that have already been or could be answered adequately by a systematic review of the literature]    2.      Choose a clearly inadequate research design or using evidently unsuitable measurement instrument [which will not lead to a valid, reproducible and efficient answer to the main study question, taking  into account the state‐of‐the‐art in the field at issue]   3.      Present grossly misleading information in a grant application 4.      Write no or a clearly inadequate research protocol  [in which essential details are lacking]    5.      Ignore substantial safety risks of the study to participants, workers or environment   6.      Ignore substantial risks of the expected findings for society or environment    7.      Importantly change the research design during the study without disclosure  [or – if applicable‐ without permission of sponsor, Institutional Review Board or Institutional Animal Care and Use Committee]    8.      Give insufficient attention to the equipment, skills or expertise which are essential to perform the study                            (From Bouter et al 2016'"`UNIQ--ref-0000001E-QINU`"'). '"`UNIQ--references-0000001F-QINU`"'
Replicability	Good Practices	Replication is of great importance to science, because science aims to discover laws of nature. Since such laws are permanent, experiments on which they are based should be infinitely replicable'"`UNIQ--ref-00000394-QINU`"'. This concept is highly important to medicine. Being able to replicate, for example, an epidemiologic study to determine health effects of certain risk factors could build up existing scientific evidence and impact decision making that might affect the public health'"`UNIQ--ref-00000395-QINU`"'. Replicability also represents a direct public interest since science is significantly funded by public resources. If a study cannot be replicated, the money invested in it is wasted. It is estimated that annual costs of non-replicable preclinical research are approximately US$28 billion'"`UNIQ--ref-00000396-QINU`"'. Replication can be divided into direct and conceptual'"`UNIQ--ref-00000397-QINU`"'. Direct replication is an exact replication of an experiment and it ensures that the phenomenon is reproducible; however, it does not guarantee that the theory behind the phenomenon is true. Therefore, confirming the same results with a different methodology or a different experimental system adds more credibility to the proposed theory or model'"`UNIQ--ref-00000398-QINU`"'. Nevertheless, we cannot expect that every experiment can be replicated down to the last detail, especially in psychology and medicine. We can always expect to see random deviation in the results and conclusions when conducting an independent experiment'"`UNIQ--ref-00000399-QINU`"'. '"`UNIQ--references-0000039A-QINU`"'
Replicability in the Humanities	Principles & Aspirations	Some scholars argue that replicability is possible at least in the fields of humanities which are empirical, such as history, archeology, linguistics, literature, art and theology. In other words, they are based on “the collection of data”.'"`UNIQ--ref-000005B7-QINU`"' One of the most common arguments that refute this idea is that study objects in the humanities are usually “unique phenomena”, for example certain historical events.'"`UNIQ--ref-000005B8-QINU`"' Therefore, it is not clear how a study should be replicated. Scholars advocating for replicability in the humanities provide a counterargument: although subjects studied in the humanities are unique, they still have “multiple instances”. For example, French Revolution was as a unique event, however, a researcher can study it several times and each time generate new data (in artifacts, literary accounts and paintings) which enables repetition of a particular method (studying a text) and discovering new things about that unique event.'"`UNIQ--ref-000005B9-QINU`"' Majority of scholars who refute the idea of replication in the humanities maintain that replication might be possible in some, but it is not possible in all fields of humanities. because the main reason for this is that the research issues and questions often rely on interpretation.'"`UNIQ--ref-000005BA-QINU`"' Further intra-disciplinary and interdisciplinary debates regarding this topic should be encouraged. '"`UNIQ--references-000005BB-QINU`"'
Research culture	Good Practices	Research communities can be the science system as a whole, institutions or research labs. In these places a different reseach cultures might reign. Nontheless, research culture has an impact on the science system as a whole. The impact encompasses research integrity, diversity and inclusion, career paths, collaborations, the reward system, communication and more. Creating and maintaining a good research culture is invaluable for good science.
Research metrics	Good Practices	Research metrics are used to evaluate the popularity, impact and importance of individual scientists, articles and journals, as well as the performance of employees and projects. The logic behind such an approach is that cited items are perceived to have a bigger impact on science and are, therefore, of greater value. Consequently, research metrics can be employed as a basis of staff promotion and funding distribution. Bibliometrics are also used in research, when analyzing relationships between researchers, and when assessing the impact of research projects and grants.
Research misconduct	Misconduct & Misbehaviors	The proper conduct and reporting of research is fundamental to the scientific method and the integrity of the research record. Research misconduct however distorts the knowledge base. The practices of falsification, fabrication and plagiarism are widely agreed to constitute misconduct and are intentional deceptions. The Office of Research Integrity defines research misconduct as follows: Research misconduct is ‘fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results.' Fabrication is making up data or results and recording or reporting them. Falsification is manipulating research materials, equipment, or processes, or changing or omitting data or results such that the research is not accurately represented in the research record. Plagiarism is the appropriation of another person's ideas, processes, results, or words without giving appropriate credit. Research misconduct does not include honest error or differences of opinion.’ Falsification, fabrication and plagiarism, however, are relatively rare '"`UNIQ--ref-00000007-QINU`"' '"`UNIQ--ref-00000008-QINU`"'. In contrast, other behaviors, ranging from unintentional ‘sloppy' science to conscious minor breaches of research integrity are more frequent and possibly more damaging to science. '"`UNIQ--ref-00000009-QINU`"' '"`UNIQ--ref-0000000A-QINU`""`UNIQ--references-0000000B-QINU`"'
Responsible mentoring	Good Practices	Mentoring is important as it has traditionally been a successful way for research development of individuals, as well as research institutions and systems. Although mentoring is an old concept (Mentor and Telemachus in The Odyssey), it is a difficult concept. It is should not be confused with other types of professional research relationship, such as teaching, tutoring, coaching, advising, counselling, supervising, sponsoring, role-modelling, preceptoring, peer support.'"`UNIQ--ref-00000549-QINU`"' Mentoring is a complex phenomenon,'"`UNIQ--ref-0000054A-QINU`"' which integrates different functions, as mentors help their mentees to acquire, synthesize and integrate new knowledge and skills, as well as develop professionally and personally. It is an intense, personal as well as professional relationship with high commitment over a long period of time. It is reciprocal but asymmetrical, as the primary goal is the professional growth and development of a mentee. We do not have solid evidence that mentorship work. A systematic review of mentoring in academic medicine'"`UNIQ--ref-0000054B-QINU`"' showed that it is perceived as very important bur there is little evidence that it is actually successful. This is similar for many other disciplines and types of mentoring.'"`UNIQ--ref-0000054C-QINU`"' There are different ethical issues in mentoring, related to the individuals involved in the mentoring relationship but also related to the hosting organization.'"`UNIQ--ref-0000054D-QINU`"' Issues for mentees include lack of motivation and poor collaboration, and laps in professionalism, failure to acknowledge mentee’s contribution, lack of commitment and collaboration. Ethics burdens to a mentoring relationship may be the power imbalance, misalignment of goals, poor communication, competition, gender or cultural bias, and personality conflicts. Organizations where mentorship happen are also responsible for ethics problems generated by mentoring: they may not have adequate recruitment procedures, oversight, assessment and recognition of good mentorship, lack of clear guidelines, and lack of administrative support, such as protected time for mentoring. '"`UNIQ--references-0000054E-QINU`"'
The decision on ice	Other	When it is decided that no further fertility treatments will be pursued, couples are facing the challenging decision regarding the disposition of their frozen embryos, also known as “embryo disposal decision” (EDD) '"`UNIQ--ref-00000967-QINU`"'. Essentially, at the end of the storage period, which varies amongst different countries and institutions, couples have 4 outcomes to choose from: to continue storage by paying an additional cost, to discard, or to donate embryos to research or to another couple. There is also the complex matter of “abandoned embryos” that refers to the cases where the couple cannot be reached and/or fails to provide the clinic with a decision pertaining to the embryos’ fate'"`UNIQ--ref-00000968-QINU`"', so the embryologists become their custodians and guardians, which raises ethical questions, as well as bureaucratic challenges. To avoid such complications, some have advocated the use of a “properly prepared legal document, i.e., a pre-freeze agreement,”'"`UNIQ--ref-00000969-QINU`"'. There are numerous studies describing patients’ views on the disposal procedure of their excess embryos. Some couples perceive them as barely, more than a group of cells, or a tissue, while others consider them as their unborn children'"`UNIQ--ref-0000096A-QINU`""`UNIQ--ref-0000096B-QINU`""`UNIQ--ref-0000096C-QINU`""`UNIQ--ref-0000096D-QINU`"'. In a model of patients’ decision-making processes for the fate of frozen embryos, developed by Takahashi et al.'"`UNIQ--ref-0000096E-QINU`"', this burden was expressed as “Mottainai,” a prevalent, culturally embedded moral standard in Japan. “Mottai” is a Buddhist term that refers to the intrinsic dignity or sacredness of a material entity. “Nai” is negation'"`UNIQ--ref-0000096F-QINU`"'. Therefore, “Mottainai” is an expression of sadness and guilt over the disrespectful and wasteful treatment of valuable entities'"`UNIQ--ref-00000970-QINU`"'.
Values and norms	Principles & Aspirations	In codes of conduct for scientific research, the concepts of values and norms are often used interchangeably. Yet, it is crucial to distinguish between the two concepts '"`UNIQ--ref-0000003B-QINU`""`UNIQ--ref-0000003C-QINU`"'. Values are general ideals. They underlie norms, which are action-guiding rules. There are three kinds of such rules: permissions, orders or commands and prohibitions. Values show what persons and communities hold as important. Norms say what has to be done in order to realize values. Without a reference to underlying values, rules lack motivation and justification. Without corresponding norms, values lack specification and concrete direction. Values and norms can be formal (that is: explicitly formulated) or informal (that is: implicitly assumed). Often, when values are discussed, corresponding norms are not explicitly mentioned. On the other hand, when norms are posed, the underlying values often remain implicit. Yet it is important to be aware of the concrete action-guiding rules envisaged when a certain value is mentioned, and of the general ideal behind a specific norm. An important aim of moral reflection is to provide such clarifications. '"`UNIQ--references-0000003D-QINU`"'
Virtues in research integrity	Principles & Aspirations	Research integrity is not only about following rules. It also requires personal engagement and competence. These requirements show that research integrity requires virtues. A person who is virtuous, not merely follows methodological or moral rules, but embodies goodness or excellence . '"`UNIQ--ref-00000042-QINU`"' Goodness or excellence in research depends on what we do, as well as on who we are, intellectually and morally. The possession of a virtue says something about this person as a person. So, to tell of a person that she is imaginative or honest, is to say something about this person’s character. Aristotle described virtue as ‘the state of character which makes a man good and which makes him do his work well.’ '"`UNIQ--ref-00000043-QINU`"' MacIntyre defined virtue as ‘an acquired human quality the possession and the exercise of which tends to enable us to achieve those goods which are internal to practices and the lack of which effectively prevents us from achieving any such goods’. '"`UNIQ--ref-00000044-QINU`"' MacIntyre, therefore, emphasized the importance of practice for the expression and development of virtues. Aristotle distinguishes between two kinds of virtues, intellectual and moral virtues. Examples of the first kind of virtues are critical thinking, curiosity, imaginativeness, perseverance and open-mindedness. Examples of moral virtues are courage, honesty, generosity, fair-mindedness, and justice. Although intellectual and moral virtues are distinct, they have in common that they are both character traits. A number of attempts have been made to identify which virtues are essential for good scientific practice . '"`UNIQ--ref-00000045-QINU`"' '"`UNIQ--ref-00000046-QINU`"' These include: honesty;curiosity;attentiveness or observance;perseverance or patience; objectivity; humility to evidence; skepticism; meticulousness; courage; collaboration; resoluteness; accountability; availability; competency; reliability; sincerity; creativity; accountability; punctuality; truthfulness; selflessness; reflexivity; clarity of purpose; collaborative spirit; fairness; loyalty; moderation; positivity/open-mindedness; respectfulness. According to Aristotle, a virtuous person has the disposition to act in accordance with the right middle. A virtuous person is able to see and do what is right in the specific situation, and knows how to avoid the extremes of showing too little or too much. An example of a virtue is courage. Someone who is brave knows how to find the right middle between the extremes of cowardice on the one hand and recklessness on the other. That applies not only to war, to the Greeks an important example of human action. It also applies to interacting with people with whom one collaborates. For example, if the person makes a mistake, it may be important to tell her ' the truth '. That requires courage, as the right middle between making an allusion in the hope that the other understands the message, and confronting the other in public with the fact that she does something wrong. What is the right middle depends on the situation, that is, the seriousness of the error, the openness of the other for the message, and the ability of the person who performs the act. In some cases the right middle is closer to being cautious;in other cases more emphasis is needed. Being virtuous means living in accordance with one’s natural potential. Thus, virtues refer to human nature. Yet, developing virtues requires training and exercise in practice. In practice, one learns to see what is the importance of, for example, honesty as openness to criticism, and how it can be adequately shaped. How much attention should you devote to literature before you do a study? When does that literature help sharpen the mind, and when does it lead to confusion? Of course it is important to study existing investigations before one starts to research, for example by doing a systematic review. But how to ensure that this really gives an insight into what was previously found, and provides a connecting factor for further research? The same applies to the discussion of possible explanations for results of own research. What literature do you refer to, and how do you use it to sharpen the findings? Do the quoted articles really help them to better understand the outcomes of the study, draw conclusions and formulate new questions? The answer to such questions does not come from textbooks, but requires insights and skills that are already acquired in practice. '"`UNIQ--references-00000047-QINU`"'
Collaboration In Research	Good Practices	Scientific research is often done in a team, hence, one must be prepared to collaborate with others. Every researcher must know their role and what is expected of them before they begin their research, in order to avoid conflict. Having a list of principles that every scientist must follow throughout their research ensures that there won’t be any clashes or misunderstandings in the resulting works. All research components should be in sync and make sense when merged together in the final results.
Cross-boundary collaborations	Good Practices	Cross-boundary collaborations provide opportunities but also difficulties. It is important to be aware of differences in research practice, guidelines and legislation. Collaborators should try to reach consensus and agreement in the design and implementation of research.
High income and low- and middle-income country collaborations	Good Practices	Collaborations between high-income countries (HICs) and low- and middle-income countries (LMICs) can be mutually beneficial endeavors. Researchers from HIC might benefit from local expertise and experience and gain access to unique resources, environments and participants. Researchers from LMICs potentially benefit from access to funding, international networks and opportunities for local capacity building. Collaborations can also, unfortunately, lead to negative experiences, ranging from different standards in data management and ethics applications to a lack of participation in research agenda setting and even coercive recruitment practices or exploitation of people/samples/resources.
Conflict of interest in peer review	Misconduct & Misbehaviors	Peer review process is vital to science, as it provides quality assurance before publication of new knowledge. Any situation which can compromise peer review process by influencing decision making should hence be reported, and prevented.'"`UNIQ--ref-0000023D-QINU`"' '"`UNIQ--references-0000023E-QINU`"'
Conflict of interest: a research integrity and research ethics perspective	Misconduct & Misbehaviors	COI is a core concept in research integrity. It can even be argued that most research integrity issues are in some way related to underlying COIs, especially if integrity is understood to refer to doing what is right even if confronted by countervailing incentives.[2] Authorship conflicts, for example, often occur because researchers have a strong secondary interest to be listed as authors on as many papers as possible to advance their career, even if they have not contributed to a paper (or if their contribution does not constitute authorship). Usually, discussions on COIs in the research integrity literature focus on the narrower aspect of how COIs can bias research results and thus decrease the reliability of research results, however. In line with most of the relevant literature, this theme page adopts a narrow perspective on COIs. In addition to their potential effects on research integrity, COIs have an important research ethics dimension as well, especially in biomedical research.[3] An example is the specific role of medical doctors in clinical research: According to the International Code of Medical Ethics, they are obliged to “be dedicated to providing competent medical service in full professional and moral independence, with compassion and respect for human dignity”.[4] However, if they act as researchers in clinical research, they are confronted with two potentially conflicting interests: a duty to care (primary duty) and the responsibility to generate new knowledge (which in this case is a secondary interest that can under certain circumstances conflict with the duty to care).[5]   Therefore, it is crucial to understand what COIs are, how they affect research integrity and research ethics, and what the research community as well as individual researchers can do to minimize their potential detrimental effects.
Editorial conflicts of interest	Misconduct & Misbehaviors	Editors play a special role in science, as they ultimately determine what gets published in their journals. We often say that editors are gate-keepers of science, because of their control over journal policies.'"`UNIQ--ref-00000316-QINU`"' Publishing new discoveries is important in science, and following established methods of control such as the peer-review process is necessary. Sometimes, having an undisclosed interest could influence editorial decisions or hinder the proper review of manuscripts. This could lead to a loss of confidence in science, which can be particularly harmful when science is publicly funded.'"`UNIQ--ref-00000317-QINU`"' '"`UNIQ--references-00000318-QINU`"'
Intellectual conflicts of interest	Misconduct & Misbehaviors	There is concern that intellectual conflicts of interest may cause bias in research. The idea is that if researchers prefer one intervention over another, they will intentionally or unintentionally introduce bias into the design of the study, data analysis or data interpretation so that the results are in favor of the preferred intervention.  However, there is not enough evidence on this. In psychotherapy research, it has been shown that researcher allegiance (i.e. intellectual conflicts of interest) is associated with study results: therapies with higher allegiance are shown to be more effective in randomized clinical trials.'"`UNIQ--ref-0000035E-QINU`""`UNIQ--ref-0000035F-QINU`""`UNIQ--ref-00000360-QINU`"' It is not clear, though, whether this correlation is causal. It could be that researchers have allegiance towards more effective interventions because they are effective, rather than that the interventions appear to be more effective because the researchers have an allegiance to them.'"`UNIQ--ref-00000361-QINU`"' Although some argue that the association between researcher allegiance and study results might be causal since the association exists even when there is evidence that two interventions are equally effective, the evidence remains inconclusive on how researcher allegiance/ intellectual conflicts of interest might affect study results.'"`UNIQ--ref-00000362-QINU`"' At the same time, some argue that intellectual conflicts of interest are unavoidable.'"`UNIQ--ref-00000363-QINU`"' Researchers will have a certain educational background, prior research experience, and personal and professional affiliations, which will naturally make them more likely to favor one research outcome over another.'"`UNIQ--ref-00000364-QINU`"' Not only is this unavoidable, but it is what drives science forward: researchers would not spend years researching a topic that they did not feel passionate about. It is precisely the passion and intellectual interest that researchers have that inspires them to delve into research. What conclusions can we make? If intellectual conflicts of interest lead researchers to introduce systematic biases into their research (e.g. selection bias, reporting bias, etc.), then they can be said to be problematic.'"`UNIQ--ref-00000365-QINU`"' More evidence is needed to establish whether this is the case. However, if intellectual conflicts of interest do not lead to systematic bias, it is hard to argue that they are problematic even if they do affect study results.'"`UNIQ--ref-00000366-QINU`"' For example, if researchers that prefer intervention A are more likely to have results that favor intervention A even in the absence of systematic bias, it could be that: 1)     they are better trained in intervention A than other researchers, or 2)     they know more about intervention A than other researchers , or 3)     they carry out intervention A more diligently than other researchers. It would be difficult to argue that possibilities 1, 2 or 3 are problematic. Innovation in science is driven by passionate researchers who develop and propose new hypotheses, which they often strongly believe in. It makes sense that if these passionate researchers who know more about the hypotheses than others are not able to show their truthfulness, then no one else will be able to, indicating that the hypotheses are not correct. Yet, if the innovative researchers are able to provide evidence on the truthfulness of the hypotheses, the hypotheses remain open to a closer scrutiny by the rest of the scientific community.'"`UNIQ--ref-00000367-QINU`"' Since science is a self-correcting process, it may not matter if the researcher with the intellectual conflict of interest is more likely to obtain study results in line with their allegiances. Other researchers with different allegiances will be able to scrutinize and test the results, thereby correcting for the intellectual conflict of interest. '"`UNIQ--references-00000368-QINU`"'
The influence of pharmaceutical company on drug availability	Misconduct & Misbehaviors	Delayed drug availability may affect research results.
Anonymisation and pseudonymisation	Good Practices	Data protection is defined as a fundamental human right and using personal data raises significant ethics issues '"`UNIQ--ref-000004CF-QINU`"'. Pseudonymisation and anonymisation are methods used to protect one's privacy and minimize the risk in the event of unauthorized access. Pseudonymised data are considered personal data and therefore are in the scope of GDPR, unlike irreversibly anonymised data which are no longer defined as personal data and are outside of the scope of GDPR '"`UNIQ--ref-000004D0-QINU`"' '"`UNIQ--references-000004D1-QINU`"'
Data management plans	Good Practices	Since research funders, organisations, reviewers, and individual researchers all have different needs from data management , DPMs are becoming integral parts of grant applications and research organisations.'"`UNIQ--ref-000006C9-QINU`"' They are usually short, and state which data will be created and how. DMPs also define the plans for data sharing and presentation,'"`UNIQ--ref-000006CA-QINU`"' prescribe how the data will be stored, who will have access to it, what documentation and metadata will be created with it, and how it will be preserved.'"`UNIQ--ref-000006CB-QINU`"' Creating DMPs provides several benefits for researchers, such as reducing the loss of data, monitoring the research progress, and preparing data for future use. Apart from that, they are also time saving.'"`UNIQ--ref-000006CC-QINU`"' '"`UNIQ--references-000006CD-QINU`"'
FAIR principles: sharing data for maximisation of results	Good Practices	While conducting our research we (as researchers) produce different kind of data: we write research designs and workflows, we collect raw data, we analyse them, we write about them. However, most of the time the only part of our research which is publicly shared is represented by the articles which we produce as a result of the entire research cycle. In fact, all phases of research could be of potential interest for other researchers, who could reuse the data we produce in a different way. By maximizing access to and re-use of research data we can optimize the impact of the data that we produce. In line with the principles of Open Science, good data management becomes a fundamental instrument to promote and facilitate the reusability, accessibility and exploitation of research data, thereby allowing for the generation of new knowledge.'"`UNIQ--ref-0000013B-QINU`"' In 2014, a workshop named ‘Jointly Designing a data FAIRPORT’ was organized in Leiden by a group of academic and private sector stakeholders. The aim of the workshop was to improve the infrastructure supporting humans and machines in the discovery and analysis of scientific data and their associated algorithms and workflows. A set of guidelines was developed by the participants to support data producers, scientists and data publishers to take full advantage of the generation of data.'"`UNIQ--ref-0000013C-QINU`"' Four foundational principles were agreed by the community to allow stakeholders to discover, integrate, re-use and adequately cite the massive quantities of information being generated by contemporary data intensive science. These foundational principles were subsequently improved, detailed and elaborated on by the FORCE 11 working group, which is still engaged in fostering the implementation and continued update of the FAIR principles. These foundational principles are known as FAIR principles, see below for specification of the principles. '"`UNIQ--ref-0000013D-QINU`"' FAIR principles Findable: (Meta)data are assigned a globally unique and eternally persistent identifier. Data are described with rich metadata. (meta)data are registered or indexed in a searchable resource. Metadata specify the data identifier. Accessible (meta)data are retrievable by their identifier using a standardized communications protocol. the protocol is open, free, and universally implementable. the protocol allows for an authentication and authorization procedure, where necessary. metadata are accessible, even when the data are no longer available. Interoperable (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. (meta)data use vocabularies that follow FAIR principles. (meta)data include qualified references to other (meta)data. Re-usable meta(data) have a plurality of accurate and relevant attributes. (meta)data are released with a clear and accessible data usage license. (meta)data are associated with their provenance. (meta)data meet domain-relevant community standards. All researchers at all levels but also society as a whole can benefit from the implementation of FAIR data management. Granting access to data produced throughout the entire research cycle is also important on a global scale since it allows researchers who operate in countries with less developed research infrastructures to benefit from others scientists’ work.'"`UNIQ--ref-0000013E-QINU`"' '"`UNIQ--references-0000013F-QINU`"'
Feedback of findings in genome-wide association studies	Good Practices	The first sequencing of the whole human genome in 2003 cost roughly $2.7 billion. Advances in whole genome scanning technologies have enabled commercial companies to make genomic information available to the end consumer at competitive prices. Consumers can now have access to commercial genotyping of their genome from direct-to-consumer testing companies. According to NHGRI-funded genome-sequencing groups, the cost to generate a high-quality 'draft' whole human genome sequence in mid-2015 was just above $4,000; by late in 2015, that figure had fallen below $1,500. This changing of landscape and technologies in which GWAS takes place is likely to affect the problem of reporting of findings. Is it possible that the participants in GWAS will expect a feedback similar to the information provided by consumer genetics companies?
How to select trustworthy repositories	Good Practices	After deciding what research data to keep for long-term preservation, researchers should select the right repository. There is a variety of repositories – those that are focused on a specific research area and those for general purpose.'"`UNIQ--ref-0000091B-QINU`"' Funders, journals, and universities also have their own repositories.'"`UNIQ--ref-0000091C-QINU`""`UNIQ--ref-0000091D-QINU`"' Since there are more than 2,000 data repositories,'"`UNIQ--ref-0000091E-QINU`"' researchers should use certain principles and standards in their selection process. They should: -check whether there are any funder requirements that may mandate which repository to use -check with the journal they are submitting their paper to, because some journals keep a list of approved repositories they will accept or have specific policies on data archiving -check for discipline specific repositories because they could be more suitable to their datasets and other researchers expect to find them there -or deposit their data into a University repository.'"`UNIQ--ref-0000091F-QINU`"' '"`UNIQ--references-00000920-QINU`"'
Imputation of missing data in clinical trials	Good Practices	Missing data are unavoidable in clinical trials. Frequently, complete cases analysis is used only including individuals with no missing data '"`UNIQ--ref-00000568-QINU`"'. However, that can generate bias and can lead to exclude several individuals, causing loss of precision and power '"`UNIQ--ref-00000569-QINU`"'. The risk of bias from missing data depends on the cause '"`UNIQ--ref-0000056A-QINU`"': Missing completely at random: There are no systematic differences between the missing values and the observed values. Missing at random: Any systematic difference between the missing values and the observed values can be explained by differences in observed data. Missing not at random: Systematic differences remain between the missing values and the observed values. The determination of the type of missing values is difficult due to the nature of missing values '"`UNIQ--ref-0000056B-QINU`"'. Therefore, practical guidelines are needed to deal with missing data.
Methods to increase data availability	Good Practices	Data access is extremely important for transparent modern science. The rising number of research studies impedes the filtering of research findings, aggravates peer-review process and increases the possibility of false study reports. Having in mind the direct implications of scientific findings on everyday practice, data availability is further prioritized. The open data movement follows the principles of transparency, participation, and collaboration (1). Open data policy is important because it nurtures the virtues of transparency and honesty, which allows each respondent to check the authenticity of the published results at any time. Data sharing represents a significant part of research ethics and nowadays, many journals require researchers to publish resources to make them available to other investigators (2,3). However, deposited published data may be incomplete, in some cases intentionally because authors could feel like losing priority in future publishing, which may complicate new analyses on previously published data (2). In an effort to enhance data-sharing practices, some journals have mandatory data availability statement (DAS). However, according to a recent study on data availability statements, 93% of authors of manuscripts with DASs that stated authors are eager to share their data either didn't respond or refused to share their data. In conclusion, the level of compliance is disappointing even when the authors state in their article that they will share data upon request, indicating that the DAS may not be enough to guarantee data sharing (4).
Sharing and preserving data in repositories	Good Practices	Not storing data properly and disregarding safeguards can lead to losing important research data. This does not occur rarely. A study carried out on 516 articles published from 1991 to 2011 has revealed that availability of research data in biology decreases about 17% per year.'"`UNIQ--ref-00000006-QINU`"' Various reasons can lead to unavailability of research data, whether researchers change their contact information and are not reachable anymore or they use outdated technology, such as floppy disks, to store their data.'"`UNIQ--ref-00000007-QINU`"' Apart from that, even when researchers are able to access their data, they often lose hours and hours searching for them in their computer files.'"`UNIQ--ref-00000008-QINU`"' Therefore, depositing data into repositories can save a considerable amount of time. There are several benefits for researchers who deposit their data into repositories: -data is clustered together which enables easier and faster analysis and reporting -potential problems are detected easier because repositories are categorised -data is preserved and archived.'"`UNIQ--ref-00000009-QINU`"' Overall, such practice promotes transparency in research and reduce misconduct.'"`UNIQ--ref-0000000A-QINU`"' However, data repositories also have some downsides. For example, there is a possibility of a system crash that could affect the stored data, so it is important always to back up datasets.'"`UNIQ--ref-0000000B-QINU`"' '"`UNIQ--references-0000000C-QINU`"'
Paper Mills	Misconduct & Misbehaviors	Paper mills pose significant threats to the integrity and trustworthiness of academic research, and to the scholarly record. The possibility that hundreds, if not thousands, of ‘fake’ papers are published in academic journals seriously compromises the trust that scholars and the public have in published research. Paper mills also contribute to resource waste, as the investigation and retraction of fake papers is a costly and time consuming process for publishers. Moreover, more money could be wasted if fake papers are used to obtain funding for further research, and in the case of clinical research the health of patients may be put at risk.'"`UNIQ--ref-00000037-QINU`"' Paper mills present a growing problem for the scientific community, with one estimate in 2022 suggesting that 2% of paper submissions across all scientific journals are likely to come from paper mills; in some subject areas, this figure is likely to be much higher .'"`UNIQ--ref-00000038-QINU`"' Estimates made using the Paper Mill Alarm indicate that the number of articles bearing a close textual similarity to paper mill products have been steadily rising since 2000.'"`UNIQ--ref-00000039-QINU`"' There is also concern that the proliferation of generative artificial intelligence (AI) tools will exacerbate this problem, by providing paper mills with the ability to generate new papers and avoid detection techniques at greater speed.'"`UNIQ--ref-0000003A-QINU`"' Paper mills can thrive because of the pressure for researchers to publish in order to advance their careers. Publication may be necessary to obtain their doctorate for example, or to be considered eligible for a promotion by their institution. For example, the Beijing municipal health authority had a policy in place as recently as 2021 requiring attending physicians in non-research roles to meet a minimum number of first-author publications in professional journals in order to gain promotion.'"`UNIQ--ref-0000003B-QINU`"' In other cases, researchers may make use of paper mills to boost their chances of obtaining research funding when applying for a grant.'"`UNIQ--ref-0000003C-QINU`"' '"`UNIQ--references-0000003D-QINU`"'
Conflicts of interest in the review of grant proposals	Good Practices	By not declaring COIs, reviewers undermine the transparancy and honesty of the application process. The role of reviewers and the process of reviewing grant applications differs greatly among RFOs. However, many RFOs stipulate the role of reviewers for internal (staff) members, invited external reviewers and appointed committee members. In all instances having a COI when reviewing a grant proposal needs to be declared
Industry funded research	Good Practices	Collaborations are essential to scientific progress, but should not undermine the independence of research. The Wellcome Trust, a UK based funder, does not for example fund any researchers that receive funding from the tobacco industry. They state “There is overwhelming evidence that tobacco damages the health of smokers and non-smoker” .'"`UNIQ--ref-00000301-QINU`"'The goals of industry (maximizing profit) and researchers (furthering knowledge) are often not aligned.'"`UNIQ--ref-00000302-QINU`"' There are a number of examples where the industry clearly interfered with scientific research to promote their own products. Industry stakeholders are known to have sponsered research to supress evidence showing the adverse effects of their products. For example, the tobacco industry funded research to show that second hand smoking was not harmful. '"`UNIQ--ref-00000303-QINU`"' The sugar industry funded research to show the harmful effect of total fat, saturated fat and cholesterol were more harmful than sugar intake for causing coronary heart disease.'"`UNIQ--ref-00000304-QINU`"' These are clear cases of intereference. There are also other ways in which industry sponsors affect research. Many systematic reviews and meta-analyses have shown that industry sponsored research has more favourable outcomes than non-industry sponsored research. This is also called the funding effect. However, some systematic reviews have also shown that there is little or no difference between industry sponsors and study outcomes.'"`UNIQ--ref-00000305-QINU`"' Per discipline and type of research the “funder effect” may differ. '"`UNIQ--references-00000306-QINU`"'
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