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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It shows that important tasks should not be delegated. +
It shows a clear case of self-plagiarism where both the plagiarised and plagiarising manuscripts were published in the same journal. +
This brief matters because it addresses the persistent gap between integrity policies (written rules) and how research is actually conducted. By insisting that integrity be integral to how research is organised, governed, evaluated, and rewarded, it helps reduce hypocrisy, confusion, and perverse incentives. Embedding integrity at institutional and systemic levels makes research more trustworthy, robust, and aligned with public expectations. Moreover, clarifying concepts and procedures reduces ambiguity and legal risk, supporting fair, transparent, and consistent integrity governance across institutions and nations. +
Social research, especially ethnographic, may be less accurate when it comes to predictions of precise methodological steps, possible scenarios encountered and directions of findings. As noted previously, ethnographic research may often be less understood by ethics committees who may carry some degree of ‘biomedical bias’, threatening both the research’s methodology and its direction'"`UNIQ--ref-00000004-QINU`"'.
This is an interesting case for discussion amongst all those working in ethnographic research (i.e., students, supervisors, researchers) or dealing with it (i.e., ethic committee members and administrators). It is also a useful resource for teaching ethnographic research methods.
Finally, the case further reminds us that protecting human research subjects from harm and at the same time promoting their best interests may sometimes become a seemingly contradictory affair.
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In relation to human research, The Belmont report lays down three basic ethical principles which are aimed at protecting research subjects. '"`UNIQ--ref-00000000-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-00000001-QINU`"''"`UNIQ--ref-00000002-QINU`"''"`UNIQ--references-00000003-QINU`"' +
Currently, citizen science is becoming more and more important in different fields of science. For example, in natural sciences, it enables large-scale data collection by involving a vast number of individuals which would be challenging to achieve for traditional research methods within the same timeframe and resources. This training will guide you through the crucial elements of responsible citizen science, including protection of human research participants, plants, animals and ecosystems;rights of citizen scientists;conflicts of interest;quality of research outputs etc. By the end of this training, you will gain a deeper understanding of responsible open science and acquire the following skills and attitudes necessary for responsible practising of citizen science:
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It is important to realise that not only researchers, but also students can falsify data. +
The Institutional Review Board acknowledges that in order for it to come to decisions regarding issues concerning disclosure of identifiable health information, informed consent, principles of beneficence and maleficence, coercion of research subjects and the intrusiveness of surveys, it must be able to discern those activities that are research-based from those that are practice-based.
The case indicates that disclosure of identifiable health information for the purposes of public health practice does not require informed consent. However, in the case of public health research, a waiver of consent is required from an IRB.
The case also demonstrates that, for situations where information would be used for both practice and research, the demands for consent fall either under the research provisions or the public health provisions, as appropriate. +
Although it is nearly impossible to define 'good academic publishing', scientific gatekeeping must always be pursued'"`UNIQ--ref-0000000C-QINU`"'.
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There are several quick messages emerging here. An underlying implicit message is that even with the best intentions in mind, one may be in danger of unwillingly performing ethics misconduct.
Second, when unsure, once can ask for clarification of the best research ethics practices from the relevant institutions (in this case, COPE).
Third, the primary aim of this requested publication of cases is to inform future medical practice, and therefore, and provide an educational resource for trainees and practicing doctors. In answering, COPE provides ideas of ways to deal with this dilemma;several issues are considered in terms of privacy, stakes to be protected and legalities.
Finally, different countries might have different regulations, guidelines and practices for ethics in research, as well as different legal environments and systems when patient safety concerns are involved. +
This policy brief is important because as research and innovation increasingly aim to address grand societal challenges (climate change, health, inclusion), simply doing “science & tech” isn’t enough the “society” part must be present. By bringing citizens in, R&I becomes more relevant, equitable and sustainable. Yet meaningful citizen participation is not straightforward: this brief surfaces the ethical, organizational and procedural barriers so that R&I funders and institutions can better design inclusive processes. Ensuring participation isn’t tokenistic but genuine strengthens trust in research, improves outcomes and aligns innovation with lived realities making this brief valuable for policy-makers, funders and practitioners alike. +
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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. +
Besides explaining the principles of quality enhancements, this guideline also deals with evaluations and reviews at different levels: institutional, discipline-wide and national. It also details the procedures to deal with complaints, investigations and appeals. +
Besides explaining the principles of quality enhancements, this guideline also deals with evaluations and reviews at different levels: institutional, discipline-wide and national. It also details the procedures to deal with complaints, investigations and appeals. +
Currently, citizen science is becoming more and more important in different fields of science. For example, in natural sciences, it enables large-scale data collection by involving a vast number of individuals which would be challenging to achieve for traditional research methods within the same timeframe and resources. This training will guide you through the crucial elements of responsible citizen science, including protection of human research participants, plants, animals and ecosystems;rights of citizen scientists;conflicts of interest;quality of research outputs etc. By the end of this training, you will gain a deeper understanding of responsible open science and acquire the following skills and attitudes necessary for responsible practising of citizen science. +
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-00000002-QINU`"')
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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
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-00000000-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-00000001-QINU`"').
'"`UNIQ--nowiki-00000002-QINU`"'Included in a separate misconduct section in The Embassy categorisation.'"`UNIQ--references-00000003-QINU`"' +
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-00000002-QINU`"').
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It can be difficult for researchers to know what to do if they suspect misconduct but do not have concrete evidence. The extreme hierarchies present in scientific departments and labs can exacerbate the problem for junior researchers. +
