Research misconduct and crime lessons from criminal science on preventing misconduct and promoting integrity

On "intent" in research misconduct

Research misconduct, broadly defined as acts of fabrication, falsification and/or plagiarism, violate the value system of science, cost significant wastage of public resources, and in more extreme cases endanger research participants or members of the society at large. Determination of culpability in research misconduct requires establishment of intent on the part of the respondent or perpetrator. However, "intent" is a state of mind, and its perception is subjective, unequivocal evidence for which would not be as readily established compared to the objective evidence available for the acts themselves. Here, we explore the concept of "intent" in research misconduct, how it is framed in criminological/legal terms, and narrated from a psychological perspective. Based on these, we propose a framework whereby lines of questioning and investigation, as defined by legislative terms and informed by the models and tools of psychology, could help in establishing a preponderance of evidence for culpable intent. Such a framework could be useful in research misconduct adjudications and in delivering sanctions.

Survey study of research integrity officers' perceptions of research practices associated with instances of research misconduct

BACKGROUND

Research on research integrity has tended to focus on frequency of research misconduct and factors that might induce someone to commit research misconduct. A definitive answer to the first question has been elusive, but it remains clear that any research misconduct is too much. Answers to the second question are so diverse, it might be productive to ask a different question: What about how research is done allows research misconduct to occur?

METHODS

With that question in mind, research integrity officers (RIOs) of the 62 members of the American Association of Universities were invited to complete a brief survey about their most recent instance of a finding of research misconduct. Respondents were asked whether one or more good practices of research (e.g., openness and transparency, keeping good research records) were present in their case of research misconduct.

RESULTS

Twenty-four (24) of the respondents (39% response rate) indicated they had dealt with at least one finding of research misconduct and answered the survey questions. Over half of these RIOs reported that their case of research misconduct had occurred in an environment in which at least nine of the ten listed good practices of research were deficient.

CONCLUSIONS

These results are not evidence for a causal effect of poor practices, but it is arguable that committing research misconduct would be more difficult if not impossible in research environments adhering to good practices of research.

Differing perceptions concerning research misconduct between China and Flanders: A qualitative study

In the field of research integrity, there has been increasing interest in the influence of culture on research misconduct. Yet, there is a lack of empirical study on how differently researchers from distinct cultural backgrounds perceive research misconduct. Hence, we used the qualitative approach to investigate and compare perspectives concerning research misconduct between Chinese and Flemish researchers. By means of 45 interviews we explored their perspectives on types, determinants of, and solutions to research misconduct. Our findings show elements of scientific culture shared by both groups, but also clear dissimilarities. The Chinese participants more often mentioned plagiarism and inappropriate authorship as examples of research misconduct, while Flemish respondents brought up fabrication and falsification. Research misconduct was associated with diverse determinants, though the Chinese favored the "bad apple" theory (more intrinsic), while the Flemish pointed to the "publish or perish" pressure and attributed misconduct to situational aspects (rather extrinsic). Accordingly, they proposed diverse strategies to handle this issue, yet education and training were recommended by both groups. This study confirms that research misconduct is the result of many factors intertwining and interacting, and suggests that cultural traits contribute to our perceptions of research misconduct and subsequent bias in that context.

Commentary: Perverse incentives or rotten apples?

Around 2% of the investigators admit to have falsified or fabricated data at least once. Also, 34% report to have been guilty to one or more questionable research practices, such as doing many statistical analyses and to publish only what fits their theoretical framework. Prevention of questionable research practices is very important. Universities should ensure that the training is in order and the research culture is adequate, and they should critically look at perverse incentives, such as a too high publication pressure, but also by ensuring proper guidelines, and by having a fair and transparent procedure for suspected violations of scientific integrity.

Research misconduct and data fraud in clinical trials: prevalence and causal factors

The disclosure of cases of research misconduct in clinical trials, conventionally defined as fabrication, falsification or plagiarism, has been a disturbingly common phenomenon in recent years. Such cases can potentially harm patients enrolled on the trials in question or patients treated based on the results of those trials and can seriously undermine the scientific and public trust in the validity of clinical trial results. Here, I review what is known about the prevalence of research misconduct in general and the contributing or causal factors leading to the misconduct. The evidence on prevalence is unreliable and fraught with definitional problems and with study design issues. Nevertheless, the evidence taken as a whole seems to suggest that cases of the most serious types of misconduct, fabrication and falsification (i.e., data fraud), are relatively rare but that other types of questionable research practices are quite common. There have been many individual, institutional and scientific factors proposed for misconduct but, as is the case with estimates of prevalence, reliable empirical evidence on the strength and relative importance of these factors is lacking. However, it seems clear that the view of misconduct as being simply the result of aberrant or self-delusional personalities likely underestimates the effect of other important factors and inhibits the development of effective prevention strategies.

Data fraud in clinical trials

Highly publicized cases of fabrication or falsification of data in clinical trials have occurred in recent years and it is likely that there are additional undetected or unreported cases. We review the available evidence on the incidence of data fraud in clinical trials, describe several prominent cases, present information on motivation and contributing factors and discuss cost-effective ways of early detection of data fraud as part of routine central statistical monitoring of data quality. Adoption of these clinical trial monitoring procedures can identify potential data fraud not detected by conventional on-site monitoring and can improve overall data quality.

Life after Misconduct: Promoting Rehabilitation while Minimizing Damage

The scientific community has an interest in dealing with misconduct, but also in providing a path to rehabilitation in the aftermath of misconduct. The prospect of rehabilitation could minimize harms by improving reporting of misconduct, rebuilding damaged trust, and providing more insight into the conditions that led to unethical behavior, allowing scientists to work collectively to create conditions in which scientific misconduct is less likely.

Understanding research misconduct: a comparative analysis of 120 cases of professional wrongdoing

We analyzed 40 cases of falsification, fabrication, or plagiarism (FFP), comparing them to other types of wrongdoing in research (n = 40) and medicine (n = 40). Fifty-one variables were coded from an average of 29 news or investigative reports per case. Financial incentives, oversight failures, and seniority correlate significantly with more serious instances of FFP. However, most environmental variables were nearly absent from cases of FFP and none were more strongly present in cases of FFP than in other types of wrongdoing. Qualitative data suggest FFP involves thinking errors, poor coping with research pressures, and inadequate oversight. We offer recommendations for education, institutional investigations, policy, and further research.

Research ethics III: Publication practices and authorship, conflicts of interest, and research misconduct

PURPOSE

In this series of articles--Research Ethics I, Research Ethics II, and Research Ethics III--the authors provide a comprehensive review of the 9 core domains for the responsible conduct of research (RCR) as articulated by the Office of Research Integrity.

METHOD

In Research Ethics III, they review the RCR domains of publication practices and authorship, conflicts of interest, and research misconduct. Whereas the legal definition of research misconduct under federal law pertains mainly to intentional falsification, fabrication, and plagiarism, they discuss a host of research practices that raise ethical concerns.

CONCLUSIONS

The integrity of the scientific record--its accuracy, completeness, and value--ultimately impacts the health and well-being of society. For this reason, scientists are both entrusted and obligated to use the highest standards possible when proposing, performing, reviewing, and reporting research or when educating and mentoring new investigators.

A theoretical comparison of the models of prevention of research misconduct

The current methods of dealing with research misconduct involve detection and rectification after the incident has already occurred. This method of monitoring scientific integrity exerts considerable negative effects on the concerned persons and is also wasteful of time and resources. Time has arrived for research administrators to focus seriously on prevention of misconduct. In this article, preventive models suggested earlier by Weed and Reason have been combined to arrive at six models of prevention. This is an effort to streamline the thinking regarding misconduct prevention, so that the advantages and disadvantages of each can be weighed and the method most appropriate for the institute chosen.

"Positive" results increase down the Hierarchy of the Sciences

The hypothesis of a Hierarchy of the Sciences with physical sciences at the top, social sciences at the bottom, and biological sciences in-between is nearly 200 years old. This order is intuitive and reflected in many features of academic life, but whether it reflects the "hardness" of scientific research--i.e., the extent to which research questions and results are determined by data and theories as opposed to non-cognitive factors--is controversial. This study analysed 2434 papers published in all disciplines and that declared to have tested a hypothesis. It was determined how many papers reported a "positive" (full or partial) or "negative" support for the tested hypothesis. If the hierarchy hypothesis is correct, then researchers in "softer" sciences should have fewer constraints to their conscious and unconscious biases, and therefore report more positive outcomes. Results confirmed the predictions at all levels considered: discipline, domain and methodology broadly defined. Controlling for observed differences between pure and applied disciplines, and between papers testing one or several hypotheses, the odds of reporting a positive result were around 5 times higher among papers in the disciplines of Psychology and Psychiatry and Economics and Business compared to Space Science, 2.3 times higher in the domain of social sciences compared to the physical sciences, and 3.4 times higher in studies applying behavioural and social methodologies on people compared to physical and chemical studies on non-biological material. In all comparisons, biological studies had intermediate values. These results suggest that the nature of hypotheses tested and the logical and methodological rigour employed to test them vary systematically across disciplines and fields, depending on the complexity of the subject matter and possibly other factors (e.g., a field's level of historical and/or intellectual development). On the other hand, these results support the scientific status of the social sciences against claims that they are completely subjective, by showing that, when they adopt a scientific approach to discovery, they differ from the natural sciences only by a matter of degree.

Mentoring and research misconduct: an analysis of research mentoring in closed ORI cases

We are reporting on how involved the mentor was in promoting responsible research in cases of research misconduct. We reviewed the USPHS misconduct files of the Office of Research Integrity. These files are created by Institutions who prosecute a case of possible research misconduct; ORI has oversight review of these investigations. We explored the role of the mentor in the cases of trainee research misconduct on three specific behaviors that we believe mentors should perform with their trainee: (1) review source data, (2) teach specific research standards and (3) minimize stressful work situations. We found that almost three quarters of the mentors had not reviewed the source data and two thirds had not set standards. These two behaviors are positively correlated. We did not see convincing evidence in the records that mentors were causing stress, but it was apparent in the convicted trainees' confessions that over 50% experienced some kind of stress. Secondary data, while not created for this research purpose, allows us to look at concrete research behaviors that are otherwise not very researchable. We believe it is important for mentors and institutions to devote more attention to teaching mentors about the process of education and their responsibilities in educating the next generation of scientists. This becomes a critical issue for large research groups who need to determine who is in charge educating, supervising and assuring data integrity.