Abstract a scholar, deliberately or through gross negligence,

Abstract

Introduction: Science is playing a big role in our society.
Therefore, scientists should adhere to ethical standards. The number of
misconduct in scientific work differs from study to study. This paper focuses
only on plagiarism as one type of scientific misconduct. The following question
will be discussed: how often does plagiarism occur in different scientific
disciplines?

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Methods:
Every study has a
different approach to assess the prevalence of Plagiarism. The research
subjects of the first chosen study (5) are scientists. This meta-analysis (5)
summarizes the results of 17 survey studies, published between 1987 and 2010. The
other two studies (3, 6) analyzed retracted scientific articles (3) and papers
that were submitted in the Croatian Medical Journal from 2009 to 2010 (6).

Results:
According to the
meta-analysis (5), 1.7 % of the
respondents admitted of having plagiarized at least once. Furthermore, nearly
30 % are knowing that one of their colleagues have committed plagiarism at
least once. The second study (3) found that 9.8% of the 2047 articles they
analyzed, were retracted because of plagiarism. In the analysis of manuscripts
(6) 85 of 754 articles (11,3%) contained plagiarized parts.

Discussion: Because of the limitations and the difference in the
results in many studies, it could be assumed that the results are inaccurate. That´s
why it´s
very hard to determine the prevalence of plagiarism in scientific work. Though,
I believe that we can estimate the occurrence somewhere between the results of
the 3 studies (1,7-11 %), provided that most of the studies, containing
plagiarism, were detected.  

 

Introduction

Science, scientists and scientific research are
playing a big role in our society. Although most people are unaware of it,
gaining scientific knowledge affects a large part of our lives and the human
development. That´s why it´s important for scientists to adhere to ethical
standards and don´t commit fraud. According to the TUM Code of Conduct for
Safeguarding Good Academic Practice (1) “academic misconduct has occurred when
a scholar, deliberately or through gross negligence, makes false statements,
infringes upon intellectual property rights or the research activities of
others”. This includes e.g. fabrication and falsification of data, false
statements in letters of application and about the scholarly achievements of
applicants, plagiarism, intellectual theft especially of unpublished work,
claiming academic authorship, sabotaging the research activities of others and
making false accusations.

In Fanelli´s meta-analysis (2), nearly 2% of the
respondents admitted that they fabricated or falsified Research at least once,
while 14% of the respondents have noticed scientific misconduct of colleagues. Fang
and colleagues (3) noted that we have a huge increase in retracted articles
because of fraud since 1975.  As we shall
see there is a big discrepancy in the data about scientific misconduct.

I decided to focus only on results about plagiarism,
which is probably gaining the most attention in the media whenever a new case
occurs to the public. For example, the plagiarism scandal involving Mr.
Guttenberg in 2011 created sensation and caused a questioning of the
self-regulation of science. Plagiarism is defined as the “unauthorized use or
claims of authorship” (1) or, more detailed, “plagiarism takes many forms, from
passing off another’s paper as the author’s own paper, to copying or
paraphrasing substantial parts of another’s prepare, without attribution to
claiming results from research conducted by others” (4). These forms could be
self-plagiarism, true/direct plagiarism or patchwork/mosaic plagiarism. (4, 6)

This paper discusses the following question: how often
does plagiarism occur in different scientific disciplines? Therefore, I chose 3
Studies, which will be described in detail. The first one is a meta-analysis of
surveys, published in 2014 (5). The second one is a review of retracted biomedical
and life-science research articles (3). Lastly, I will assess a review of manuscripts
in the Croatian Medical Journal (6).

 

Methods

In this part I´m going
to present you the methodological aspects of the studies. Every study differs
more or less in its approach. There are two reviews (3, 6) which we will look
at, that have a quite similar research object.

At first, we´ll have a
closer look to the work of Pupovac and Fanelli (5). In 2014, the authors
published a systematic review and meta-analysis of anonymous surveys, in which
scientists of different academic disciplines were asked if they´ve ever
plagiarized. “From May to December 2011 they searched 35 bibliographic
databases, five grey literature databases and hand searched nine journals for
potentially relevant studies. (5)” Studies,
that asked scientists whether they have plagiarized or knew of a colleague who
committed plagiarism, were included. While studies, which were asking for
academic (e.g. students) plagiarism and studies which didn´t measured the
actual prevalence of plagiarism, were excluded. (In the end 18 relevant studies
were found.) The main outcome of effect was the extent of scientists who
admitted or witnessed plagiarism at least once. For the statistical analysis “proportions and relative standard errors
were logit-transformed …. Analyses used standard inverse-variance weighting,
and heterogeneity was measured with Chochran’s Q and I2 statistics.
Both quantities are directly proportional to the amount of between-study
variability. Cochran’s Q tests heterogeneity for statistical significance,
whereas I2 expresses the proportion of total variation in study
estimates that is due to heterogeneity. Irrespective of whether Cochran’s Q was
statistically significant, they pooled effects using a random effects model
based on restricted maximum likelihood estimation. (5)” Furthermore, they
used a mixed-effects meta-regression to evaluate the reasons for different
admission rates and also tested every factor. “In secondary and exploratory
analyses, a step-forward approach was used, in which significant factors
retained in the model as covariates whilst each remaining factor was tested
again, one at a time. (5)” Characteristics of the respondents (e.g. country of
the study, participants discipline) and methodological factors (e.g. sampling
method, response rate) were assessed. In addition, the authors compared data of
plagiarism to other forms of misconduct. Therefore, a matched-control paradigm and
the Wilcoxon´s signed rank test was used. Lastly, funnel plots were used to
measure the risk of publication bias and the robustness of results was tested.

Fang and colleagues (3)
are following a completely different approach to detect fraud. In 2012, they
published a detailed review of retracted scientific articles. 2.047 biomedical
and life-science research articles from PubMed, which have been published
between 1973 and 2011 were included in their review. In contrast to the
previous study, the aim was not only to detect plagiarism. The main outcome was
to find out the reasons of the retraction of the selected articles. Secondary,
they wanted to discover temporal trends, geographic origin, journal impact
factors and the “Time-to-Retraction” of the articles. For this reason, they had
to categorize and classify the articles. “Retracted articles were classified
according to whether the cause of retraction was documented fraud (data
falsification or fabrication), suspected fraud, plagiarism, error, unknown, or
other reasons (e.g., journal error, authorship dispute). (3)” 158 articles were
reclassified (e.g. from error to fraud) after cross-checking them against
reports of the Office of Research integrity. Any other missing information
about causes of retraction was searched in Google and included Retraction
Watch, news media, and other public records. “Impact factors were based on the
2011 edition of Journal Citation Reports Science Edition …. Journals without
an impact factor were assigned a value of 0.1. Statistical analyses were
performed using Prism (GraphPad Software). (3)”

In
the next paper (6) the research objects were, similar to the previous study and
in contrast to the first one, original research manuscripts, review manuscripts
and case reports submitted for publication in the Croatian Medical Journal. The
objective was to identify the prevalence of plagiarism of lodged papers from
2009 to 2010. The papers came from 64 countries. 754 documents (abstracts and
full texts) were checked by using the following plagiarism detection software:
eTBLAST, Cross-Check, WCopyfind. Those where analyzed through Déjà vu database
and manually verified. The findings were categorized into true plagiarism,
self-plagiarism, patchwork plagiarism and also were divided into countries of
origin. Furthermore, “manuscripts were grouped into three plagiarism categories
according to the extent of plagiarism (text similarity rate): minor (11-24%),
moderate (25-49%), and major (50% and more). (6)” The authors set criteria for plagiarism:
Criterion A for abstracts were 6 words in a row that are equivalent to words in
already existing abstracts. Criterion B for the full texts was a text similarity rate higher than
10% in parts of the manuscript. If this was the case, the text was
hand-checked, which included reading the whole paper and set it against the
suspected original. The study procedure is summarized in figure 1. In the
statistical analysis categorical variables were constituted with absolute and relative frequencies; “distributions were compared with test of proportions with power estimation. Continuous variables are expressed as median with 95% confidence interval (CI), because data did not follow the normal distribution (Kolmogorov–Smirnov test). (6)” For assessing Between-group differences Mann–Whitney and Kruskal–Wallis tests were used.  Additionally, the Mann-Whitney test adjusted for
multiple comparisons was deployed for Post-hoc comparisons. Spearman´s
correlation coefficient exhibited the degree of association between variables. “A P value of less than 0.05 was considered significant. (6)” Data were analyzed with the MedCalc statistical software. Russel-Lenth´s power and sample size
webpage calculated Power estimation for test of proportions.

 

Results

This part contains
a summary of the most important results of the 3 chosen studies. In Fang and
colleagues (3) article there are results about other types of misconduct. For
the purpose of this paper I will only mention the results on plagiarism.

But before that, we´ll
examine the findings of Pupovac and Fanelli (5). Their meta-analysis included
17 survey studies (Appendix 1), from which, 7 had been self-reports and the
others asked about colleague’s behavior. The studies were published between
1987 and 2010, mostly in the US and in peer-reviewed scientific journals.

1.7% of the
respondents confessed to have plagiarized at least once. When the word
“plagiarism” was explicitly used in a survey, the number amounts to 1.8%. Both
results were significant. “Between-studies
heterogeneity was not significantly different from that expected by sampling
error (Cochran e Q= 7.01, df=6, P=0.32; I2 =30%), although
statistical power to detect heterogeneity was low. Meta-regression identified
four study characteristics that, taken individual, had a statistically
significant influence on the outcome. Admission rates were negatively
associated with response rate, delivery method (mailed surveys yielded lower
admissions), and year of survey (admission rates have declined over time). In
addition, surveys conducted amongst students had significantly higher admission
rates than the others (5).” A mean pooled estimated 29,6% of respondent
reported, that they know at least one colleague, who committed plagiarism. In
surveys, which explicitly used the word “plagiarism”, the estimate was 23,61%,
but the difference not statistically significant. The heterogeneity between
studies was large and statistically significant. The exploratory analyses found
out that surveys that asked more generic/indirect questions had higher
admission rates and that there is an interaction between the year of survey and
study size. “To assess the robustness of the meta-analytical estimates,
they recalculated admission rates on self and non-self reports leaving out
one study a time. Admission rates thus recalculated were never significantly
different from the overall summary estimate. (5)”

The second study (3) found that 9.8% of the 2047
articles they analyzed, were retracted because of plagiarism. The rest of them
were revoked because of fraud, error, duplicate publication or another reason. The
issue of plagiarism in retracted articles is a recent but increasing event, as
you can see in Figure 2. Besides, plagiarism appears stronger in emerging and
poorer countries then e.g. in the USA. The journal impact factor does not show
a significant correlation with retractions because of plagiarism.

In the analysis of
manuscripts (6) 57 papers, analyzed by eTBLAST, applied to Criterion A and B.
Further WCopyfind-analysis found that 33 of these manuscripts had similar text
content to already existing papers. 228 abstracts met criterion A, while 151 of
all examined met criterion B, when analyzed with CrossCheck. After all further
analysis and manual verification 85 (of 754) articles contained plagiarized
parts. “Of them, 63 (8%) contained true
plagiarism and 22 (3%) contained self-plagiarism …. Of the 63 manuscripts
that contained true plagiarism, 18 contained patchwork plagiarism from two
sources and one manuscript contained plagiarism from three sources. Nine
manuscripts contained major plagiarism, with eight of them containing true
plagiarism …. (6)” Nearly one fifth of the 85 papers were peer reviewed.
Most of the plagiarized manuscripts came from China, Turkey and Croatia, while
the proportion of plagiarized than non-plagiarized articles from China (21% :
8%) was higher than the proportion of articles from Croatia (14% : 25%). 

 

Discussion

As I´ve already
mentioned in the beginning, there is a big discrepancy in the data.
Nevertheless, we saw that the 2 reviews (3, 6) with similar techniques to
detect plagiarism found out that 9.8% (3) and about 11% (6) of the examined
papers contained plagiarism. It can be concluded that different approaches lead
to different results. Douglas L Weed (7) described three types of empirical
estimation studies of misconduct and came to the same conclusion. In Pupovac
and Fanelli´s work (5) 1,7% of respondents admitted their own misbehavior,
while about 30% noticed one colleague who had plagiarized at least once. A
study conducted in Iran (8) had 4,9 % of the respondents admitting to
plagiarism. Mass surveys asking students about plagiarism had prevalence rates
up to 40% (9, 10). That leads us to the question, why does the results differ
from another. It can be assumed that the results are possibly inaccurate. As
Krumpal (11) pointed out, survey questions asking about taboo topics are often
distorted by the social desirability bias. Moreover, Pupovac and Fanelli (5) considered
that their survey data could be influenced by the study design. Hence, the
heterogeneity of the studies and the results is another limitation, which could
not be explained by their statistical methods. Besides these issues and the
publication bias I would like to point out one last limitation that was not
mentioned by the authors: It was not described what it meant to “know that a
colleague plagiarized”. We don´t know if this was only a rumor or the scientist
has real evidence for this accusation. Maybe that´s why the prevalence of plagiarism
in self-reports is much lower compared to the prevalence in non-self-reports.

Our other two studies
(3, 6) are not vulnerable for social desirability bias, because of their
research object. But, there are two other issues. The first one is, as already
noticed by Fang and colleagues (3) that “not all articles suspected or fraud
had been retracted”. Second, the results aren´t representative. We cannot draw
conclusions from this data to an entirety, because not all articles were
assessed. The same limitation occurs in the other study (6). The lack of
representativeness here is due to the plagiarism detection software, which
cannot search all databases. Because of those limitations and others in
different studies it´s very hard to determine the prevalence of plagiarism in
scientific work. Though, I believe that we can estimate the occurrence
somewhere between the results of the 3 studies. (1,7-11 %).

Future studies should
try to cope with the social desirability bias by using recommended methods (12)
e.g. use of forced choice items. In general, we need a lot more studies dealing
with this topic. The number of studies is rare. To provide completeness,
studies, that are using the same methodology as our second and third (3, 6)
should be conducted as systematic review.