Fraudulent and Misleading Data

The Use of Fraudulent or Misleading Data

Researchers can tamper with data when they record, report, or use data for instructional purposes. According to current Federal Guidelines for Research Misconduct, the use of fraudulent or misleading data is in violation of U.S. federal laws [Page 587]when a researcher has (a) deviated from standard practices in the field, (b) intentionally deceived or engaged in reckless research practices, and (c) when there is sufficient evidence to support these accusations. Under federal guidelines, using fraudulent or misleading data can be classified as either falsification (when data or elements of the research process have been manipulated to improperly represent the actual data) or fabrication (data or results have been made up).

The use of fraudulent or misleading data is not limited to quantitative research activities. Researchers employing qualitative or rhetorical methods can also engage in this unprofessional activity. In the most egregious cases of research misconduct, researchers have intentionally falsified or fabricated data to achieve different results than their actual data show. For example, some researchers have made up data to inflate their results or omitted data that did not support their hypotheses. Other researchers have unintentionally reported misleading data. For example, some researchers have ignorantly created graphs that exaggerate their results.

There are many reasons why researchers would intentionally use fraudulent or misleading data. Environmental reasons may include financial pressure (e.g., pressure to win government grants), institutional demands (e.g., requirements and time constraints in the tenure process), competition (e.g., colleagues competing for resources), and public pressure (e.g., pressure to solve an important societal problem). Personal reasons may include desires for prestige, recognition by colleagues, and financial gain. Some scholars have criticized universities for perpetuating competitive and pressured environments that tempt researchers to engage in research misconduct. Though intriguing, this criticism does not release individual researchers from the ethical responsibility to truthfully present their research.

Two reasons researchers unintentionally use misleading data are carelessness and naiveté. Examples of carelessness in research include improper recording of data or data gathering procedures; mistakes in transcribing, coding, or uploading data; and haphazard decisions about analysis procedures. Examples of naiveté include using inappropriate analysis procedures, presenting data improperly, misinterpreting the results, and failing to understand and report study limitations. Regardless of intent, there are serious consequences for using fraudulent or misleading data.

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