Sunday, March 17, 2013

Research misconduct in LIS?

The editorial, Bogus Evidence by R. Laval Hunsucker in the latest Evidence-Based Library & Information Practice (EBLIP), discusses at great length the potential for research misconduct in the LIS field.  After setting the stage with the recent apparent rise in "questionable research practices" (QRP's) and outright fraud in the basic, medical, and social sciences, Laval brings our attention to our own profession, or rather, the lack of attention that our profession has given this issue.  He questions whether we, as members of the LIS profession, should consider research misconduct to be more or less or equally prevalent than in other research fields.  He admits that there is enough evidence to support any of these positions, yet not enough evidence to reach any conclusions.  And that, Laval asserts, is the crux of the problem.  Why should we assume that we are any better (or worse) than any other field?  And if we are neither better nor worse, shouldn't we be concerned that we are equally bad?

Laval brings up some very valid points, particularly regarding the difficulty of detecting research fraud.  Indeed, having been involved in a few research studies, I can imagine where fraud could occur, if so desired, particularly with data.  Auditing the data collected is rarely done, and yet, it is, I believe, the weakest (or easiest) point.  I have heard of large surveys where one single survey-taker fraudulently completed forms. Proper follow-ups detected the problem, but not before so many had been submitted that the integrity of the entire study had been threatened.  But that is an easier problem to detect because the researchers were themselves conducted the study with integrity.  The more difficult cases occur when the researchers manufacture the data.  Only a full data audit could detect this, but as mentioned above, this is so rarely done because it is difficult and time-consuming (and thus, costs money).

So, like so many researchers, those conducting studies in LIS are trusted to collect, analyze, and report their data in an unbiased and appropriate manner with little oversight.  Is this trust justified?  It appears that in this day and age of competition for jobs, promotions, and respect, people are growing more deceitful.  But could we not say, too, that in this day and age of growing transparency with the Internet, people are growing more skeptical and distrustful?

Professionally, I'm less concerned with outright fraud in the LIS literature than with QRP's related to poor training and limited knowledge.  This is particularly true regarding studies conducted by practicing librarians like myself, rather than LIS research faculty who have completed more formal training and apprenticeship in research, in the form of the dissertation.  Most practicing physicians do not initiate and formally conduct clinical studies.  There are many who participate in research, but very few actually develop proposals, gather the data, analyze the results, and write the papers of their own research.  Yet academic librarians are very often expected to do so themselves, often with less training than the physicians receive.  Therefore, why should we not expect QRP's to occur?  Laval himself notes that the "good news, and the other important difference, is that genuinely fraudulent research in LIS is almost certainly far less prevalent than sloppy research in LIS."

Actually, the apparent increase in research misconduct does need more study in order to establish the environment in which our research can be trusted.  But to judge all studies with a jaundiced eye will make it more difficult to move ideas into practice.  Laval discusses the many proposed solutions, ranging from changes to rewards and incentives to formalized research integrity training.  Like any complex problem with multiple foundations, no solution addressing just one of these foundations will work by itself.  But like they tell those with mental or addiction problems, simply recognizing the problem exists is the first step.

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