Scientific ethics - a "corrosive" problem?

Nature is reporting this week on a new study showing that 1/3 of NIH grant recipients surveyed admitted to some level of scientific bad behavior (ranging from outright falsification to publishing the same data in two places to rejecting a datum based on gut instinct). See their story here. (You may need to create an account, but its free). Out of sixteen offenses surveyed their top ten were considered worthy of punishment at an institutional level, while the bottom six were more along the lines of carelessness. Some of the offenses were specifically things related to human subjects, but others were pretty applicable to anyone. The results were included in an editorial by the authors that some of the "corrosive" behaviors may be the result of competitive funding and work environments. While part of me wants this study and its topic to get more "airplay" and fire up some real discussions about the way science is funded and careers are tracked, another part of me doesn't want this to become another public smudge mark on our profession (much like the recent Yucca Mtn scandal).

But, at the very least, their queries can provide some useful fodder for self reflection. They were yes/no questions, whether you had engaged in any of these behaviours in the past three years. The questions are (BC Martinson, MS Anderson and R de Vries, Nature 435, 737-738 (9 June 2005)):

Major transgressions

1. Falsifying or cooking data
2. ignoring major aspects of human-subject requirements
3. not properly disclosing involvement with firms whose products are based on your own research
4. relationships with students, research subjects, or clients that may be considered questionable
5. using another's ideas without obtaining permission or giving proper credit
6. unauthorized use of confidential information in connection with one's own research
7. failing to present data that conflict with one's previous research
8. circumventing certain minor aspects of human-subjects requirements
9. overlooking other's use of flawed data or questionable interpretation of data
10. changing the design, methodology, or results of a study in response to pressure from a funding source

Other transgressions

1. Publishing the same data or results in two or more publications
2. Inappropriately assigning authorship credit
3. Witholding details of methodology or results in papers or proposals
4. Using inadequate or inappropriate research designs
5. Dropping observations or data points from analyses based on gut feeling they were inadequate
6. inadequate record keeping on research projects