After the Guardian article came out portraying the Meta-Research team’s efforts to improve detection of data fabrication, I received a bunch of e-mails of support, questions, or people who wanted to change science (which we need to for larger issues than scientific misconduct).
The following are excerpts of an e-mail conversation and show how someone might go about fabricating data or why they would do such a thing. It is not always the researcher, it can also be one of the assistants, or anyone involved in the research process. I found this interesting, but most of all very blatant. Maybe people who fabricate are overconfident in their capability to do so.
A woman was telling her friend about the method she uses to produce the results for medical surveys related to drug trials. She stated that she normally has to get around 150-250 patient responses to surveys (I assume by phone) and described using a mobile phone app to take the recordings from only a few responses and manipulate it in order to sound like a different person. She also described making audio recordings of herself putting on different accents in order to generate the responses. As far as I could tell, the motivation was to reduce the amount of work; possibly combined with being able to claim any voucher associated with completing the questionnaire.
It sounded like it was at a low level of worker, presumably not someone who was involved in using the data. It sounded as if the recordings were audited in some way – that was why she was using the voice modulator in order to generate the samples but it wasn’t clear whether the audit was someone doing spot checks listening to them; or something more automated. I got the impression she had learnt the trick off a colleague but I’m not sure. As far as I could tell there was no intention to push the results one way or the other, but presumably a very uncertain result is almost as dangerous if not more.
If anyone has anecdotes of people boasting about fabrication that they have overheard and would like to share, please send them to me. We hardly know how people go about fabricating data, so anecdotes are more than welcome to improve some understanding and provide food-for-thought.