For some neuroscience or psychology experiments with simple task repeated for a large number of trials (like event-related potential experiment, or measuring human visibility map), what are some good advice to prevent subjects from getting tired and bored and negatively affect the data?
Hello,
Boredom appears to be a state of drive-tension in which the drive-aims are repressed; yet the tension as such is experienced, and therefore one turns to the external world for help in the struggle against repression. The person who is bored can be therefore compared to one who has forgotten a name and inquires about it from others. When a bored person is looking for stimulation because he has lost his drive-aims to repression, it is understandable that, to stimulation which could bring about the desired discharge, he will offer the same resistance which resulted in the repression of the drive-aims; and that if the “stimulation” offered by the external world is too distantly related to the original drive-aim, there cannot occur displacement of the cathectic-energy onto the activity suggested by the stimulation.
Boredom is a "therapeutic process". You can refer to the following links for further information.
http://www.contemporarypsychotherapy.org/volume-9-no-1-summer-2017/boredom-in-the-countertransference-mutual-dissociation-in-the-therapeutic-encounter/
https://www.ncbi.nlm.nih.gov/pubmed/6085028
https://static1.squarespace.com/static/53a79084e4b01786c921de45/t/53a86478e4b009ec07711b38/1403544696336/On+the+Psychology+of+Boredom+%28Fenichel%2C+1951%29.pdf
Best Regards,
Great question.
Trial-by-trial feedback can help, but will increase (perceptual) learning, so best to discard the first few 100 trials (i.e., an initial practise block).
Frequent breaks, lots of encouragement, telling them the research is important, and paying them accordingly, also good strategies. If a very long experiment, then making them periodically stand up and take on fluids can help militate against fatigue. If more than ~2000 trials / 90 minutes, may need to consider breaking the experiment up over multiple sessions (but again, learning effects then become an issue).
If really important, you can also further incentivize good performance with monetary bonuses (based on real performance, or awarded pseudo-randomly).
Finally, some people *will* get bored. So it's important that you observe your participants carefully (and make notes), so you have an independent reason to exclude them later if necessary (in addition to bad performance on 'catch trials' and/or overall)
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