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Micro-incentives represent a new but little-studied trend in participant compensation for user studies. In this paper, we use a combination of statistical analysis and models from labor economics to evaluate three canonical micro-payment schemes in the context of high-burden user studies, where participants wear sensors for extended durations. We look at how these strategies affect compliance, data quality, and retention, and show that when used carefully, micro-payments can be highly beneficial. We find that data quality is different across the micro-incentive schemes we experimented with, and therefore the incentive strategy should be chosen with care. We think that adaptive micro-payment based incentives can be used to successfully incentivize future studies at much lower cost to the study designer, while ensuring high compliance, good data quality, and lower retention issues.
Musthag et al. (Sat,) studied this question.