Online data collection in auditory perception and cognition research: Recruitment, testing, data quality and ethical considerations
Abstract
Online studies using recruitment services (such as Prolific or Amazon’s MTurk) and online testing platforms (such as Gorilla or PsyToolkit) are becoming increasingly common in psychological science. Although auditory disciplines have been slower to adopt these methods, uptake is rapidly increasing in auditory perception and cognition research. Utilizing online data collection and recruitment presents several advantages to researchers in terms of the speed of research and the range of target demographics available compared to either traditional lab studies or web-based recruitment via traditional means. Online platforms and recruitment services also present a set of technical and ethical challenges owing to the fact that the people completing experiments are working with their own devices outside the lab. This article discusses the potential technical and ethical implications of online studies, including both recruitment services and online testing platforms, with specific reference to auditory perception and cognition research. Rates of remuneration, sampling characteristics, anonymity, quality control, and ethics are all discussed with respect to these approaches. We also provide proposals for how researchers can ensure that online research meets present-day ethical and technical guidelines as well as research transparency standards
Study specs
- Authors
- T Eerola,J Armitage,N Lavan
- Institution
- Durham University
- Discipline
- Cognitive Psychology,Research Methodology
- Year
- 2021
- Human Data Platform
- Prolific
- Source
- View Source Google Scholar
Peer Review & Critical Discussion
Potential Selection Bias in 2023 Cohort
The participant pool shows a concerning overrepresentation of users from high-income demographics. Looking at Table 3, we can see that 78% of respondents had annual incomes above $75k, which significantly limits the generalizability of these findings to broader populations.
Non-naive Participants Issue
I've noticed a methodological concern regarding participant naivety. Given that Prolific users often complete multiple studies, there's a real risk that participants had prior exposure to similar experimental paradigms, which could confound the results.
RLHF Applicability to This Study Design
The implications for RLHF training pipelines are understated. If we accept the authors' conclusions about preference stability, this has direct consequences for how we should structure reward model training. The temporal decay effect described in Section 4.2 is particularly relevant.
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