Evaluating mobile-based data collection for crowdsourcing behavioral research.

IF 4.6 2区 心理学 Q1 PSYCHOLOGY, EXPERIMENTAL Behavior Research Methods Pub Date : 2025-02-28 DOI:10.3758/s13428-025-02618-1
Dennis T Esch, Nikolaos Mylonopoulos, Vasilis Theoharakis
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Abstract

Online crowdsourcing platforms such as MTurk and Prolific have revolutionized how researchers recruit human participants. However, since these platforms primarily recruit computer-based respondents, they risk not reaching respondents who may have exclusive access or spend more time on mobile devices that are more widely available. Additionally, there have been concerns that respondents who heavily utilize such platforms with the incentive to earn an income provide lower-quality responses. Therefore, we conducted two studies by collecting data from the popular MTurk and Prolific platforms, Pollfish, a self-proclaimed mobile-first crowdsourcing platform, and the Qualtrics audience panel. By distributing the same study across these platforms, we examine data quality and factors that may affect it. In contrast to MTurk and Prolific, most Pollfish and Qualtrics respondents were mobile-based. Using an attentiveness composite score we constructed, we find mobile-based responses comparable with computer-based responses, demonstrating that mobile devices are suitable for crowdsourcing behavioral research. However, platforms differ significantly in attentiveness, which is also affected by factors such as the respondents' incentive for completing the survey, their activity before engaging, environmental distractions, and having recently completed a similar study. Further, we find that a stronger system 1 thinking is associated with lower levels of attentiveness and acts as a mediator between some of the factors explored, including the device used and attentiveness. In addition, we raise a concern that most MTurk users can pass frequently used attention checks but fail less utilized measures, such as the infrequency scale.

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MTurk 和 Prolific 等在线众包平台彻底改变了研究人员招募人类参与者的方式。然而,由于这些平台主要招募基于电脑的受访者,因此有可能无法接触到受访者,而这些受访者可能只能使用移动设备,或者花更多时间使用移动设备。此外,还有人担心,受访者在赚取收入的激励下大量使用这些平台,会降低回答的质量。因此,我们进行了两项研究,分别从流行的 MTurk 和 Prolific 平台、自称移动优先众包平台的 Pollfish 以及 Qualtrics 受众小组收集数据。通过在这些平台上分布相同的研究,我们考察了数据质量和可能影响数据质量的因素。与 MTurk 和 Prolific 不同,Pollfish 和 Qualtrics 的大多数受访者都是移动用户。使用我们构建的注意力综合评分,我们发现基于移动设备的回答与基于计算机的回答相当,这表明移动设备适合众包行为研究。然而,各平台在专注度方面存在显著差异,这还受到受访者完成调查的动机、参与调查前的活动、环境干扰以及最近是否完成过类似研究等因素的影响。此外,我们还发现,较强的 "系统 1 思维 "与较低的专注力水平相关,并在所探究的一些因素(包括所使用的设备和专注力)之间起到中介作用。此外,我们还提出了一个令人担忧的问题,即大多数 MTurk 用户可以通过常用的注意力检查,但却无法通过较少使用的测量,如不频繁量表。
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来源期刊
CiteScore
10.30
自引率
9.30%
发文量
266
期刊介绍: Behavior Research Methods publishes articles concerned with the methods, techniques, and instrumentation of research in experimental psychology. The journal focuses particularly on the use of computer technology in psychological research. An annual special issue is devoted to this field.
期刊最新文献
Probing beyond: The impact of model size and prior informativeness on Bayesian SEM fit indices. Polytomous explanatory item response models for item discrimination: Assessing negative-framing effects in social-emotional learning surveys. Evaluating mobile-based data collection for crowdsourcing behavioral research. The Animal-AI Environment: A virtual laboratory for comparative cognition and artificial intelligence research. Correction: Assessing the distortions introduced when calculating d': A simulation approach.
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