When researchers learn about conducting research online, it can sometimes be difficult to understand quite how all the tools that are available can actually be applied to a project. This post is about how specific research ideas can be carried out using the kinds of features available for online research. Online research tools can make it much simpler to recruit balanced samples of individuals that are hard to find and selectively sample using more traditional methods.
On CloudResearch, you can selectively recruit participants based on many variables that may be of interest to you, ranging from age, gender and race, to political orientation, religion, employment, physical health symptoms, and personality (see them all here. This feature can be immensely useful in targeting specific populations. If you don’t want to use this feature or want to screen for participant characteristics of a kind that isn’t on our full list, you can still find specific populations by running your own screening studies to find the kind of participants that you want to target in subsequent studies (to learn more about how to do this see “best practices” section here, as well as this post here)
As an example of how this feature may be useful, let us imagine a religion researcher who is interested in how religiosity and religious orientation (Extrinsic vs Intrinsic orientations) predict many behaviors and decisions in life. For this researcher to carry out studies comparing different levels of religiosity, she needs to find a sample that is not religiously homogeneous. This researcher may even want to recruit a sample that is balanced, with a third of the sample being highly religious, a third of the sample being somewhat religious, and a third of the sample being not religious at all. Once a sample like this is recruited, all sorts of interesting questions about how religion impacts behaviors can be tested.
A study just like this was recently published by some of the members of the CloudResearch staff in the Journal of Religion and Health (Litman, Robinson, Weinberger-Litman, Finkelstein, 2017). In this study, CloudResearch’s Panel feature was used in order to selectively recruit 3 groups of approximately 150 participants with different relationships to religion, some being very religious, other less religious, and the 3rd group of those who were not religious at all. In this study, researchers found that attitudes toward cleanliness was significantly predicted by religiousness, and religious orientation, even when most covariates of attitudes toward cleanliness were included in a regression model. This research has important implications for the relationship between religion and health.
Imagine for a moment how difficult it would have been to conduct this research without online sampling methods. Perhaps researchers would have tried to reach out to students on their college campus either through a college database of students, or by recruiting people in person. These researchers might hope that by reaching out to great numbers of students they would find enough to fill these three categories of religion. Maybe if they couldn’t find enough religious students this way, they would need to seek out religious groups on campus and reach out to them directly. Additional time might be spent sitting with each student while they completed a survey. This would require multiple research assistants and a lot of time and perseverance. Still, this would result in data from a convenience sample that is highly skewed toward the young, more liberal, students that are on most campuses. If this research was conducted on MTurk without the use of CloudResearch tools, it also would have been very hard to get a sample that includes religious individuals, as MTurk has a much higher rate of atheism (around 40%), than the U.S. population.
Features available in online research have significant impact on the kinds of studies that can be carried out, enhancing methods available to researchers and making one aspect of their job a whole lot easier. There are many more examples of researchers using CloudResearch to carry out complex projects, some of which can be seen in the references linked below.
References
Dixon, L. J., Witcraft, S. M., McCowan, N. K., & Brodell, R. T. (2017). Stress and Skin Disease Quality of Life: The Moderating Role of Anxiety Sensitivity Social Concerns.British Journal of Dermatology
Gill, M. J., & Mendes, D. M. (2016). When the Minority Thinks “Essentially” Like the Majority: Blacks Distinguish Bio-Somatic from Bio-Behavioral Essentialism in Their Conceptions of Whites, and Only the Latter Predicts Prejudice. PloS one 11(8), e0160086.
Litman, L., Robinson, J., Weinberger-Litman, S. L., & Finkelstein, R. (2017). Both Intrinsic and Extrinsic Religious Orientation are Positively Associated with Attitudes Toward Cleanliness: Exploring Multiple Routes from Godliness to Cleanliness. Journal of religion and health, 1-12.
Litman, L., Williams, M. T., Rosen, Z., Weinberger-Litman, S. L., & Robinson, J. (2017). Racial Disparities in Cleanliness Attitudes Mediate Purchasing Attitudes Toward Cleaning Products: a Serial Mediation Model. Journal of racial and ethnic health disparities, 1-9.
