We appreciate the points raised by Chrisinger about the generalizability of our findings
1
and agree that researchers should be careful to present the perspectives of vulnerable
populations. Our article acknowledges the potential limitations (and strengths) of
using Amazon Mechanical Turk for data collection, as well as challenges with generalizability.
The fact that our findings were nearly identical to a prior nationally representative
study was informative about the level of bias potentially present in our results.
2
We agree with Chrisinger that the Supplemental Nutrition Assistance Program (SNAP)
is a “highly stigmatized welfare program” and were encouraged that our study found
high levels of public support for SNAP policies. SNAP is a critical program for the
health and well-being of millions of low-income Americans; SNAP participants are the
most important stakeholder group, but their voice has been largely lacking in the
literature on SNAP. Thus, we published our survey questions in hope that researchers
can examine these issues in future studies capturing populations that may have been
under-represented in our sample.To read this article in full you will need to make a payment
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References
- Improving the nutritional impact of the Supplemental Nutrition Assistance Program: perspectives from the participants.Am J Prev Med. 2017; 52: S193-S198https://doi.org/10.1016/j.amepre.2016.07.024
- Public support for policies to improve the nutritional impact of the Supplemental Nutrition Assistance Program (SNAP).Public Health Nutr. 2014; 17: 219-224https://doi.org/10.1017/S136898001200506X
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© 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
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- Letter Regarding “Improving the Nutritional Impact of the Supplemental Nutrition Assistance Program”American Journal of Preventive MedicineVol. 53Issue 3
- PreviewIn their article, “Improving the Nutritional Impact of the Supplemental Nutrition Assistance Program: Perspectives From the Participants,” Leung et al.1 present survey data collected through an online service, Amazon Mechanical Turk (mTurk). Unfortunately, the piece does not report enough information to draw reasonable conclusions about generalizability and, more importantly, risks leading readers toward policy conclusions that are not necessarily supported by the data. This letter presents two critical concerns regarding data interpretation and participant selection.
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