The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
Telephone versus Face-to-Face Interviewing of National Probability Samples with Long Questionnaires
Abstract
The last 50 years have seen a gradual replacement of face-to-face interviewing with telephone interviewing as the dominant mode of survey data collection in the United States. But some of the most expensive and large-scale nationally funded, long-term survey research projects involving national area-probability samples and long questionnaires retain face-to-face interviewing as their mode. In this article, we propose two ways in which shifting such surveys to random digit dialing (RDD) telephone interviewing might affect the quality of data acquired, and we test these hypotheses using data from three national mode experiments. Random digit dialing telephone respondents were more likely to satisfice (as evidenced by no-opinion responding, nondifferentiation, and acquiescence), to be less cooperative and engaged in the interview, and were more likely to express dissatisfaction with the length of the interview than were face-to-face respondents, despite the fact that the telephone interviews were completed more quickly than the face-to-face interviews. Telephone respondents were also more suspicious about the interview process and more likely to present themselves in socially desirable ways than were face-to-face respondents. These findings shed light on the nature of the survey response process, on the costs and benefits associated with particular survey modes, and on the nature of social interaction generally.
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Metadata
- Authors
- Holbrook, A. L., Green, M. C., & Krosnick, J. A.
- Venue
- Public Opinion Quarterly
- Publisher
- Oxford University Press (OUP)
- Published
- 2003
- Volume
- 67
- Issue
- 1
- Pages
- 79-125
- ISSN
- 0033-362X (ISSN-L)
- 1537-5331
- OpenAlex
- W2184015064
- Cited by
- 916
- References
- 71
- FWCI
- 64.25
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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