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Cited by 237

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The Reliability and Validity of Drug Use Responses in a Large Scale Longitudinal Survey

Single, Eric, Kandel, Denise, Johnson, Bruce D.·1975·Journal of Drug Issues

Abstract

The problem of developing reliable and valid measures is potentially greater for drug use than for other behaviors because the use of many of the drugs is Illegal and disapproved of by society. In the absence of independent criteria, responses to drug use questions may be tested for consistency and validity. In a survey based on a representative sample of 8,206 New York State public secondary school students, we find that self-reported Illicit drug use is consistent at one point in time, but less so over time. Self-reported Illicit drug use is strongly related to adolescents' attributes as well as to data independently obtained from best school friends. Only a very small proportion of respondents report the use of a fictitious drug. However, inconsistencies over time are related to sporadic patterns of drug use, suggesting that the failure to report certain types of drug use is more the result of poor recall than of willful concealment of use. Underreporting is potentially a greater problem in drug research than overreporting.

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Metadata

Authors
Single, E., Kandel, D., & Johnson, B. D.
Venue
Journal of Drug Issues
Published
1975-10
Volume
5
Issue
4
Pages
426-443
ISSN
  • 0022-0426 (ISSN-L)
  • 1945-1369
OpenAlex
W2339443500
Cited by
237
References
0
FWCI
18.78
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Reliability and Validity of Drug Use Responses in a Large Scale Longitudinal Survey. https://app.cochat.ai/papers/10.1177/002204267500500411
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Single, E., Kandel, D., & Johnson, B. D. (1975). The Reliability and Validity of Drug Use Responses in a Large Scale Longitudinal Survey. Journal of Drug Issues. https://doi.org/10.1177/002204267500500411

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.