Assessing the self-reported honesty threshold in adolescent epidemiological research: comparing supervised machine learning and inferential statistical techniques

Assessing the self-reported honesty threshold in adolescent epidemiological research: comparing supervised machine learning and inferential statistical techniques

Abstract Background Epidemiological surveys offer essential data on adolescent substance use. Nevertheless, the precision of these self-report-based surveys often faces mistrust from researchers and the public. We evaluate the efficacy of a direct method to assess data quality by asking adolescents...

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Bibliographic Details
Main Authors: Janaka V. Kosgolla, Douglas C. Smith, Shahana Begum, Crystal A. Reinhart
Format: Article
Language:English
Published: BMC 2023-09-01
Series:BMC Medical Research Methodology
Subjects:
Adolescents
Substance use
Self-reported honesty
Machine learning
Response validity
Epidemiological surveys
Online Access:https://doi.org/10.1186/s12874-023-02035-y

Internet

https://doi.org/10.1186/s12874-023-02035-y

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