Dataset Information

Item Responses in Quantity-Frequency Questionnaires: Implications for Data Generalizability.

ABSTRACT: Alcohol consumption is an important predictor of a variety of negative outcomes. There is an extensive literature that examines the differences in the estimated level of alcohol consumption between types of assessments (e.g., quantity-frequency [QF] questionnaires, daily diaries). However, it is typically assumed that all QF-based measures are nearly identical in their assessment of the volume of alcohol consumption in a population. Using timeline follow-back data and constructing common QF consumption measures, we examined differences among survey instruments to assess alcohol consumption and heavy drinking. Using three data sets, including clinical to community samples, we demonstrate how scale-specific item characteristics (i.e., number of response options and ranges of consumption assessed by each option) can substantially affect the estimated mean level of consumption and estimated prevalence of binge drinking. Our analyses suggest that problems can be mitigated by employing more resolved measures of quantity and frequency in consumption questionnaires.

SUBMITTER: Stevens JE

PROVIDER: S-EPMC8351754 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Item Responses in Quantity-Frequency Questionnaires: Implications for Data Generalizability.

Stevens Jordan E JE Shireman Emilie E Steinley Douglas D Piasecki Thomas M TM Vinson Daniel D Sher Kenneth J KJ

Assessment 20190625 5

Alcohol consumption is an important predictor of a variety of negative outcomes. There is an extensive literature that examines the differences in the estimated level of alcohol consumption between types of assessments (e.g., quantity-frequency [QF] questionnaires, daily diaries). However, it is typically assumed that all QF-based measures are nearly identical in their assessment of the volume of alcohol consumption in a population. Using timeline follow-back data and constructing common QF cons ...[more]

PMID: 31238706

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Dataset Information

Item Responses in Quantity-Frequency Questionnaires: Implications for Data Generalizability.

Publications

Item Responses in Quantity-Frequency Questionnaires: Implications for Data Generalizability.

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