Changes in substance use-related health risk behaviors on the timeline follow-back interview as a function of length of recall period

Anne Buu; Runze Li; Maureen A. Walton; Hanyu Yang; Marc A. Zimmerman; Rebecca M. Cunningham

doi:10.3109/10826084.2014.891621

Changes in substance use-related health risk behaviors on the timeline follow-back interview as a function of length of recall period

Anne Buu
, Runze Li
, Maureen A. Walton
, Hanyu Yang
, Marc A. Zimmerman
, Rebecca M. Cunningham

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

The timeline follow-back (TLFB) interview was adopted to collect retrospective data on daily substance use and violence from 598 youth seeking care in an urban Emergency Department in Flint, Michigan during 2009-2011. Generalized linear mixed models with flexible smooth functions of time were employed to characterize the change in risk behaviors as a function of the length of recall period. Our results suggest that the 1-week recall period may be more effective for capturing atypical or variable patterns of risk behaviors, whereas a recall period longer than 2 weeks may result in a more stable estimation of a typical pattern.

Original language	English (US)
Pages (from-to)	1259-1269
Number of pages	11
Journal	Substance Use and Misuse
Volume	49
Issue number	10
DOIs	https://doi.org/10.3109/10826084.2014.891621
State	Published - Aug 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 16 Peace, Justice and Strong Institutions

All Science Journal Classification (ASJC) codes

Medicine (miscellaneous)
Health(social science)
Public Health, Environmental and Occupational Health
Psychiatry and Mental health

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10.3109/10826084.2014.891621

Cite this

@article{a28c9cf497cc4533852be4928fa61218,

title = "Changes in substance use-related health risk behaviors on the timeline follow-back interview as a function of length of recall period",

abstract = "The timeline follow-back (TLFB) interview was adopted to collect retrospective data on daily substance use and violence from 598 youth seeking care in an urban Emergency Department in Flint, Michigan during 2009-2011. Generalized linear mixed models with flexible smooth functions of time were employed to characterize the change in risk behaviors as a function of the length of recall period. Our results suggest that the 1-week recall period may be more effective for capturing atypical or variable patterns of risk behaviors, whereas a recall period longer than 2 weeks may result in a more stable estimation of a typical pattern.",

author = "Anne Buu and Runze Li and Walton, \{Maureen A.\} and Hanyu Yang and Zimmerman, \{Marc A.\} and Cunningham, \{Rebecca M.\}",

note = "Funding Information: Buu{\textquoteright}s research was supported by a National Institutes of Health (NIH) grant, K01 AA016591; Li{\textquoteright}s research was supported by NIH grants P50 DA010075, P50 DA036107, and R01 CA168676; The work of Walton, Zimmerman, and Cunningham was supported by a NIH grant R01 DA024646. Funding Information: Runze Li, Ph.D., is Distinguished Professor of Statistics and Professor of Public Health Sciences, a member of the Methodology Center, Pennsylvania State University, University Park, Pennsylvania, USA. Dr. Li{\textquoteright}s research interest includes analysis of intensive longitudinal data, variable selection for high dimensional data, and statistical methodology applications to substance use research, life science research, and engineering research. His work has been funded by the National Institute on Drug Abuse (NIDA) and the National Science Foundation. He has published in a broad assortment of methodological and substantive journals. Dr. Li is co-editor(in-chief) of Annals of Statistics, and served as Associate Editor of Annals of Statistics, Journal of American Statistical Association, and Statistica Sinica. Awards include NSF Career award, Fellow of Institute of Mathematical Statistics, Fellow of American Statistical Association and the United Nations{\textquoteright} World Meteorological Organization Gerbier-Mumm International Award for 2012.",

year = "2014",

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doi = "10.3109/10826084.2014.891621",

language = "English (US)",

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journal = "Substance Use and Misuse",

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AU - Buu, Anne

AU - Li, Runze

AU - Walton, Maureen A.

AU - Yang, Hanyu

AU - Zimmerman, Marc A.

AU - Cunningham, Rebecca M.

N1 - Funding Information: Buu’s research was supported by a National Institutes of Health (NIH) grant, K01 AA016591; Li’s research was supported by NIH grants P50 DA010075, P50 DA036107, and R01 CA168676; The work of Walton, Zimmerman, and Cunningham was supported by a NIH grant R01 DA024646. Funding Information: Runze Li, Ph.D., is Distinguished Professor of Statistics and Professor of Public Health Sciences, a member of the Methodology Center, Pennsylvania State University, University Park, Pennsylvania, USA. Dr. Li’s research interest includes analysis of intensive longitudinal data, variable selection for high dimensional data, and statistical methodology applications to substance use research, life science research, and engineering research. His work has been funded by the National Institute on Drug Abuse (NIDA) and the National Science Foundation. He has published in a broad assortment of methodological and substantive journals. Dr. Li is co-editor(in-chief) of Annals of Statistics, and served as Associate Editor of Annals of Statistics, Journal of American Statistical Association, and Statistica Sinica. Awards include NSF Career award, Fellow of Institute of Mathematical Statistics, Fellow of American Statistical Association and the United Nations’ World Meteorological Organization Gerbier-Mumm International Award for 2012.

PY - 2014/8

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N2 - The timeline follow-back (TLFB) interview was adopted to collect retrospective data on daily substance use and violence from 598 youth seeking care in an urban Emergency Department in Flint, Michigan during 2009-2011. Generalized linear mixed models with flexible smooth functions of time were employed to characterize the change in risk behaviors as a function of the length of recall period. Our results suggest that the 1-week recall period may be more effective for capturing atypical or variable patterns of risk behaviors, whereas a recall period longer than 2 weeks may result in a more stable estimation of a typical pattern.

AB - The timeline follow-back (TLFB) interview was adopted to collect retrospective data on daily substance use and violence from 598 youth seeking care in an urban Emergency Department in Flint, Michigan during 2009-2011. Generalized linear mixed models with flexible smooth functions of time were employed to characterize the change in risk behaviors as a function of the length of recall period. Our results suggest that the 1-week recall period may be more effective for capturing atypical or variable patterns of risk behaviors, whereas a recall period longer than 2 weeks may result in a more stable estimation of a typical pattern.

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Changes in substance use-related health risk behaviors on the timeline follow-back interview as a function of length of recall period

Abstract

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