Using the Timeline Followback to determine time windows representative of annual alcohol consumption with problem drinkers

Vakili, Shervin; Sobell, Linda C.; Sobell, Mark B.; Simco, Edward R.; Agrawal, Sangeeta

doi:10.1016/j.addbeh.2008.03.009

Cited by 52 publications

(53 citation statements)

References 27 publications

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“…We also created scatter plots to compare correlations between average number of drinks per day over 30 days to 14 days and to 7 days. To evaluate agreement between 30 days and 14 days and between 30 days and 7 days for heavy episodic drinking criteria, we evaluated percent kappa statistics, agreement, sensitivity, and negative predictive values considering the 30-day report as the gold standard as supported by prior research (Vakili et al, 2008). Statistical analyses were performed using Stata Version 10.0 (StataCorp LP, College Station, TX).…”

Section: Discussionmentioning

confidence: 99%

“…The TLFB was administered via telephone interview by trained telephone interviewers and assessed the quantity and pattern of alcohol consumption over the prior 30-day period (Braithwaite et al, 2005). The TLFB has been evaluated in clinical and nonclinical populations and has been shown to have high test-retest reliability across multiple populations of drinkers (Roy et al, 2008;Sobell et al, 1988Sobell et al, , 2001Sobell et al, , 2003Vakili et al, 2008).…”

Section: Data Collectionmentioning

confidence: 99%

“…Timeline followback (TLFB) is a well-established and valid method to measure patient self-report of alcohol consumption Sobell et al, 1988Sobell et al, , 2001. The use of TLFB has the advantage that it allows for varied time horizons ranging from 1 day to 1 year (Vakili et al, 2008). However, for many researchers, longer time horizons increase subject response burden and may not lead to more informative data (Vakili et al, 2008).…”

mentioning

confidence: 99%

“…The use of TLFB has the advantage that it allows for varied time horizons ranging from 1 day to 1 year (Vakili et al, 2008). However, for many researchers, longer time horizons increase subject response burden and may not lead to more informative data (Vakili et al, 2008). The concordance between longer versus shorter time horizons has been a subject of prior research (Carey et al, 2004;Hoeppner et al, 2010;Roy et al, 2008;Sobell et al, 2001;Toll et al, 2008;Vakili et al, 2008) but rarely investigated in non-substance-related treatment-seeking individuals and not in patients with HIV infection.…”

mentioning

confidence: 99%

“…HIV-infected individuals may differ from noninfected individuals in some of the variables associated with the extent to which sampled time windows of drinking estimation are representative. These include stability of drinking patterns, alcohol problem severity, and motivation to change (Bertholet et al, 2010;Braithwaite et al, 2008;Kraemer et al, 2006;Vakili et al, 2008). Thus, it is important to document the performance of the TLFB in those with and without HIV infection.…”

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confidence: 99%

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Measuring Alcohol Consumption Using Timeline Followback in Non-Treatment-Seeking Medical Clinic Patients With and Without HIV Infection: 7-, 14-, or 30-day Recall

Fiellin

McGinnis

Maisto

et al. 2013

J. Stud. Alcohol Drugs

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Section: Discussionmentioning

confidence: 99%

Section: Data Collectionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Measuring Alcohol Consumption Using Timeline Followback in Non-Treatment-Seeking Medical Clinic Patients With and Without HIV Infection: 7-, 14-, or 30-day Recall

Fiellin

McGinnis

Maisto

et al. 2013

J. Stud. Alcohol Drugs

View full text Add to dashboard Cite

Marijuana-Using Drivers, Alcohol-Using Drivers, and Their Passengers

2014

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Importance Driving after marijuana use increases the risk of a motor vehicle crash. Understanding this behavior among young drivers and how it may differ from alcohol-related driving behaviors could inform prevention efforts. Objective To describe prevalence, sex differences, and risk factors associated with underage college students’ driving after using marijuana, driving after drinking alcohol, or riding with a driver using these substances. Design, Setting, Participants Cross-sectional telephone survey of a random sample of 315 first-year college students (aged 18-20 years) from 2 large public universities, who were participating in an ongoing longitudinal study. At recruitment, 52.8% of eligible individuals consented to participate; retention was 93.2% one year later when data for this report was collected. Main Outcome Measure(s) Self-reported past-28-day driving after marijuana use, riding with a marijuana-using driver, driving after alcohol use, and riding with an alcohol-using driver. Results In the prior month, 20.3% of students had used marijuana. Among marijuana-using students, 43.9% of males and 8.7% of females drove after using marijuana (p<0.001) and 51.2% of male and 34.8% of female students rode as a passenger with a marijuana-using driver (p=0.21). Most students (65.1%) drank alcohol, and among this group 12.0% of male students and 2.7% of female students drove after drinking (p=0.01), with 20.7% and 11.5% (p=0.07), respectively, reporting riding with a drinking driver. Controlling for demographics and substance use behaviors, driving after substance use was associated with at least a 2-fold increase in risk of being a passenger with another user; the reverse was also true. A 1% increase in the reported percentage of friends using marijuana was associated with a 2% increased risk of riding with a marijuana using driver (95% CI=1.01-1.03). Among students using any substances, past 28-day use of only marijuana was associated with a 6.24-fold increased risk of driving after substance use compared to using only alcohol (95% CI=1.89-21.7). Conclusions and Relevance Driving and riding after marijuana use is common among underage, marijuana-using college students. This is concerning given recent legislation that may increase marijuana availability.

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The ad-libitum alcohol ‘taste test’: secondary analyses of potential confounds and construct validity

et al. 2015

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RationaleMotivation to drink alcohol can be measured in the laboratory using an ad-libitum ‘taste test’, in which participants rate the taste of alcoholic drinks whilst their intake is covertly monitored. Little is known about the construct validity of this paradigm.ObjectiveThe objective of this study was to investigate variables that may compromise the validity of this paradigm and its construct validity.MethodsWe re-analysed data from 12 studies from our laboratory that incorporated an ad-libitum taste test. We considered time of day and participants’ awareness of the purpose of the taste test as potential confounding variables. We examined whether gender, typical alcohol consumption, subjective craving, scores on the Alcohol Use Disorders Identification Test and perceived pleasantness of the drinks predicted ad-libitum consumption (construct validity).ResultsWe included 762 participants (462 female). Participant awareness and time of day were not related to ad-libitum alcohol consumption. Males drank significantly more alcohol than females (p < 0.001), and individual differences in typical alcohol consumption (p = 0.04), craving (p < 0.001) and perceived pleasantness of the drinks (p = 0.04) were all significant predictors of ad-libitum consumption.ConclusionsWe found little evidence that time of day or participant awareness influenced alcohol consumption. The construct validity of the taste test was supported by relationships between ad-libitum consumption and typical alcohol consumption, craving and pleasantness ratings of the drinks. The ad-libitum taste test is a valid method for the assessment of alcohol intake in the laboratory.

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Using the Timeline Followback to determine time windows representative of annual alcohol consumption with problem drinkers

Cited by 52 publications

References 27 publications

Measuring Alcohol Consumption Using Timeline Followback in Non-Treatment-Seeking Medical Clinic Patients With and Without HIV Infection: 7-, 14-, or 30-day Recall

Measuring Alcohol Consumption Using Timeline Followback in Non-Treatment-Seeking Medical Clinic Patients With and Without HIV Infection: 7-, 14-, or 30-day Recall

Marijuana-Using Drivers, Alcohol-Using Drivers, and Their Passengers

The ad-libitum alcohol ‘taste test’: secondary analyses of potential confounds and construct validity

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