Dataset Information

Validation of a multisubstance online Timeline Followback assessment.

ABSTRACT: OBJECTIVES:The Timeline Followback (TLFB) was originally developed to assess alcohol consumption patterns (American Journal of Public Health, 86, 1996, 966) and has been increasingly modified for Web-based use. Additionally, new modes of substance use administration have emerged, creating a need for an adaptable TLFB tool than can capture data such as cannabis product potency or prescription drug use. Our goal was to validate an online TLFB that reliably assesses a wide range of substances in greater detail. METHODS:Using a within-subjects counterbalanced design, daily substance use data were collected from 50 college students over a 14-day retrospective period using both the traditional in-person TLFB and online TLFB (O-TLFB). RESULTS:All substance use variables, including detailed measures of cannabis metrics, correlated significantly (r's ranged from .653 to .944, p < .001) between TLFB versions. Further, results demonstrated that both the online TLFB and in-person TLFB demonstrated concurrent validity with both the Alcohol Use Disorders Identification Test (AUDIT) and Marijuana Dependence Scale (MDS). CONCLUSION:Overall, the data suggest that this new O-TLFB demonstrates strong reliability and delivers a versatile and secure tool for substance use assessment that is relevant to a variety of biomedical and psychological research contexts.

SUBMITTER: Martin-Willett R

PROVIDER: S-EPMC6955818 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Validation of a multisubstance online Timeline Followback assessment.

Martin-Willett Renée R Helmuth Timothy T Abraha Median M Bryan Angela D AD Hitchcock Leah L Lee Kaitlyn K Bidwell L Cinnamon LC

Brain and behavior 20191202 1

<h4>Objectives</h4>The Timeline Followback (TLFB) was originally developed to assess alcohol consumption patterns (American Journal of Public Health, 86, 1996, 966) and has been increasingly modified for Web-based use. Additionally, new modes of substance use administration have emerged, creating a need for an adaptable TLFB tool than can capture data such as cannabis product potency or prescription drug use. Our goal was to validate an online TLFB that reliably assesses a wide range of substanc ...[more]

PMID: 31793226

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Project description:Prenatal alcohol exposure (PAE) has been linked to poor pregnancy outcomes, yet there is no recognized standard for PAE assessment, and the specific effects of quantity, frequency, and timing remain largely unknown. The Safe Passage Study was designed to investigate the role of PAE in a continuum of poor peri- and postnatal outcomes. The objective of this manuscript is to describe the rationale for, and feasibility of, modifications to the traditional Timeline Followback (TLFB) for collecting PAE information in a large cohort of pregnant women. Participants from the Northern Plains region (in the United States) and Cape Town, South Africa, were followed prospectively using a modified 30-day TLFB interview, administered up to five times, to obtain detailed PAE information. Required modifications for our population included capturing information regarding sharing, type/brand, container size, and duration, in order to accurately record the amount of alcohol consumed. PAE status was defined for 99.9% of the 11,892 enrolled pregnancies at least once during pregnancy and for 92% across all trimesters. Of 53,823 drinks reported, 98% had all items necessary for standard drink computation. Sharing was reported for 74% of drinks in Cape Town, South Africa and for 10% in the Northern Plains. Compared to referent values from the traditional TLFB, 74% and 67% of drinks had different alcohol-by-volume and container size, respectively. Furthermore, a statistically significant difference was found between the number of containers reported and the number of standard drinks computed, using information from the modified TLFB. This is the first study of this size to wholly encompass all of these changes into a single measure in order to more accurately calculate daily consumption and assess patterns over time. The methods used to collect PAE information and create alcohol exposure measures likely increased the accuracy of standard drinks reported and could be generalized to other populations.

Project description:IntroductionIn smoking cessation clinical trials, timeline followback (TLFB) interviews are widely used to track daily cigarette consumption. However, there are no standard tools for calculating abstinence based on TLFB data. Individual research groups have to develop their own calculation tools, which is not only time- and resource-consuming but might also lead to variability in the data processing and calculation procedures.Aims and methodsTo address these issues, we developed a novel open-source Python package named abstcal to calculate abstinence using TLFB data. This package provides data verification, duplicate and outlier detection, missing-data imputation, integration of biochemical verification data, and calculation of a variety of definitions of abstinence, including continuous, point-prevalence, and prolonged abstinence.ResultsWe verified the accuracy of the calculator using data derived from a clinical smoking cessation study. To improve the package's accessibility, we have made it available as a free web app.ConclusionsThe abstcal package is a reliable abstinence calculator with open-source access, providing a shared validated online tool to the addiction research field. We expect that this open-source abstinence calculation tool will improve the rigor and reproducibility of smoking and addiction research by standardizing TLFB-based abstinence calculation.ImplicationsAbstinence calculation is an essential task in any smoking intervention study. However, there have not been standard open-source tools available to the researchers. This commentary describes a Python-based package called abstcal that can calculate abstinence from TLFB data, a common methodology to collect smoking consumption data in research settings. The package supports the calculation of point-prevalence, prolonged, and continuous abstinence. Importantly, the package has a web app interface that allows researchers to use the tool without any coding experience. This tool will facilitate smoking research by providing a standardized and easy-to-use abstinence calculation tool.

Project description:BackgroundFamily functioning relies on different factors that are related to the individual characteristics of each member, the social context in which the family nucleus is integrated, and the internal and interpersonal family factors. The Short Version of the Family Assessment Measure-III, Dyadic Adjustment Scale, Inventory of Parent and Peer Attachment, Twenty-item Toronto Alexithymia Scale, Hospital Anxiety and Depression Scale, and Multidimensional Scale of Perceived Social Support are among the most commonly employed self-report measures for the assessment of family functioning and related factors. Traditionally, these scales have been administered using paper-and-pencil versions. However, with increased access to the Internet, online administration of questionnaires has become more common. The present study aimed to validate an online version of each of the above-mentioned questionnaires in a heterogeneous sample of Italian healthy individuals.MethodsOne-hundred participants were recruited for each questionnaire. A crossover design was used in each validation. The minimum important difference (MID) was applied to evaluate the differences in the variances of the paper-and-pencil and online format scores. A MID >0.5 is a reasonable first approximation of a threshold of important change. Taking into account the cross over design, mean difference between pencil-and-paper and online versions, and Intraclass Correlation Coefficient were also estimated by mixed models.ResultsThe MID was <0.5 for all the instruments used. Therefore, no significant difference was observed between the score variances of the paper-and-pencil and online formats of all the questionnaires. Moreover, for each questionnaire the difference between the means of online and paper-and-pencil administrations scores (mean O-P) was calculated. We reported 95% confidence intervals that did not include the 0; therefore, mean (O-P) was not statistically significant.ConclusionsThe current findings indicate that the online versions of all the questionnaires we administered can be considered reliable tools for the assessment of family functioning and related factors.

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Validation of a multisubstance online Timeline Followback assessment.

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Validation of a multisubstance online Timeline Followback assessment.

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