Using alcohol biosensors and biomarkers to measure changes in drinking: Associations between transdermal alcohol concentration, phosphatidylethanol, and self-report in a contingency management study of persons with and without HIV.

Veronica L Richards, Yan Wang, Eric C Porges, Joseph M Gullett, Robert F Leeman, Zhi Zhou, Nancy P Barnett, Robert L Cook
Author Information
  1. Veronica L Richards: Department of Epidemiology, University of Florida. ORCID
  2. Yan Wang: Department of Epidemiology, University of Florida.
  3. Eric C Porges: Center for Cognitive Aging and Memory, University of Florida.
  4. Joseph M Gullett: Center for Cognitive Aging and Memory, University of Florida. ORCID
  5. Robert F Leeman: Department of Health Sciences, Bouve College of Health Sciences, Northeastern University.
  6. Zhi Zhou: Department of Epidemiology, University of Florida.
  7. Nancy P Barnett: Department of Behavioral and Social Sciences, Brown University School of Public Health.
  8. Robert L Cook: Department of Epidemiology, University of Florida.

Abstract

alcohol use can be measured in many ways, including objectively through transdermal alcohol biosensors (e.g., transdermal alcohol concentration; TAC) or blood biomarkers (e.g., phosphatidylethanol; PEth), or subjectively through self-report (e.g., with the timeline followback; TLFB). However, it is unclear which measures best indicate changes in alcohol use within individuals following intervention, and if they have concurrent validity. In the context of contingency management (CM) with a goal of 30-day abstinence ( = 45, 60% male, 80% Black; = 56.7; 58% with HIV), we examined relationships among changes in TAC-AUC (area under the curve, reflecting volume consumed), PEth, and self-reported number of drinks. The Secure Continuous Remote alcohol Monitor Continuous alcohol Monitoring (SCRAM-CAM) biosensor was used to collect TAC-AUC during a pre-CM period (���7 days) and over a 30-day CM period. PEth was collected at baseline and 30-day follow-up. Number of drinks was self-reported through a 30-day TLFB at baseline and follow-up. Daily TAC-AUC and number of self-reported drinks were calculated for the pre-CM period and for the last 7 days of the CM period. Linear regression models controlling for baseline values revealed that change in TAC-AUC was significantly associated with change in PEth (�� = 0.33, < .0001) and with change in number of self-reported drinks (�� = 0.34, < .0001). Change in PEth was significantly associated with change in number of self-reported drinks (�� = 0.85, < .0001). We conclude that all three measures may be appropriate for measuring within-person change in alcohol use, while controlling for baseline values, in the context of a study testing an intervention such as CM. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Associated Data

ClinicalTrials.gov | NCT03353701

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Grants

  1. U01 AA020797/NIAAA NIH HHS
  2. T32 AA025877/NIAAA NIH HHS
  3. UH3 AA026214/NIAAA NIH HHS
  4. T32 DA017629/NIDA NIH HHS
  5. P01 AA029543/NIAAA NIH HHS
  6. /NIAAA NIH HHS
  7. /NIDA NIH HHS

MeSH Term

Humans
Male
Middle Aged
Female
Self Report
Alcohol Drinking
Ethanol
Biomarkers
HIV Infections

Chemicals

phosphatidylethanol
Ethanol
Biomarkers

Word Cloud

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