Evidence map›Paper›PMID 34998252›Full record

ArticleDrug and alcohol dependence2022

A virtual reality platform for the measurement of drinking topography.

Victor J Schneider, Nicholas Bush, Darya Vitus, Ryan W Carpenter, Michael Robinson, Jeff Boissoneault

Open access · hybridAbstract read
In one paragraph

Article in Drug and alcohol dependence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.3field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Pain and alcohol consumption in virtual reality.Experimental and clinical psychopharmacology · 2023
    Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Victor J SchneiderCenter for Pain Research and Behavioral Health, University of Florida, Gainesville, FL 32610, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL 32610, USA.
Nicholas BushCenter for Pain Research and Behavioral Health, University of Florida, Gainesville, FL 32610, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL 32610, USA.
Darya VitusCenter for Pain Research and Behavioral Health, University of Florida, Gainesville, FL 32610, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL 32610, USA.
Ryan W CarpenterDepartment of Psychology, University of Missouri-St. Louis, St. Louis, MO 63121, USA.
Michael RobinsonCenter for Pain Research and Behavioral Health, University of Florida, Gainesville, FL 32610, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL 32610, USA.
Jeff BoissoneaultCenter for Pain Research and Behavioral Health, University of Florida, Gainesville, FL 32610, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL 32610, USA. Electronic address: jboissoneault@phhp.ufl.edu.
University of Florida Health · USUniversity of Florida · USUniversity of Missouri–St. Louis · US

Funding

Translational Science Training to Reduce the Impact of Alcohol on HIV InfectionT32AA025877 · NIAAA · UNIVERSITY OF FLORIDA · PI Robert L Cook, DEBRA E LYON · 2018 to 2026
$3.3M
NIAAA NIH HHS T32 AA025877
6 · The paper itself

Abstract

backgroundThe assessment of alcohol consumption during a drinking bout, known as drinking topography, may help improve understanding of biopsychosocial mechanisms underlying alcohol consumption. However, past studies have been limited by effort-intensive, time-consuming, and error-prone processes involved in collecting, organizing, and standardizing drinking topography data. Recent technologies allowing integrated data collection and greater environmental control, such as virtual reality (VR), could resolve these problems.

methodsIn this pilot project, we assessed alcohol consumption topography of participants in a VR drinking environment with a programmable virtual confederate (i.e., bar goer) during two testing sessions. In one, the confederate drank quickly (30-60 s sip interval). In the other, the confederate drank slowly (60-120 s sip interval). Participants' hands and beverage were represented in VR. Between sips, beverages were placed on a Bluetooth-enabled scale, allowing real-time updates of drink weight. Participant experience was assessed after each testing visit. Multilevel modeling was used to characterize the effect of confederation condition on sip interval and sip volume. Descriptive analyses were used for participant experience data.

resultsResults showed significant, moderate-to-strong between-visit correlations for topographic measures (r = 0.50 to r = 0.84) and indicate participants found the experience to be comfortable and acceptable. Multilevel models indicated participants had greater sip volumes and lower sip intervals when the confederate drank quickly.

conclusionsFuture studies should take advantage of the considerable translational value of this technology to improve understanding of risk associated with individual drinking bouts and develop novel interventions for reducing hazardous drinking.

Indexed as

Virtual RealityAlcohol DrinkingHumansPilot ProjectsAlcoholDrinking topographySimulated barVirtual reality

Identifiers

PMID34998252
PMCPMC9358601
OpenAlexW4205609376

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.