Evidence map›Paper›PMID 30748019›Full record

ReviewAlcoholism, clinical and experimental research2019

Assessment of Alcohol Use in the Natural Environment.

Thomas M Piasecki

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Alcoholism, clinical and experimental research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 3 pooled it
9.1field-weighted citation impact, top 2% 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

70 citing papers in PubMed, 3 syntheses or guidelines pooled it, 81 citations in OpenAlex.

  1. Reward Processing in Binge Eating and Harmful Drinking: A Systematic Review.The International journal of eating disorders · 2026
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  18. Common and unique latent transition analysis (CULTA) as a way to examine the trait-state dynamics of alcohol intoxication.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2025
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10 more citing papers are in PubMed but not listed here.

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

1 author at 1 institution in 1 country.

Thomas M PiaseckiDepartment of Psychological Sciences, University of Missouri, Columbia, Missouri.ORCID 0000-0002-2793-2049
University of Missouri · US

Funding

Supplement to Promote Diversity: Characterizing Low Alcohol Sensitivity in Laboratory and Real-World ContextsR01AA025451 · NIAAA · UNIVERSITY OF MISSOURI-COLUMBIA · PI BARTHOLOW, BRUCE D, PIASECKI, THOMAS M · 2018 to 2022
$2.7M
NIAAA NIH HHS R01 AA025451
6 · The paper itself

Abstract

The current article critically reviews 3 methodological options for assessing drinking episodes in the natural environment. Ecological momentary assessment (EMA) typically involves using mobile devices to collect self-report data from participants in daily life. This technique is now widely used in alcohol research, but investigators have implemented diverse assessment strategies. This article focuses on "high-resolution" EMA protocols that oversample experiences and behaviors within individual drinking episodes. A number of approaches have been used to accomplish this, including using signaled follow-ups tied to drinking initiation, asking participants to log entries before and after individual drinks or drinking episodes, and delivering frequent signaled assessments during periods of the day when alcohol use is most common. Transdermal alcohol sensors (TAS) are devices that are worn continuously and are capable of detecting alcohol eliminated through the skin. These methods are appealing because they do not rely upon drinkers' self-report. Studies using TAS have been appearing with greater frequency over the past several years. New methods are making the use of TAS more tractable by permitting back-translation of transdermal alcohol concentration data to more familiar estimates of blood alcohol concentration or breath alcohol concentration. However, the current generation of devices can have problems with missing data and tend to be relatively insensitive to low-level drinking. An emerging area of research investigates the possibility of using mobile device data and machine learning to passively detect the user's drinking, with promising early findings. EMA, TAS, and sensor-based approaches are all valid, and tend to produce convergent information when used in conjunction with one another. Each has a unique profile of advantages, disadvantages, and threats to validity. Therefore, the nature of the underlying research question must dictate the method(s) investigators select.

Indexed as

Ecological Momentary AssessmentWearable Electronic DevicesAlcohol DrinkingBlood Alcohol ContentBreath TestsHumansMonitoring, AmbulatoryBlood Alcohol ContentEcological Momentary AssessmentMachine LearningTransdermal Alcohol Sensor

Identifiers

PMID30748019
PMCPMC6443469
OpenAlexW2911623403

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.