Processing transdermal alcohol concentration (TAC) data to detect low-level drinking

Roache, John D.; Karns-Wright, Tara E.; Goros, Martin; Hill‐Kapturczak, Nathalie; Mathias, Charles W.; Dougherty, Donald M.

doi:10.1016/j.alcohol.2018.08.014

Cited by 33 publications

(56 citation statements)

References 22 publications

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“…Abbreviations within the table are as follows: (e)BrAC, (estimated) breath alcohol concentration; SD, standard deviation; TAC, transdermal alcohol concentration; time, time of peak in hours. the SCRAM) or criteria as developed by researchers themselves (Roache et al, 2019). Roache and colleagues (2015) investigated the sensitivity of 2 versions of the SCRAM (SCRAMII and SCRAMx) in detecting low-level drinking when using different thresholds: (i) TAC > 0.00 g/dl, (ii) TAC > 0.02 g/dl, and (iii) TAC > 0.03 g/dl (Table 7).…”

Section: Studies Using Scrammentioning

confidence: 99%

“…These criteria are necessarily conservative due to their use in the justice system and the legal implications associated with false positives. Further, the TAC data often show unnatural spikes that are likely caused by environmental noise, which require careful and considerate processing to ensure that we are reviewing alcohol consumption and not environmental noise (Roache et al, 2019). This is especially true of the SCRAM which only samples every 30 minutes, making it difficult to conclude whether a spike is environmental noise, a result of sudden temperature or humidity change, or movement for example.…”

Section: Processing Of Tac Data Including Criteria and Thresholds Usmentioning

confidence: 99%

“…Previous studies have used either self‐report or BrAC as a reference measure to designate true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN). The positive or negative readings are identified by either the criteria as developed by AMS (manufacturers of the SCRAM) or adjusted criteria (Roache et al, 2019). Raw TAC data often show unnatural spikes that are likely caused by environmental noise such as alcohol in the carpet or spilling of drinks.…”

Section: Tac Monitorsmentioning

confidence: 99%

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Wearable Transdermal Alcohol Monitors: A Systematic Review of Detection Validity, and Relationship Between Transdermal and Breath Alcohol Concentration and Influencing Factors

Egmond

Wright

Livingston

et al. 2020

Alcoholism Clin & Exp Res

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Background: Research on alcohol consumption mostly relies on self-reported data, which are subject to recall bias. Wearable transdermal alcohol concentration (TAC) monitors address this limitation by continuously measuring the ethanol excreted via the skin. This systematic review aims to provide an overview of TAC monitors' reliability to detect alcohol consumption and methods to estimate breath alcohol concentration (BrAC) and number of standard drinks consumed in a given time frame. Methods: The databases MEDLINE, PsycINFO, SCOPUS, Engineering Village, and CINAHL were systematically searched to identify 1,048 empirical research papers published from 2013 onwards, of which 13 were included after full-text screening. The selected studies included 3 TAC monitors: SCRAM TM , WristTAS TM , and Skyn TM. Results: TAC measures of SCRAM, WrisTAS, and Skyn are found to be positively correlated with BrAC (r = 0.56 to 0.79) and/or self-reports (r = 0.62). Using the AMS criteria for detection results in low sensitivity, adjusted criteria can increase the sensitivity of the SCRAM from 39.9 to 68.5%. The WrisTAS and an early prototype of the Skyn showed high failure rates (17 to 38%). Recent advances toward transforming the TAC data into more clinically relevant measures have led to the development of mathematical models and the BrAC Estimator Software. Using TAC data, both approaches produce estimates explaining 70 to 82% of actual BrAC and self-reported drinking or to highly correlate with the actual BrAC measures (b = 0.90 to 0.91). Conclusions: Transdermal alcohol monitors offer an opportunity to measure alcohol consumption in a valid and continuous way with mathematical models and software estimating BrAC values improving interpretation of TAC data. However, the SCRAM seems unable to detect low-to-moderate drinking levels using the thresholds and criteria set by the manufacturer. Moreover, the WrisTAS and the Skyn prototype show a high failure rate, raising questions about reliability. Future studies will assess the validity of new-generation wristbands, including the next Skyn generations.

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Section: Studies Using Scrammentioning

confidence: 99%

Section: Processing Of Tac Data Including Criteria and Thresholds Usmentioning

confidence: 99%

Section: Tac Monitorsmentioning

confidence: 99%

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Wearable Transdermal Alcohol Monitors: A Systematic Review of Detection Validity, and Relationship Between Transdermal and Breath Alcohol Concentration and Influencing Factors

Egmond

Wright

Livingston

et al. 2020

Alcoholism Clin & Exp Res

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“…This results in many false negatives when compared to self‐report of drinking in community samples, particularly for light drinking episodes (Barnett et al., ; Dougherty et al., ). Accordingly, researchers have begun to develop and evaluate more liberal criteria sets to more completely capture drinking events in basic research (Barnett et al., ; Roache et al., ) and tools for processing and interpreting SCRAM data (Barnett et al., ). Investigations using WrisTAS have employed varying approaches, including a mathematical filtering scheme (Rosen et al., ) and differing thresholds on peak TAC (Marques and McKnight, ; Simons et al., ) to identify drinking events.…”

Section: Transdermal Alcohol Sensorsmentioning

confidence: 99%

“…Studies applying varying episode detection rules to SCRAM data have reported correctly identifying between 39.9 and 87.7% of drinking events observed in the laboratory or reported by drinkers in the field (Barnett et al., , ; Karns‐Wright et al., ; Marques and McKnight, ; Neville et al., ; Roache et al., ). Drinking events undetected by SCRAM tend to be those involving lower levels of consumption (e.g., 1 to 4 drinks; Barnett et al., ; Karns‐Wright et al., ; Roache et al., , ). In studies using WrisTAS, TAC data have detected between 23.6 and 85.6% of drinking events identified by other means (Bond et al., ; Marques and McKnight, ; Simons et al., ).…”

Section: Transdermal Alcohol Sensorsmentioning

confidence: 99%

Assessment of Alcohol Use in the Natural Environment

Piasecki

2019

Alcoholism Clin & Exp Res

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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.

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To Drink or Not to Drink: Is That the Question? Examining Correspondence and Predictive Validity of Morning Drinking Intentions for Young Adults’ Drinking Behaviors and Consequences

Courtney

Russell

2022

Prev Sci

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Objective: The Theory of Planned Behavior suggest that intentions are significant and proximal determinants of behavior. The purpose of this study was to test the predictive validity of drinking intentions for subsequent same-day drinking behaviors and negative consequences.Methods: 222 regularly drinking young adults (21-29 years, 84% undergraduates) completed an ecological momentary assessment (EMA) protocol and wore an alcohol monitor for five consecutive 24-hour periods spanning six days (Wednesday-Monday). Each morning, participants reported their drinking intentions for the day and their previous day's alcohol consumption and number of negative drinking consequences.Results: Multilevel models showed that, at the within-person level, on days when people reported intending to drink, to get drunk, or to drink more than usual they had higher odds of drinking, consumed more drinks, and had higher peak transdermal alcohol concentrations later that day. However, drinking occurred on 28% of days without drinking intentions, suggesting intentions were an imperfect signal for future drinking behavior. Morning drinking intentions also predicted experiencing more negative consequences, even after controlling for alcohol consumption. Conclusions:On average, young adults' morning-reported drinking-related intentions predicted increased odds of same-day drinking behavior and alcohol-related consequences. However, drinking frequently occurred on days participants did not intend to drink, suggesting that focusing only on drinking intention days will result in many missed prevention opportunities. Together, these results suggest the need for additional research to increase the predictive value of drinking intention assessments and for prevention interventions aimed at helping individuals follow-through on their intentions not to drink.

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Processing transdermal alcohol concentration (TAC) data to detect low-level drinking

Cited by 33 publications

References 22 publications

Wearable Transdermal Alcohol Monitors: A Systematic Review of Detection Validity, and Relationship Between Transdermal and Breath Alcohol Concentration and Influencing Factors

Wearable Transdermal Alcohol Monitors: A Systematic Review of Detection Validity, and Relationship Between Transdermal and Breath Alcohol Concentration and Influencing Factors

Assessment of Alcohol Use in the Natural Environment

To Drink or Not to Drink: Is That the Question? Examining Correspondence and Predictive Validity of Morning Drinking Intentions for Young Adults’ Drinking Behaviors and Consequences

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