Alcohol Use Disorder in the Age of Technology: A Review of Wearable Biosensors in Alcohol Use Disorder Treatment

Experimentally Induced Reductions in Alcohol Consumption and Brain, Cognitive, and Clinical Outcomes in Older Persons With and Those Without HIV Infection (30-Day Challenge Study): Protocol for a Nonrandomized Clinical Trial

BACKGROUND

Both alcohol consumption and HIV infection are associated with worse brain, cognitive, and clinical outcomes in older adults. However, the extent to which brain and cognitive dysfunction is reversible with reduction or cessation of drinking is unknown.

OBJECTIVE

The 30-Day Challenge study was designed to determine whether reduction or cessation of drinking would be associated with improvements in cognition, reduction of systemic and brain inflammation, and improvement in HIV-related outcomes in adults with heavy drinking.

METHODS

The study design was a mechanistic experimental trial, in which all participants received an alcohol reduction intervention followed by repeated assessments of behavioral and clinical outcomes. Persons were eligible if they were 45 years of age or older, had weekly alcohol consumption of 21 or more drinks (men) or 14 or more drinks (women), and were not at high risk of alcohol withdrawal. After a baseline assessment, participants received an intervention consisting of contingency management (money for nondrinking days) for at least 30 days followed by a brief motivational interview. After this, participants could either resume drinking or not. Study questionnaires, neurocognitive assessments, neuroimaging, and blood, urine, and stool samples were collected at baseline, 30 days, 90 days, and 1 year after enrollment.

RESULTS

We enrolled 57 persons with heavy drinking who initiated the contingency management protocol (mean age 56 years, SD 4.6 years; 63%, n=36 male, 77%, n=44 Black, and 58%, n=33 people with HIV) of whom 50 completed 30-day follow-up and 43 the 90-day follow-up. The planned study procedures were interrupted and modified due to the COVID-19 pandemic of 2020-2021.

CONCLUSIONS

This was the first study seeking to assess changes in brain (neuroimaging) and cognition after alcohol intervention in nontreatment-seeking people with HIV together with people without HIV as controls. Study design strengths, limitations, and lessons for future study design considerations are discussed. Planned analyses are in progress, after which deidentified study data will be available for sharing.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03353701; https://clinicaltrials.gov/study/NCT03353701.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/53684.

Signal processing and machine learning with transdermal alcohol concentration to predict natural environment alcohol consumption

Wrist-worn alcohol biosensors continuously and discreetly record transdermal alcohol concentration (TAC) and may allow alcohol researchers to monitor alcohol consumption in participants' natural environments. However, the field lacks established methods for signal processing and detecting alcohol events using these devices. We developed software that streamlines analysis of raw data (TAC, temperature, and motion) from a wrist-worn alcohol biosensor (BACtrack Skyn) through a signal processing and machine learning pipeline: biologically implausible skin surface temperature readings (< 28°C) were screened for potential device removal and TAC artifacts were corrected, features that describe TAC (e.g., rise duration) were calculated and used to train models (random forest and logistic regression) that predict self-reported alcohol consumption, and model performances were measured and summarized in autogenerated reports. The software was tested using 60 Skyn data sets recorded during 30 alcohol drinking episodes and 30 nonalcohol drinking episodes. Participants (N = 36; 13 with alcohol use disorder) wore the Skyn during one alcohol drinking episode and one nonalcohol drinking episode in their natural environment. In terms of distinguishing alcohol from nonalcohol drinking, correcting artifacts in the data resulted in 10% improvement in model accuracy relative to using raw data. Random forest and logistic regression models were both accurate, correctly predicting 97% (58/60; AUC-ROCs = 0.98, 0.96) of episodes. Area under TAC curve, rise duration of TAC curve, and peak TAC were the most important features for predictive accuracy. With promising model performance, this protocol will enhance the efficiency and reliability of TAC sensors for future alcohol monitoring research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Gender differences in changes in alcohol consumption achieved by free provision of non-alcoholic beverages: a secondary analysis of a randomized controlled trial

BACKGROUND

We recently demonstrated that a 12-week intervention consisting of the provision of free non-alcoholic beverages reduced alcohol consumption in excessive drinkers for 8 weeks after the intervention. However, gender differences in this effect were not explored. Thus, this secondary analysis investigated gender differences in the influence of non-alcoholic beverage provision on alcohol consumption.

METHODS

Individuals who frequently drank excessively (at least 40 g/day in men and 20 g/day in women) and who were not diagnosed with alcoholism were recruited. Participants were randomized into the intervention or control group by simple randomization using a random number table. In the intervention group, free non-alcoholic beverages were provided once every 4 weeks for 12 weeks (three times in total). The consumption of alcoholic and non-alcoholic beverages was calculated based on a drinking diary submitted with the previous 4 weeks' of data. In this study, we compared the longitudinal changes in alcohol consumption between genders in both groups.

RESULTS

The provision of non-alcoholic beverages significantly reduced alcohol consumption in both genders; however, significant differences in alcohol consumption between the control and intervention groups were observed only in men. The average alcohol consumption during the intervention fell below the level associated with a high risk of non-communicable diseases in men (32.7 g/day), but not in women (24.8 g/day). Correlation coefficient analysis showed that replacing alcoholic beverages with the provided non-alcoholic beverages resulted in different drinking patterns according to gender. The percent changes in the consumption of alcoholic and non-alcoholic beverages relative to baseline levels did not differ between genders.

CONCLUSIONS

Our results suggest that the provision of non-alcoholic beverages reduced alcohol consumption irrespective of gender. Of note, providing non-alcoholic beverages might be particularly useful for reducing high-risk alcohol consumption in male excessive drinkers.

TRIAL REGISTRATION

UMIN UMIN000047949. Registered 4 June 2022.

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

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 (n = 45, 60% male, 80% Black; Mage = 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 (β = 0.33, p < .0001) and with change in number of self-reported drinks (β = 0.34, p < .0001). Change in PEth was significantly associated with change in number of self-reported drinks (β = 0.85, p < .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).

Feasibility of a remotely monitored blood alcohol concentration device to facilitate treatment motivation

Background

Consistent monitoring of blood alcohol concentration through breathalyzers is critical for identifying reoccurrence. Little research has effectively utilized convenient wireless enabled breathalyzers that can measure blood alcohol concentration while enhancing treatment motivation for outpatient care. The current study attempted to understand the impact of wireless breathalyzers on treatment motivation and self-efficacy in remaining sober for individuals diagnosed with alcohol use disorder in an outpatient treatment facility.

Methods

Participants were assigned to one of two conditions: the experimental breathalyzer and the treatment as usual group. The groups were assessed by the University of Rhode Island Change Assessment (URICA), and on self-efficacy, measured by the Alcohol Abstinence Self-Efficacy Scale (AASE). The evaluation period took place over three months with a six-week follow-up evaluation. During the entirety of the evaluation period and post-study follow up, interviews occurred.

Results

As a secondary analysis, the URICA's motivational scores were higher for participants receiving the experimental intervention at a two-month evaluation and at the six-week follow-up. The AASE's temptation to reoccurrence scores significantly reduced over time for both groups. The confidence to resist temptation was not significant. Three major themes emerged from the interviews, including the benefit of the breathalyzer facilitating their treatment, ease of device use, and technical issues.

Conclusions

The insights gained from this study will be important to develop cost-effective ancillary interventions for comprehensive alcohol dependence treatment. On-going monitoring enabled by new technology allows treatment providers to take an individualized disease-management approach as well as facilitating timely interventions by the treatment provider.

Neurobiology and the Treatment of Alcohol Use Disorder: A Review of the Evidence Base

Alcohol use disorder (AUD) is a significant public health concern, accounting for a majority of substance use disorder cases in the United States. Treatment for AUD is complex, with multiple intervention points that may be further complicated by genotype and phenotype, resulting in diverse outcomes. In order to better understand the current landscape of AUD treatment, the present review considers different etiological models of AUD and assesses the evidence base of current treatment options. The first section of this review summarizes various etiological models of AUD and presents different approaches to classifying the disorder. Various theories, including neurobiological models, are discussed. The second section presents a comprehensive analysis of available treatment options for AUD, encompassing behavioral and pharmacological interventions and their current evidence base. Finally, this review discusses the ongoing treatment gap and significant factors contributing to low treatment utilization. Together, this review provides an overview of different etiological processes and mechanisms of AUD, as well as summarizes the literature on key treatment approaches. By integrating historical, theoretical, and empirical data, this review aims to inform both researchers and providers with valuable insights to advance AUD treatment approaches and narrow the treatment gap.

An Update on the Use of Wearable Devices in Men's Health

Men's health represents an often-overlooked aspect of public health. Men have higher mortality rates worldwide and are more negatively affected by chronic conditions such as obesity and heart disease, as well as addiction to alcohol and tobacco. Men also have health issues such as prostate cancer and male sexual dysfunction which only affect them. Because of the skewed burden of morbidity and mortality on men, it is imperative from a public health perspective to make a concerted effort to specifically improve men's health. The use of wearable devices in medical practice presents a novel avenue to invest in men's health in a safe, easily scalable, and economic fashion. Wearable devices are now ubiquitous in society, and their use in the healthcare setting is only increasing with time. There are commercially available devices such as smart watches which are available to lay people and healthcare professionals alike to improve overall health and wellness, and there are also purpose-built wearable devices which are used to track or treat a specific disease. In our review of the literature, we found that while research in the field of wearable devices is still in its early stages, there is ample evidence that wearable devices can greatly improve men's health in the long-term.

How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial

BACKGROUND

Drink Less is a behavior change app to help higher-risk drinkers in the United Kingdom reduce their alcohol consumption. The app includes a daily notification asking users to "Please complete your drinks and mood diary," yet we did not understand the causal effect of the notification on engagement nor how to improve this component of Drink Less. We developed a new bank of 30 new messages to increase users' reflective motivation to engage with Drink Less. This study aimed to determine how standard and new notifications affect engagement.

OBJECTIVE

Our objective was to estimate the causal effect of the notification on near-term engagement, to explore whether this effect changed over time, and to create an evidence base to further inform the optimization of the notification policy.

METHODS

We conducted a micro-randomized trial (MRT) with 2 additional parallel arms. Inclusion criteria were Drink Less users who consented to participate in the trial, self-reported a baseline Alcohol Use Disorders Identification Test score of ≥8, resided in the United Kingdom, were aged ≥18 years, and reported interest in drinking less alcohol. Our MRT randomized 350 new users to test whether receiving a notification, compared with receiving no notification, increased the probability of opening the app in the subsequent hour, over the first 30 days since downloading Drink Less. Each day at 8 PM, users were randomized with a 30% probability of receiving the standard message, a 30% probability of receiving a new message, or a 40% probability of receiving no message. We additionally explored time to disengagement, with the allocation of 60% of eligible users randomized to the MRT (n=350) and 40% of eligible users randomized in equal number to the 2 parallel arms, either receiving the no notification policy (n=98) or the standard notification policy (n=121). Ancillary analyses explored effect moderation by recent states of habituation and engagement.

RESULTS

Receiving a notification, compared with not receiving a notification, increased the probability of opening the app in the next hour by 3.5-fold (95% CI 2.91-4.25). Both types of messages were similarly effective. The effect of the notification did not change significantly over time. A user being in a state of already engaged lowered the new notification effect by 0.80 (95% CI 0.55-1.16), although not significantly. Across the 3 arms, time to disengagement was not significantly different.

CONCLUSIONS

We found a strong near-term effect of engagement on the notification, but no overall difference in time to disengagement between users receiving the standard fixed notification, no notification at all, or the random sequence of notifications within the MRT. The strong near-term effect of the notification presents an opportunity to target notifications to increase "in-the-moment" engagement. Further optimization is required to improve the long-term engagement.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/18690.

Resting state connectivity in people living with HIV before and after stopping heavy drinking

Background

Heavy alcohol use in people living with HIV (PLWH) has widespread negative effects on neural functioning. It remains unclear whether experimentally-induced reduction in alcohol use could reverse these effects. We sought to determine the effects of 30-days drinking cessation/reduction on resting state functional connectivity in people with and without HIV.

Methods

Thirty-five participants (48.6% PLWH) demonstrating heavy alcohol use attempted to stop drinking for 30 days via contingency management (CM). MRI was acquired at baseline and after thirty days, and functional connectivity across five resting-state fMRI (rsfMRI) networks was calculated with the Conn toolbox for Matlab and examined in relation to transdermal alcohol concentration (TAC) recorded by the ankle-worn secure continuous remote alcohol monitor (SCRAM) and self-reported alcohol use (timeline follow-back; TLFB). Associations between alcohol use and reduction, HIV status, functional connectivity, and change in functional connectivity across five major rsfMRI networks were determined relative to the pre- and post-CM timepoints.

Results

Baseline resting-state functional connectivity was not significantly associated with average TAC-AUC during the pre-CM period, though higher self-reported alcohol use over the preceding 30 days was significantly associated with higher baseline connectivity within the Dorsal Attention Network (DAN; p-FDR < 0.05). Baseline connectivity within the Salience network was significantly negatively related to objective drinking reduction after intervention (DAN; p-FDR < 0.05), whereas baseline connectivity within the Limbic network was positively associated with self-reported drinking reduction (p-FDR < 0.05). Change in between-networks functional connectivity after intervention was significantly positively associated with biosensor-confirmed drinking reduction such that higher reduction was associated with stronger connectivity between the limbic and fronto-parietal control networks (p-FDR < 0.05). PLWH with lower DAN connectivity at baseline demonstrated poorer alcohol reduction than those with higher DAN connectivity at baseline.

Discussion

Lower resting-state functional connectivity of the Salience network significantly predicted stronger drinking reduction across all participants, suggesting a potential biomarker for reduced susceptibility to the environmental and social cues that often make alcohol use reduction attempts unsuccessful. Increased between-networks connectivity was observed in participants with higher alcohol reduction after CM, suggesting a positive benefit to brain connectivity associated with reduced drinking. PLWH with lower baseline DAN connectivity may not benefit as greatly from CM for alcohol reduction.

Exploring the use of Granger causality for the identification of chemical exposure based on physiological data

Wearable sensors offer new opportunities for the early detection and identification of toxic chemicals in situations where medical evaluation is not immediately possible. We previously found that continuously recorded physiology in guinea pigs can be used for early detection of exposure to an opioid (fentanyl) or a nerve agent (VX), as well as for differentiating between the two. Here, we investigated how exposure to these different chemicals affects the interactions between ECG and respiration parameters as determined by Granger causality (GC). Features reflecting such interactions may provide additional information and improve models differentiating between chemical agents. Traditional respiration and ECG features, as well as GC features, were extracted from data of 120 guinea pigs exposed to VX (n = 61) or fentanyl (n = 59). Data were divided in a training set (n = 99) and a test set (n = 21). Minimum Redundancy Maximum Relevance (mRMR) and Support Vector Machine (SVM) algorithms were used to, respectively, perform feature selection and train a model to discriminate between the two chemicals. We found that ECG and respiration parameters are Granger-related under healthy conditions, and that exposure to fentanyl and VX affected these relationships in different ways. SVM models discriminated between chemicals with accuracy of 95% or higher on the test set. GC features did not improve the classification compared to traditional features. Respiration features (i.e., peak inspiratory and expiratory flow) were the most important to discriminate between different chemical’s exposure. Our results indicate that it may be feasible to discriminate between chemical exposure when using traditional physiological respiration features from wearable sensors. Future research will examine whether GC features can contribute to robust detection and differentiation between chemicals when considering other factors, such as generalizing results across species.

The Impact of Acetic Acid on Measuring Ethanol Concentrations in Water and Human Serum Using Short-Wave Infrared Spectroscopy

Ethanol intoxication, although an elemental part of life in many places around the world, still presents several issues associated with excessive consumption. These issues range from drunk driving, violence, and antisocial behavior to self-harm, all exerting an increased cost on the society. Monitoring of intoxication levels can help to limit the impact of these issues by preventing the use of automobiles or heavy machinery and personal monitoring. Previous works on noninvasive measurement of ethanol tissue concentration for estimation of blood alcohol concentration (BAC) performed worst during the first hour of intoxication. Gas chromatography research of intoxication shows that levels of acetic acid rise together at a similar rate as those of ethanol after initial imbibement. In this research, short-wave infrared (SWIR) spectroscopy was utilized with the aim of establishing the interaction between ethanol and acetic acid in water and serum mixtures. The most consistent and clear correlation between ethanol and acetic acid was recorded at 2262 and 2302 nm wavelengths. Partial least-squares (PLS) analysis indicates that the most effective region for consideration in measurement of ethanol is the therapeutic window four (IV) due to high variance in vibration of carbon bonds. The behavior of spectra at different concentration ranges was examined and described in detail in relation to the consequence of alcohol measurement. The investigation concluded that ethanol shows distinctive regions of absorbance at wavelengths of 2262 and 2302 nm, with variations arising from increasing concentrations of acetic acid, whilst also showing that therapeutic window four is amongst the most influential regions of the spectrum for SWIR.

Wearable Sensor and Mobile App-based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study (Preprint)

BACKGROUND

Digital health technologies using mobile apps and wearable devices are a promising approach to the investigation of substance use in the real world and for the analysis of predictive factors or harms from substance use. Moreover, consecutive repeated data collection enables the development of predictive algorithms for substance use by machine learning methods.

OBJECTIVE

We developed a new self-monitoring mobile app to record daily substance use, triggers, and cravings. Additionally, a wearable activity tracker (Fitbit) was used to collect objective biological and behavioral data before, during, and after substance use. This study aims to describe a model using machine learning methods to determine substance use.

METHODS

This study is an ongoing observational study using a Fitbit and a self-monitoring app. Participants of this study were people with health risks due to alcohol or methamphetamine use. They were required to record their daily substance use and related factors on the self-monitoring app and to always wear a Fitbit for 8 weeks, which collected the following data: (1) heart rate per minute, (2) sleep duration per day, (3) sleep stages per day, (4) the number of steps per day, and (5) the amount of physical activity per day. Fitbit data will first be visualized for data analysis to confirm typical Fitbit data patterns for individual users. Next, machine learning and statistical analysis methods will be performed to create a detection model for substance use based on the combined Fitbit and self-monitoring data. The model will be tested based on 5-fold cross-validation, and further preprocessing and machine learning methods will be conducted based on the preliminary results. The usability and feasibility of this approach will also be evaluated.

RESULTS

Enrollment for the trial began in September 2020, and the data collection finished in April 2021. In total, 13 people with methamphetamine use disorder and 36 with alcohol problems participated in this study. The severity of methamphetamine or alcohol use disorder assessed by the Drug Abuse Screening Test-10 or the Alcohol Use Disorders Identification Test-10 was moderate to severe. The anticipated results of this study include understanding the physiological and behavioral data before, during, and after alcohol or methamphetamine use and identifying individual patterns of behavior.

CONCLUSIONS

Real-time data on daily life among people with substance use problems were collected in this study. This new approach to data collection might be helpful because of its high confidentiality and convenience. The findings of this study will provide data to support the development of interventions to reduce alcohol and methamphetamine use and associated negative consequences.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/44275.

Validating transdermal alcohol biosensors: a meta-analysis of associations between blood/breath-based measures and transdermal alcohol sensor output

BACKGROUND AND AIMS

Transdermal alcohol sensors carry immense promise for the continuous assessment of drinking but are inconsistent in detecting more fine-grained indicators of alcohol consumption. Prior studies examining associations between transdermal alcohol concentration (TAC) and blood/breath alcohol concentration (BAC) have yielded highly variable correlations and lag times. The current review aimed to synthesize transdermal validation studies, aggregating results from more than three decades of research to characterize the validity of transdermal sensors for assessing alcohol consumption.

METHODS

Databases were searched for studies listed prior to 1 March 2022 that examined associations between transdermal alcohol sensor output and blood and breath-based alcohol measures, resulting in 31 primarily laboratory-derived participant samples (27 precise effect sizes) including both healthy and clinical populations. Correlation coefficients and lag times were pooled using three-level random-effects meta-regression. Independent raters coded study characteristics, including the body position of transdermal sensors (ankle- versus arm/hand/wrist-worn device) and methodological bias (e.g. missing data).

RESULTS

Analyses revealed that, in this primarily laboratory-derived sample of studies, the average correlation between TAC and BAC was large in magnitude [r = 0.87, 95% confidence interval (CI) = 0.80, 0.93], and TAC lagged behind BAC by an average of 95.90 minutes (95% CI = 55.50, 136.29). Device body position significantly moderated both TAC-BAC correlation (b = 0.11, P = 0.009) and lag time (b = -69.41, P < 0.001). Lag times for ankle-worn devices were approximately double those for arm/hand/wrist-worn devices, and TAC-BAC correlations also tended to be stronger for arm/hand/wrist-worn sensors.

CONCLUSIONS

This meta-analysis indicates that transdermal alcohol sensors perform strongly in assessing blood/breath alcohol concentration under controlled conditions, with particular promise for the newer generation of wrist-worn devices.

Systematic review: Wearable remote monitoring to detect nonalcohol/nonnicotine-related substance use disorder symptoms

BACKGROUND AND OBJECTIVES

Substance use disorders (SUDs) are chronic relapsing diseases characterized by significant morbidity and mortality. Phenomenologically, patients with SUDs present with a repeating cycle of intoxication, withdrawal, and craving, significantly impacting their diagnosis and treatment. There is a need for better identification and monitoring of these disease states. Remote monitoring chronic illness with wearable devices offers a passive, unobtrusive, constant physiological data assessment. We evaluate the current evidence base for remote monitoring of nonalcohol, nonnicotine SUDs.

METHODS

We performed a systematic, comprehensive literature review and screened 1942 papers.

RESULTS

We found 15 studies that focused mainly on the intoxication stage of SUD. These studies used wearable sensors measuring several physiological parameters (ECG, HR, O2 , Accelerometer, EDA, temperature) and implemented study-specific algorithms to evaluate the data.

DISCUSSION AND CONCLUSIONS

Studies were extracted, organized, and analyzed based on the three SUD disease states. The sample sizes were relatively small, focused primarily on the intoxication stage, had low monitoring compliance, and required significant computational power preventing "real-time" results. Cardiovascular data was the most consistently valuable data in the predictive algorithms. This review demonstrates that there is currently insufficient evidence to support remote monitoring of SUDs through wearable devices.

SCIENTIFIC SIGNIFICANCE

This is the first systematic review to show the available data on wearable remote monitoring of SUD symptoms in each stage of the disease cycle. This clinically relevant approach demonstrates what we know and do not know about the remote monitoring of SUDs within disease states.

Review of Ethanol Intoxication Sensing Technologies and Techniques

The field of alcohol intoxication sensing is over 100 years old, spanning the fields of medicine, chemistry, and computer science, aiming to produce the most effective and accurate methods of quantifying intoxication levels. This review presents the development and the current state of alcohol intoxication quantifying devices and techniques, separated into six major categories: estimates, breath alcohol devices, bodily fluid testing, transdermal sensors, mathematical algorithms, and optical techniques. Each of these categories was researched by analyzing their respective performances and drawbacks. We found that the major developments in monitoring ethanol intoxication levels aim at noninvasive transdermal/optical methods for personal monitoring. Many of the "categories" of ethanol intoxication systems overlap with each other with to a varying extent, hence the division of categories is based only on the principal operation of the techniques described in this review. In summary, the gold-standard method for measuring blood ethanol levels is through gas chromatography. Early estimation methods based on mathematical equations are largely popular in forensic fields. Breath alcohol devices are the most common type of alcohol sensors on the market and are generally implemented in law enforcement. Transdermal sensors vary largely in their sensing methodologies, but they mostly follow the principle of electrical sensing or enzymatic reaction rate. Optical devices and methodologies perform well, with some cases outperforming breath alcohol devices in terms of the precision of measurement. Other estimation algorithms consider multimodal approaches and should not be considered alcohol sensing devices, but rather as prospective measurement of the intoxication influence. This review found 38 unique technologies and techniques for measuring alcohol intoxication, which is testament to the acute interest in the innovation of noninvasive technologies for assessing intoxication.

Leveraging mHealth and Wearable Sensors to Manage Alcohol Use Disorders: A Systematic Literature Review

Background: Alcohol use disorder (AUD) is a condition prevalent in many countries around the world, and the public burden of its treatment is close to $130 billion. mHealth offers several possible interventions to assist in the treatment of AUD. Objectives: To analyze the effectiveness of mHealth and wearable sensors to manage AUD from evidence published over the last 10 years. Methods: Following the Kruse Protocol and PRISMA 2020, four databases were queried (PubMed, CINAHL, Web of Science, and Science Direct) to identify studies with strong methodologies (n = 25). Results: Five interventions were identified, and 20/25 were effective at reducing alcohol consumption. Other interventions reported a decrease in depression and an increase in medication compliance. Primary barriers to the adoption of mHealth interventions are a requirement to train users, some are equally as effective as the traditional means of treatment, cost, and computer literacy. Conclusion: While not all mHealth interventions demonstrated statistically significant reduction in alcohol consumption, most are still clinically effective to treat AUD and provide a patient with their preference of a technologically inclined treatment Most interventions require training of users and some technology literacy, the barriers identified were very few compared with the litany of positive results.

Sensitivity, specificity, and tolerability of the BACTrack Skyn compared to other alcohol monitoring approaches among young adults in a field-based setting

BACKGROUND

There is a need for novel alcohol biosensors that are accurate, able to detect alcohol concentration close in time to consumption, and feasible and acceptable for many clinical and research applications. We evaluated the field accuracy and tolerability of novel (BACTrack Skyn) and established (Alcohol Monitoring Systems SCRAM CAM) alcohol biosensors.

METHODS

The sensor and diary data were collected in a larger study of a biofeedback intervention and compared observationally in the present sub-study. Participants (high-risk drinkers, 40% female; median age 21) wore both Skyn and SCRAM CAM sensors for 1-6 days and were instructed to drink as usual. Data from the first cohort of participants (N = 27; 101 person-days) were used to find threshold values of transdermal alcohol that classified each day as meeting or not meeting defined levels of drinking (heavy, above-moderate, any). These values were used to develop scoring metrics that were subsequently tested using the second cohort (N = 20; 57 person-days). Data from both biosensors were compared to mobile diary self-report to evaluate sensitivity and specificity in relation to a priori standards established in the literature.

RESULTS

Skyn classification rules for Cohort #1 within 3 months of device shipment showed excellent sensitivity for heavy drinking (94%) and exceeded expectations for above-moderate and any drinking (78% and 69%, respectively), while specificity met expectations (91%). However, classification worsened when Cohort #1 devices ≥3 months from shipment were tested (area under curve for receiver operator characteristic 0.87 vs. 0.79) and the derived classification threshold when applied to Cohort #2 was inadequately specific (70%). Skyn tolerability metrics were excellent and exceeded the SCRAM CAM (p ≤ 0.001).

CONCLUSIONS

Skyn tolerability was favorable and accuracy rules were internally derivable but did not yield useful scoring metrics going forward across device lots and months of usage.

A Review on Flexible Electrochemical Biosensors to Monitor Alcohol in Sweat

The continued focus on improving the quality of human life has encouraged the development of increasingly efficient, durable, and cost-effective products in healthcare. Over the last decade, there has been substantial development in the field of technical and interactive textiles that combine expertise in electronics, biology, chemistry, and physics. Most recently, the creation of textile biosensors capable of quantifying biometric data in biological fluids is being studied, to detect a specific disease or the physical condition of an individual. The ultimate goal is to provide access to medical diagnosis anytime and anywhere. Presently, alcohol is considered the most commonly used addictive substance worldwide, being one of the main causes of death in road accidents. Thus, it is important to think of solutions capable of minimizing this public health problem. Alcohol biosensors constitute an excellent tool to aid at improving road safety. Hence, this review explores concepts about alcohol biomarkers, the composition of human sweat and the correlation between alcohol and blood. Different components and requirements of a biosensor are reviewed, along with the electrochemical techniques to evaluate its performance, in addition to construction techniques of textile-based biosensors. Special attention is given to the determination of biomarkers that must be low cost and fast, so the use of biomimetic materials to recognize and detect the target analyte is turning into an attractive option to improve electrochemical behavior.

Sociodemographic and clinical factors associated with transdermal alcohol concentration from the SCRAM biosensor among persons living with and without HIV

BACKGROUND

Transdermal alcohol biosensors can objectively monitor alcohol use by measuring transdermal alcohol concentration (TAC). However, it is unclear how sociodemographic and clinical factors that influence alcohol metabolism are associated with TAC. The main aim of this study was to examine how sociodemographic factors (sex, age, race/ethnicity) and clinical factors (body mass index, liver enzymes: alanine aminotransferase [ALT] and aspartate transaminase [AST]), alcohol use disorder, and HIV status were associated with TAC while controlling for level of alcohol use.

METHODS

We analyzed data from a prospective study involving contingency management for alcohol cessation among persons living with and without human immunodeficiency virus (HIV) that used the Secure Continuous Remote Alcohol Monitoring (SCRAM) biosensor. Forty-three participants (M_age  = 56.6 years; 63% male; 58% people living with HIV) yielded 183 SCRAM-detected drinking days. Two indices derived from SCRAM: peak TAC (reflecting level of intoxication) and TAC area under the curve (TAC-AUC; reflecting alcohol volume)-were the main outcomes. Self-reported alcohol use (drinks/drinking day) measured by Timeline Followback was the main predictor. To examine whether factors of interest were associated with TAC, we used individual generalized estimating equations (GEE), followed by a multivariate GEE model to include all significant predictors to examine their associations with TAC beyond the effect of self-reported alcohol use.

RESULTS

Number of drinks per drinking day (B = 0.29, p < 0.01) and elevated AST (B = 0.50, p = 0.01) were significant predictors of peak TAC. Positive HIV status, female sex, elevated AST, and number of drinks per drinking day were positively associated with TAC-AUC at the bivariate level, whereas only self-reported alcohol use (B = 0.85, p < 0.0001) and female sex (B = 0.67, p < 0.05) were significant predictors of TAC-AUC at the multivariate level.

CONCLUSIONS

HIV status was not independently associated with TAC. Future studies should consider the sex and liver function of the participant when using alcohol biosensors to measure alcohol use.

Exercise as a Useful Intervention to Reduce Alcohol Consumption and Improve Physical Fitness in Individuals With Alcohol Use Disorder: A Systematic Review and Meta-Analysis

Objective: This meta-analysis and systematic review examined the effects of exercise interventions on alcohol consumption and binge drinking in individuals with alcohol use disorder (AUD). Data sources: PubMed, Web of Science, Google Scholar, SPORTDiscus, and ERIC databases. Study Inclusion and Exclusion Criteria: Peer-reviewed randomized controlled trials published in English between 1970 and 2021. All studies compared exercise (Ex) and treatment as usual (TAU) to TAU in adults with an alcohol-related diagnosis. All forms of exercise interventions were included (e.g., aerobic exercise, yoga, resistance exercise, etc.). Data Extraction: Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols standard and the Meta-Analyses and Systematic Reviews of Observational Studies guidelines were followed. Risk of bias was assessed using the Cochrane risk-of-bias tool as described by the Cochrane Handbook for Systematic Reviews and Interventions. Results: The literature searches retrieved a combined 2527 studies, with 1,034 studies screened after removal of duplicates and 973 (94%) rejected after reviewing titles and abstracts. Full-text review was performed on 61 studies, with seven studies meeting inclusion criteria for qualitative and meta-analysis. Across seven studies (n = 492 participants), a significant effect (Z-value = -3.37; g = -0.30; 95% CI [-0.50--0.09]; p = 0.001) was found for Ex+TAU on drinking volume. There was no effect of Ex+TAU on binge drinking. The effect of Ex+TAU on physical fitness (VO2max, ml•kg-1•min-1) was significant (Z-score = 3.70; g = 0.64; 95% CI [0.19-1.08]; p < 0.001). Conclusions: Exercise interventions may decrease alcohol consumption and improve fitness and can be an effective adjunctive treatment for individuals with alcohol-related diagnoses including AUD.

PANI-Based Wearable Electrochemical Sensor for pH Sweat Monitoring

Nowadays, we are assisting in the exceptional growth in research relating to the development of wearable devices for sweat analysis. Sweat is a biofluid that contains useful health information and allows a non-invasive, continuous and comfortable collection. For this reason, it is an excellent biofluid for the detection of different analytes. In this work, electrochemical sensors based on polyaniline thin films deposited on the flexible substrate polyethylene terephthalate coated with indium tin oxide were studied. Polyaniline thin films were abstained by the potentiostatic deposition technique, applying a potential of +2 V vs. SCE for 90 s. To improve the sensor performance, the electronic substrate was modified with reduced graphene oxide, obtained at a constant potential of −0.8 V vs. SCE for 200 s, and then polyaniline thin films were electrodeposited on top of the as-deposited substrate. All samples were characterized by XRD, SEM, EDS, static contact angle and FT-IR/ATR analysis to correlate the physical-chemical features with the performance of the sensors. The obtained electrodes were tested as pH sensors in the range from 2 to 8, showing good behavior, with a sensitivity of 62.3 mV/pH, very close to a Nernstian response, and a reproducibility of 3.8%. Interference tests, in the presence of competing ions, aimed to verify the selectivity, were also performed. Finally, a real sweat sample was collected, and the sweat pH was quantified with both the proposed sensor and a commercial pH meter, showing an excellent concordance.