Mobile alcohol biosensors and pharmacotherapy development research

Navigating ethical challenges in psychological research involving digital remote technologies and people who use alcohol or drugs

Digital and remote technologies (DRT) are increasingly being used in scientific investigations to objectively measure human behavior during day-to-day activities. Using these devices, psychologists and other behavioral scientists can investigate health risk behaviors, such as drug and alcohol use, by closely examining the causes and consequences of monitored behaviors as they occur naturalistically. There are, however, complex ethical issues that emerge when using DRT methodologies in research with people who use substances. These issues must be identified and addressed so DRT devices can be incorporated into psychological research with this population in a manner that comports the ethical standards of the American Psychological Association. In this article, we discuss the ethical ramifications of using DRT in behavioral studies with people who use substances. Drawing on allied fields with similar ethical issues, we make recommendations to researchers who wish to incorporate DRT into their own research. Major topics include (a) threats to and methods for protecting participant and nonparticipant privacy, (b) shortcomings of traditional informed consent in DRT research, (c) researcher liabilities introduced by real-time continuous data collection, (d) threats to distributive justice arising from computational tools often used to manage and analyze DRT data, and (e) ethical implications of the "digital divide." We conclude with a more optimistic discussion of how DRT may provide safer alternatives to gold standard paradigms in substance use research, allowing researchers to test hypotheses that were previously prohibited on ethical grounds. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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.

Biopolymer Composites with Sensors for Environmental and Medical Applications

One of the biggest economic and environmental sustainability problems is the over-reliance on petroleum chemicals in polymer production. This paper presents an overview of the current state of knowledge on biopolymers combined with biosensors in terms of properties, compounding methods and applications, with a focus on medical and environmental aspects. Therefore, this article is devoted to environmentally friendly polymer materials. The paper presents an overview of the current state of knowledge on biopolymers combined with biosensors in terms of properties, compounding methods and applications, with a special focus on medical and environmental aspects. The paper presents the current state of knowledge, as well as prospects. The article shows that biopolymers made from renewable raw materials are of great interest in various fields of science and industry. These materials not only replace existing polymers in many applications, but also provide new combinations of properties for new applications. Composite materials based on biopolymers are considered superior to traditional non-biodegradable materials due to their ability to degrade when exposed to environmental factors. The paper highlights the combination of polymers with nanomaterials which allows the preparation of chemical sensors, thus enabling their use in environmental or medical applications due to their biocompatibility and sensitivity. This review focuses on analyzing the state of research in the field of biopolymer-sensor composites.

Targeting Unmet Clinical Needs in the Treatment of Alcohol Use Disorder

Alcohol Use Disorder (AUD) is a chronic psychiatric disorder marked by impaired control over drinking behavior that poses a significant challenge to the individual, their community, the healthcare system and economy. While the negative consequences of chronic excessive alcohol consumption are well-documented, effective treatment for AUD and alcohol-associated diseases remains challenging. Cognitive and behavioral treatment, with or without pharmaceutical interventions, remain the most commonly used methods; however, their efficacy is limited. The development of new treatment protocols for AUD is challenged by difficulty in accurately measuring patterns of alcohol consumption in AUD patients, a lack of a clear understanding of the neuropsychological basis of the disorder, the high likelihood of AUD patients relapsing after receiving treatment, and the numerous end-organ comorbidities associated with excessive alcohol use. Identification and prediction of patients who may respond well to a certain treatment mechanism as well as clinical measurement of a patient's alcohol exposure are bottlenecks in AUD research which should be further addressed. In addition, greater focus must be placed on the development of novel strategies of drug design aimed at targeting the integrated neural pathways implicated in AUD pathogenesis, so that next-generation AUD treatment protocols can address the broad and systemic effects of AUD and its comorbid conditions.

Transducer Technologies for Biosensors and Their Wearable Applications

The development of new biosensor technologies and their active use as wearable devices have offered mobility and flexibility to conventional western medicine and personal fitness tracking. In the development of biosensors, transducers stand out as the main elements converting the signals sourced from a biological event into a detectable output. Combined with the suitable bio-receptors and the miniaturization of readout electronics, the functionality and design of the transducers play a key role in the construction of wearable devices for personal health control. Ever-growing research and industrial interest in new transducer technologies for point-of-care (POC) and wearable bio-detection have gained tremendous acceleration by the pandemic-induced digital health transformation. In this article, we provide a comprehensive review of transducers for biosensors and their wearable applications that empower users for the active tracking of biomarkers and personal health parameters.

Using wearable technology to detect prescription opioid self-administration

ABSTRACT

Appropriate monitoring of opioid use in patients with pain conditions is paramount, yet it remains a very challenging task. The current work examined the use of a wearable sensor to detect self-administration of opioids after dental surgery using machine learning. Participants were recruited from an oral and maxillofacial surgery clinic. Participants were 46 adult patients (26 female) receiving opioids after dental surgery. Participants wore Empatica E4 sensors during the period they self-administered opioids. The E4 collected physiological parameters including accelerometer x-, y-, and z-axes, heart rate, and electrodermal activity. Four machine learning models provided validation accuracies greater than 80%, but the bagged-tree model provided the highest combination of validation accuracy (83.7%) and area under the receiver operating characteristic curve (0.92). The trained model had a validation sensitivity of 82%, a specificity of 85%, a positive predictive value of 85%, and a negative predictive value of 83%. A subsequent test of the trained model on withheld data had a sensitivity of 81%, a specificity of 88%, a positive predictive value of 87%, and a negative predictive value of 82%. Results from training and testing model of machine learning indicated that opioid self-administration could be identified with reasonable accuracy, leading to considerable possibilities of the use of wearable technology to advance prevention and treatment.

A new generation of transdermal alcohol biosensing technology: practical applications, machine -learning analytics and questions for future research

The use of transdermal alcohol monitors has burgeoned in recent years, now encompassing hundreds of thousands of individuals globally. A new generation of sensors promises to expand the range of applications for transdermal technology exponentially, and advances in machine-learning modeling approaches offer new methods for translating the data produced by transdermal devices. This article provides (1) a review of transdermal sensor research conducted to date, including an analysis of methodological features of past studies potentially key in driving reported sensor performance; (2) updates on methodological developments likely to be transformative for the field of transdermal sensing, including the development of new-generation sensors featuring smartphone integration and rapid sampling capabilities as well as developments in machine-learning analytics suited to data produced by these novel sensors and; (3) an analysis of the expanded range of applications for this new generation of sensor, together with corresponding requirements for sensor accuracy and temporal specificity. We also note questions as yet unanswered and key directions for future research.

Pharmaceutical mobile application for visually-impaired people in Thailand: development and implementation

BACKGROUND

Most mobile pharmaceutical applications produced for people with visual disabilities in Thailand fail to meet the required standard due to poor-quality regulations, defective design, lack of user support and impracticality; as a result, visually-impaired people are unable to use them. This research is motivated by the limited use of this technology in primary medical services and its aim is to enable people with disabilities to access effective digital health information. The research objective is to analyse, design and develop a mobile pharmaceutical application with functions that are appropriate for visually-impaired users, and test its usability.

RESULTS

Based on the design and development of the application, it contained five necessary functions. When testing the usability and users' satisfaction, it was found that the input or fill of information in the application was of low usability. According to the test results, the medicinal database function was missing 71 times and the voice command function was missing 34 times. Based on users' satisfaction results, users who had the highest level of usage gave higher average scores to users' attitude, users' confidence, user interface and system performance than those with lower levels of usage. The scores of both groups were found to be the same when discussing the implementation of the development.

CONCLUSIONS

This mobile application, which was developed based on the use of smart technology, will play an important role in supporting visually-impaired people in Thailand by enhancing the efficacy of self-care. The design and development of the application will ensure the suitability of many functions for visually-impaired users. However, despite the high functional capacity of the application, the gap in healthcare services between the general public and disabled groups will still exist if users have inadequate IT skills.

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

Biosensors enable observation and understanding of latent physiological occurrences otherwise unknown or invasively detected. Wearable biosensors monitoring physiological constructs across a wide variety of mental and physical health conditions have become an important trend in innovative research methodologies. Within substance use research, explorations of biosensor technology commonly focus on identifying physiological indicators of intoxication to increase understanding of addiction etiology and to inform treatment recommendations. In this review, we examine the state of research in this area as it pertains to treatment of alcohol use disorders specifically highlighting the gaps in our current knowledge with recommendations for future research. Annually, alcohol use disorders affect approximately 15 million individuals. A primary focus of existing wearable technology-based research among people with alcohol use disorders is identifying alcohol intoxication. A large benefit of wearable biosensors for this purpose is they provide continuous readings in a passive manner compared with the gold standard measure of blood alcohol content (BAC) traditionally measured intermittently by breathalyzer or blood draw. There are two primary means of measuring intoxication with biosensors: gait and sweat. Gait changes have been measured via smart sensors placed on the wrist, in the shoe, and mobile device sensors in smart phones. Sweat measured by transdermal biosensors detects the presence of alcohol in the blood stream correlating to BAC. Transdermal biosensors have been designed in tattoos/skin patches, shirts, and most commonly, devices worn on the ankle or wrist. Transdermal devices were initially developed to help monitor court-ordered sobriety among offenders with alcohol use disorder. These devices now prove most useful in continuously tracking consumption throughout clinical trials for behavioral treatment modalities. More recent research has started exploring the uses for physical activity trackers and physiological arousal sensors to guide behavioral interventions for relapse prevention. While research has begun to demonstrate wearable devices' utility in reducing alcohol consumption among individuals aiming to cutdown on their drinking, monitoring sustained abstinence in studies exploring contingency management for alcohol use disorders, and facilitating engagement in activity-based treatment interventions, their full potential to further aid in understanding of, and treatment for, alcohol use disorders has yet to be explored.

Electrochemical monitoring of alcohol in sweat

Rapid, periodic monitoring and detection of ethanol (EtOH) after consumption via a non-invasive measurement has been an area of increased research in recent years. Current point-of-care or on-site detection strategies rely on single use sensors which are inadequate for monitoring during a longer period. A low cost, portable and novel approach is developed here for real-time monitoring over several days utilising electrochemical techniques. The sensor shows oxidation of the ethanol in phosphate buffer and artificial sweat using the amperometric response from the application of +0.9 V to the polyaniline modified screen printed electrode using 1 mM EtOH as the averaged amount of EtOH eliminated in sweat after the consumption of one alcoholic beverage. Our enzyme based electrochemical sensor exhibits a qualitative assessment of the presence of EtOH in small volumes (≤40 μL) of 0.1 M sodium bicarbonate and subsequently artificial sweat, with 50 measurements taken daily over 11 days. While quantitative information is not obtained, the sensor system exhibits excellent stability after 3 months' dried storage in this complex biological matrix in an oxygen free cabinet. This addresses one of the key challenges for enzyme based electrochemical sensors, namely, the ability for real-time monitoring in complex biological matrices. The qualitative response illustrates the potential for this sensor to be exploited by non-experts which suggests the promise for their wider application in next-generation wearable electronics necessary for alcohol monitoring.

Sensitivity and specificity of a commercial urinary ethyl glucuronide (ETG) test in heavy drinkers

Introduction

To advance the use of alcohol metabolites as biomarkers in the context of alcohol research, the present study tested the sensitivity and specificity of a commercially available urinary ethyl glucuronide (uEtG) test (DrugConfirm Advanced 80hr EtG) in a clinical research context.

Methods

A community sample of heavy drinkers (N = 68) completed the 30-day Timeline Follow-Back (TLFB) interview and provided a urine sample for uEtG analysis. Analyses of sensitivity and specificity of the uEtG assay were conducted using the following outcomes: (a) past day drinking, (b) past day binge drinking (defined as ≥4 drinks for women and ≥5 drinks for men), (c) past 3-day drinking, and (d) past 3-day binge drinking.

Results

The majority of participants reported past-3-day drinking (80.9%) and a sizeable minority reported past day drinking (33.8%). While uEtG-based detection of past day drinking and binge drinking was acceptable (sensitivity = 73.91%, and 83.33%; specificity = 80.00% and 66.13%, respectively), detection of any drinking and binge drinking in the past 3 days was poor (sensitivity and specificity of 43.64% and 84.62%, and 39.39% and 62.86%, respectively).

Conclusions

This study contributes to the mixed findings on the validity of EtG tests, which suggest that commercial uEtG tests with conservative detection thresholds are not a reliable alcohol biomarker without corroborating self-report data. Lower detection thresholds are recommended when using uEtG as an alcohol biomarker. Efforts to reach acceptable levels of sensitivity and specificity with commercial assays hold potential to advance the measurement of alcohol intake, overcoming the pitfalls of self-report data.

Methods to reduce the incidence of false negative trial results in substance use treatment research

Treatment development and evaluation for substance use disorders are hindered when randomized controlled trials fail to show a treatment effect when one exists. This manuscript provides an overview of addressable methodological factors that may contribute to incorrect trial results. The collection of remote, naturalistic, real-time adherence and substance use data through ambulatory assessment methods in everyday life is presented as a partial solution. Other recommendations related to participant recruitment and selection, ensuring adequate consistency/fidelity and dose of treatment, and rigorously assessing clinical outcomes are discussed. With implementation of eligibility criteria verification, treatment adherence monitoring, and remote assessment of substance use and biomarkers, ambulatory assessment may help improve clinical trial success rates by improving precision, increasing reproducibility, and reducing the impact of methodological issues that may lead to inaccurate trial results.