A Multi-Component Data Processing Program for Transdermal Alcohol Sensors

描述（由申请人提供）：测量人体皮肤汗液中酒精含量的传感器目前可用，并被法院用于监测酒驾违者，以及niaaa资助的研究和治疗效果研究的研究人员使用。这两种可用设备（SCRAM和腕表）在研究和应用方面的潜力是相当大的，但对用户来说也存在严重的挑战。传感器内部或传感器之间没有用于识别酒精使用事件的共享程序，透皮酒精浓度（TAC）值在数量上不等同于血液或呼吸酒精含量（BAC/BrAC）， TAC曲线相对于BAC/BrAC曲线延迟。此外，传感器数据文件很大，由于数据的性质，计算汇总变量可能非常耗时。这些挑战损害了传感器数据研究的有效性和可靠性，并限制了酒精生物传感器技术在研究和治疗中的应用。本提案的主要目标是利用现有数据和成瘾研究、流行病学、数学和生物统计学方面的知名专家，推进酒精透皮传感器的研究，并解决传感器用户面临的主要挑战。具体目标是：(1)建立两种可用透皮传感器检测酒精使用事件的最佳方法，以及(2)开发两种可用传感器从TAC中反卷积BAC估计的方法，并通过这样做消除TAC中观察到的时间滞后。在解决每个目标的同时，我们将制作专门的分析工具，将研究成果纳入其中。对于Aim 1，我们将修改当前的原型，即透皮酒精传感器宏（TASMAC），其中包含用于读取传感器数据输入文件的每一行的Visual Basic代码；根据用户定义的参数，该工具将识别酒精消费事件，创建汇总变量，并格式化适合用于统计的数据输出文件

DESCRIPTION (provided by applicant): Sensors that measure alcohol in the perspiration on a person's skin are currently available and are used by courts to monitor DUI offenders and by researchers in NIAAA-funded research and treatment efficacy studies. The potential of the two available devices (SCRAM and WrisTAS) for research and applied use is considerable, but there are serious challenges for users. There are no shared procedures within or across sensors for identifying alcohol use episodes, transdermal alcohol concentration (TAC) values are not quantitatively equivalent to blood or breath alcohol content (BAC/BrAC), and TAC curves are delayed relative to BAC/BrAC curves. Furthermore, sensor data files are large and, due to the nature of the data, calculating summary variables can be very time consuming. These challenges compromise the validity and reliability of research with sensor data, and limit the adoption of the alcohol biosensor technology in research and treatment. The primary objective of this proposal is to use existing data and known experts in addiction research, epidemiology, mathematics, and biostatistics to advance research with alcohol transdermal sensors and to address the key challenges for users of the sensors. The specific aims are to: (1) establish the best methods for detecting alcohol use episodes with both available transdermal sensors, and (2) develop methods to deconvolve BAC estimates from TAC for both available sensors, and in doing so eliminate the observed time lag in TAC. Simultaneous with addressing each aim, we will produce specialized analytic tools that will incorporate the research findings. For Aim 1, we will modify a current prototype, the Transdermal Alcohol Sensor Macro (TASMAC) that contains Visual Basic code to read each line of a sensor data input file; according to user-defined parameters the tool will identify alcohol consumption episodes, create summary variables, and format a data output file suitable for use with statistical software. For Aim 2, the BAC Estimator software will be developed by Dr. Gary Rosen using methods that do not require an alcohol challenge to calibrate the estimation model. Both tools will have graphical user interfaces for ease of use, and both tools will work within Microsoft EXCEL. We will use a collaborative, interdisciplinary approach with eight researchers who have used one of the sensors; collaborators will provide data from controlled laboratory administration studies, field research, and intervention trials to evaluate research aims and develop the tool functions, and will test the tools with their data as part of the evaluation. Research findings and the resulting tools will simplify complex data processing and calculations, thereby removing a barrier to conducting basic, epidemiological, and applied clinical research with transdermal alcohol sensors. PUBLIC HEALTH RELEVANCE: Transdermal alcohol sensors have primarily been used to monitor almost 200,000 individuals who have been court ordered not to use alcohol. Research and treatments incorporating alcohol sensors will develop more quickly if we can validate alcohol use detection criteria and derive accurate estimates of alcohol concentration and alcohol impairment. The tools developed in this application will help translate our research findings into practice, will recommend best practices, and will accelerate the adoption of alcohol sensors for use in research and treatment to help reduce the problem of high-risk drinking.