Ashley P. Kennedy

Are we there yet?: feasibility of continuous stress assessment via wireless physiological sensors

Stress can lead to headaches and fatigue, precipitate addictive behaviors (e.g., smoking, alcohol and drug use), and lead to cardiovascular diseases and cancer. Continuous assessment of stress from sensors can be used for timely delivery of a variety of interventions to reduce or avoid stress. We investigate the feasibility of continuous stress measurement via two field studies using wireless physiological sensors --- a four-week study with illicit drug users (n = 40), and a one-week study with daily smokers and social drinkers (n = 30). We find that 11+ hours/day of usable data can be obtained in a 4-week study. Significant learning effect is observed after the first week and data yield is seen to be increasing over time even in the fourth week. We propose a framework to analyze sensor data yield and find that losses in wireless channel is negligible; the main hurdle in further improving data yield is the attachment constraint. We show the feasibility of measuring stress minutes preceding events of interest and observe the sensor-derived stress to be rising prior to self-reported stress and smoking events.

Identifying drug (cocaine) intake events from acute physiological response in the presence of free-living physical activity

A variety of health and behavioral states can potentially be inferred from physiological measurements that can now be collected in the natural free-living environment. The major challenge, however, is to develop computational models for automated detection of health events that can work reliably in the natural field environment. In this paper, we develop a physiologically-informed model to automatically detect drug (cocaine) use events in the free-living environment of participants from their electrocardiogram (ECG) measurements. The key to reliably detecting drug use events in the field is to incorporate the knowledge of autonomic nervous system (ANS) behavior in the model development so as to decompose the activation effect of cocaine from the natural recovery behavior of the parasympathetic nervous system (after an episode of physical activity). We collect 89 days of data from 9 active drug users in two residential lab environments and 922 days of data from 42 active drug users in the field environment, for a total of 11,283 hours. We develop a model that tracks the natural recovery by the parasympathetic nervous system and then estimates the dampening caused to the recovery by the activation of the sympathetic nervous system due to cocaine. We develop efficient methods to screen and clean the ECG time series data and extract candidate windows to assess for potential drug use. We then apply our model on the recovery segments from these windows. Our model achieves 100% true positive rate while keeping the false positive rate to 0.87/day over (9+ hours/day of) lab data and to 1.13/day over (11+ hours/day of) field data.

Continuous in-the-field measurement of heart rate: Correlates of drug use, craving, stress, and mood in polydrug users

BACKGROUND Ambulatory physiological monitoring could clarify antecedents and consequences of drug use and could contribute to a sensor-triggered mobile intervention that automatically detects behaviorally risky situations. Our goal was to show that such monitoring is feasible and can produce meaningful data. METHODS We assessed heart rate (HR) with AutoSense, a suite of biosensors that wirelessly transmits data to a smartphone, for up to 4 weeks in 40 polydrug users in opioid-agonist maintenance as they went about their daily lives. Participants also self-reported drug use, mood, and activities on electronic diaries. We compared HR with self-report using multilevel modeling (SAS Proc Mixed). RESULTS Compliance with AutoSense was good; the data yield from the wireless electrocardiographs was 85.7%. HR was higher when participants reported cocaine use than when they reported heroin use (F(2,9)=250.3, p<.0001) and was also higher as a function of the dose of cocaine reported (F(1,8)=207.7, p<.0001). HR was higher when participants reported craving heroin (F(1,16)=230.9, p<.0001) or cocaine (F(1,14)=157.2, p<.0001) than when they reported of not craving. HR was lower (p<.05) in randomly prompted entries in which participants reported feeling relaxed, feeling happy, or watching TV, and was higher when they reported feeling stressed, being hassled, or walking. CONCLUSIONS High-yield, high-quality heart-rate data can be obtained from drug users in their natural environment as they go about their daily lives, and the resultant data robustly reflect episodes of cocaine and heroin use and other mental and behavioral events of interest.

Data compatibility in the addiction sciences: An examination of measure commonality

The need for comprehensive analysis to compare and combine data across multiple studies in order to validate and extend results is widely recognized. This paper aims to assess the extent of data compatibility in the substance abuse and addiction (SAA) sciences through an examination of measure commonality, defined as the use of similar measures, across grants funded by the National Institute on Drug Abuse (NIDA) and the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Data were extracted from applications of funded, active grants involving human-subjects research in four scientific areas (epidemiology, prevention, services, and treatment) and six frequently assessed scientific domains. A total of 548 distinct measures were cited across 141 randomly sampled applications. Commonality, as assessed by density (range of 0-1) of shared measurement, was examined. Results showed that commonality was low and varied by domain/area. Commonality was most prominent for (1) diagnostic interviews (structured and semi-structured) for substance use disorders and psychopathology (density of 0.88), followed by (2) scales to assess dimensions of substance use problems and disorders (0.70), (3) scales to assess dimensions of affect and psychopathology (0.69), (4) measures of substance use quantity and frequency (0.62), (5) measures of personality traits (0.40), and (6) assessments of cognitive/neurologic ability (0.22). The areas of prevention (density of 0.41) and treatment (0.42) had greater commonality than epidemiology (0.36) and services (0.32). To address the lack of measure commonality, NIDA and its scientific partners recommend and provide common measures for SAA researchers within the PhenX Toolkit.

A randomized investigation of methadone doses at or over 100 mg/day, combined with contingency management

BACKGROUND Methadone maintenance for heroin dependence reduces illicit drug use, crime, HIV risk, and death. Typical dosages have increased over the past few years, based on strong experimental and clinical evidence that dosages under 60 mg/day are inadequate and that dosages closer to 100mg/day produce better outcomes. However, there is little experimental evidence for the benefits of exceeding 100 mg/day, or for individualizing methadone dosages. We sought to provide such evidence. METHODS We combined individualized methadone dosages over 100 mg/day with voucher-based cocaine-targeted contingency management (CM) in 58 heroin- and cocaine-dependent outpatients. Participants were randomly assigned to receive a fixed dose increase from 70 mg/day to 100mg/day, or to be eligible for further dose increases (up to 190 mg/day, based on withdrawal symptoms, craving, and continued heroin use). All dosing was double-blind. The main outcome measure was simultaneous abstinence from heroin and cocaine. RESULTS We stopped the study early due to slow accrual. Cocaine-targeted CM worked as expected to reduce cocaine use. Polydrug use (effect-size h=.30) and heroin craving (effect-size d=.87) were significantly greater in the flexible/high-dose condition than in the fixed-dose condition, with no trend toward lower heroin use in the flexible/high-dose participants. CONCLUSIONS Under double-blind conditions, dosages of methadone over 100mg/day, even when prescribed based on specific signs and symptoms, were not better than 100mg/day. This counterintuitive finding requires replication, but supports the need for additional controlled studies of high-dose methadone.

mDebugger: Assessing and Diagnosing the Fidelity and Yield of Mobile Sensor Data

Mobile sensor data collected in the natural environment are subject to numerous sources of data loss and quality deterioration. This may be due to degradation in attachment, change in placement, battery depletion, wireless interference, or movement artifacts. Identifying and fixing the major sources of data loss is critical to ensuring high data yield from mobile sensors. This chapter describes a systematic approach for identifying the major sources of data loss that can then be used to improve mobile sensor data yield.