TY - JOUR
T1 - Continuous in-the-field measurement of heart rate
T2 - Correlates of drug use, craving, stress, and mood in polydrug users
AU - Kennedy, Ashley P.
AU - Epstein, David H.
AU - Jobes, Michelle L.
AU - Agage, Daniel
AU - Tyburski, Matthew
AU - Phillips, Karran A.
AU - Ali, Amin Ahsan
AU - Bari, Rummana
AU - Hossain, Syed Monowar
AU - Hovsepian, Karen
AU - Rahman, Md Mahbubur
AU - Ertin, Emre
AU - Kumar, Santosh
AU - Preston, Kenzie L.
N1 - Funding Information:
This research was supported by the National Institute on Drug Abuse Intramural Research Program and NSF grants CNS-0910878 (funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)), CNS-1212901, IIS-1231754, and by NIH Grants U01DA023812 under Genes Environment and Health Initiative (GEI) and R01DA035502 under the Basic Behavioral and Social Sciences Research Opportunity Network (OppNet).
Funding Information:
This research was supported by the National Institute on Drug Abuse Intramural Research Program and NSF grants CNS-0910878 (funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)), CNS-1212901 , IIS-1231754 , and by NIH Grants U01DA023812 under Genes Environment and Health Initiative (GEI) and R01DA035502 under the Basic Behavioral and Social Sciences Research Opportunity Network (OppNet). The authors had sole responsibility for the design and conduct of the study, the analysis and interpretation of the data, and the preparation and review of the manuscript.
Publisher Copyright:
© 2015.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - 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.
AB - 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.
KW - Ambulatory physiological monitoring
KW - Cocaine
KW - Craving
KW - Heart rate
KW - Heroin
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U2 - 10.1016/j.drugalcdep.2015.03.024
DO - 10.1016/j.drugalcdep.2015.03.024
M3 - Article
C2 - 25920802
AN - SCOPUS:84929964245
SN - 0376-8716
VL - 151
SP - 159
EP - 166
JO - Drug and alcohol dependence
JF - Drug and alcohol dependence
ER -