Sensitivity, specificity, and tolerability of the BACTrack Skyn compared to other alcohol monitoring approaches among young adults in a field-based setting.
alcohol use
biosensors
self-monitoring
transdermal alcohol sensors
wearable alcohol sensors
Journal
Alcoholism, clinical and experimental research
ISSN: 1530-0277
Titre abrégé: Alcohol Clin Exp Res
Pays: England
ID NLM: 7707242
Informations de publication
Date de publication:
05 2022
05 2022
Historique:
revised:
14
01
2022
received:
24
08
2021
accepted:
28
02
2022
pubmed:
15
5
2022
medline:
20
5
2022
entrez:
14
5
2022
Statut:
ppublish
Résumé
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. 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. 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). 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.
Sections du résumé
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.
Identifiants
pubmed: 35567595
doi: 10.1111/acer.14804
pmc: PMC9179100
mid: NIHMS1786444
doi:
Substances chimiques
Ethanol
3K9958V90M
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
783-796Subventions
Organisme : NIAAA NIH HHS
ID : R21 AA028886
Pays : United States
Organisme : NIAAA NIH HHS
ID : R34 AA026021
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR000142
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR001863
Pays : United States
Informations de copyright
© 2022 by the Research Society on Alcoholism.
Références
Drug Alcohol Depend. 2020 Nov 1;216:108205
pubmed: 32853998
Addict Behav. 2018 Oct;85:147-152
pubmed: 29910035
P T. 2018 Dec;43(12):758-763
pubmed: 30559589
Med Sci Sports Exerc. 2008 Jan;40(1):181-8
pubmed: 18091006
Front Psychiatry. 2021 Mar 22;12:642813
pubmed: 33828497
Alcohol Clin Exp Res. 2014 Oct;38(10):2657-63
pubmed: 25346506
Psychol Addict Behav. 2016 Dec;30(8):791-801
pubmed: 27669095
J Med Internet Res. 2020 Aug 11;22(8):e17449
pubmed: 32780027
J Clin Sleep Med. 2018 Oct 15;14(10):1783-1790
pubmed: 30353814
Drug Alcohol Depend. 2017 Sep 1;178:417-424
pubmed: 28709081
Drug Alcohol Depend. 2014 Sep 1;142:301-6
pubmed: 25064019
Alcohol Clin Exp Res. 2019 Oct;43(10):2060-2069
pubmed: 31469451
J Stud Alcohol. 2003 Nov;64(6):858-61
pubmed: 14743950
Curr Sports Med Rep. 2020 Feb;19(2):45-49
pubmed: 32028347
J Subst Abuse Treat. 2017 Nov;82:67-73
pubmed: 29021117
Behav Sleep Med. 2015;13(5):395-411
pubmed: 24924956
J Stud Alcohol Drugs. 2020 Mar;81(2):212-219
pubmed: 32359051
Alcohol Clin Exp Res. 2015 Jul;39(7):1120-7
pubmed: 25988708
Health Commun. 2020 Nov;35(12):1531-1544
pubmed: 31488002
Addict Behav. 2020 Nov;110:106471
pubmed: 32526551
Alcohol Clin Exp Res. 2013 Jan;37(1):16-22
pubmed: 22823467
Alcohol Clin Exp Res. 2017 Apr;41(4):798-809
pubmed: 28118486
Addiction. 2017 Jun;112(6):1025-1035
pubmed: 28107772
JMIR Res Protoc. 2021 Feb 26;10(2):e26557
pubmed: 33635276
Ann Epidemiol. 2009 Mar;19(3):180-6
pubmed: 19217000
Exp Clin Psychopharmacol. 2014 Feb;22(1):86-96
pubmed: 24490713
N Engl J Med. 2019 Sep 5;381(10):956-968
pubmed: 31483966
Alcohol. 2021 May;92:25-34
pubmed: 33609635
Nicotine Tob Res. 2019 Jan 4;21(2):173-179
pubmed: 29059349
Drug Alcohol Depend. 2015 Mar 1;148:77-84
pubmed: 25582388
Psychol Assess. 2012 Dec;24(4):954-63
pubmed: 22612646
Addiction. 2021 Oct;116(10):2912-2920
pubmed: 33908674
Sports Med. 2021 Nov;51(11):2237-2250
pubmed: 34468950
Alcohol. 2019 Dec;81:131-138
pubmed: 30710610
Alcohol. 2019 Dec;81:101-110
pubmed: 30179708
Alcohol. 2019 Dec;81:83-92
pubmed: 30179709
J Hypertens. 2013 Sep;31(9):1731-68
pubmed: 24029863
Diabetes Care. 2019 Aug;42(8):1593-1603
pubmed: 31177185