Development and validation of a model for measuring alcohol consumption from transdermal alcohol content data among college students.
Background and aims: Transdermal alcohol content (TAC) data collected by wearable alcohol monitors could potentially contribute to alcohol research, but raw data from the devices are challenging to interpret. We aimed to develop and validate a model using TAC data to detect alcohol drinking. Design:...
| Publicado en: | Addiction Vol. 118; no. 10; pp. 2014 - 2026 |
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| Autores principales: | , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Oct2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=171583258&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 171583258 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09652140 AIO jtl: Addiction issn: 09652140 maglogo: Y pubinfo: dt: Oct2023 vid: 118 iid: 10 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 171583258 163960521 171583258 171583258 10.1111/add.16228 171583258 ppf: 2014 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: C – @attributes: type: P tig: atl: Development and validation of a model for measuring alcohol consumption from transdermal alcohol content data among college students. aug: au: Kianersi, Sina Ludema, Christina Agley, Jon Ahn, Yong‐Yeol Parker, Maria Ideker, Sophie Rosenberg, Molly affil: Department of Epidemiology and Biostatistics, Indiana University School of Public Health‐Bloomington, Bloomington Indiana,, USA sug: subj: Instrument Construction Instrument Validation Alcohol Drinking in College Students, College Models, Theoretical Substance Use Disorders Human Male Female Adolescence Young Adult United States Validation Studies Regression Algorithms Breath Tests Ethanol Self Report Mobile Applications Electrical Equipment and Supplies Alcoholism Drinking Behavior Sensitivity and Specificity Surveys Descriptive Statistics Spearman's Rank Correlation Coefficient Confidence Intervals Funding Source Adolescent: 13-18 years Male Female ab: Background and aims: Transdermal alcohol content (TAC) data collected by wearable alcohol monitors could potentially contribute to alcohol research, but raw data from the devices are challenging to interpret. We aimed to develop and validate a model using TAC data to detect alcohol drinking. Design: We used a model development and validation study design. Setting: Indiana, USA Participants: In March to April 2021, we enrolled 84 college students who reported drinking at least once a week (median age = 20 years, 73% white, 70% female). We observed participants' alcohol drinking behavior for 1 week. Measurements Participants wore BACtrack Skyn monitors (TAC data), provided self‐reported drinking start times in real time (smartphone app) and completed daily surveys about their prior day of drinking. We developed a model using signal filtering, peak detection algorithm, regression and hyperparameter optimization. The input was TAC and outputs were alcohol drinking frequency, start time and magnitude. We validated the model using daily surveys (internal validation) and data collected from college students in 2019 (external validation). Findings Participants (N = 84) self‐reported 213 drinking events. Monitors collected 10 915 hours of TAC. In internal validation, the model had a sensitivity of 70.9% (95% CI = 64.1%–77.0%) and a specificity of 73.9% (68.9%–78.5%) in detecting drinking events. The median absolute time difference between self‐reported and model‐detected drinking start times was 59 min. Mean absolute error (MAE) for the reported and detected number of drinks was 2.8 drinks. In an exploratory external validation among five participants, number of drinking events, sensitivity, specificity, median time difference and MAE were 15%, 67%, 100%, 45 minutes and 0.9 drinks, respectively. Our model's output was correlated with breath alcohol concentration data (Spearman's correlation [95% CI] = 0.88 [0.77, 0.94]). Conclusion: This study, the largest of its kind to date, developed and validated a model for detecting alcohol drinking using transdermal alcohol content data collected with a new generation of alcohol monitors. The model and its source code are available as Supporting Information (https://osf.io/xngbk). pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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