A machine learning model for the prediction of unhealthy alcohol use among women of childbearing age in Alabama.

IF 2.1 4区医学 Q3 SUBSTANCE ABUSE

Alcohol and alcoholism Pub Date : 2024-01-17 DOI:10.1093/alcalc/agad075

Karen A Johnson, Justin T McDaniel, Joana Okine, Heather K Graham, Ellen T Robertson, Shanna McIntosh, Juliane Wallace, David L Albright

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引用次数: 0

Abstract

Introduction: This study utilizes a machine learning model to predict unhealthy alcohol use treatment levels among women of childbearing age.

Methods: In this cross-sectional study, women of childbearing age (n = 2397) were screened for alcohol use over a 2-year period as part of the AL-SBIRT (screening, brief intervention, and referral to treatment in Alabama) program in three healthcare settings across Alabama for unhealthy alcohol use severity and depression. A support vector machine learning model was estimated to predict unhealthy alcohol use scores based on depression score and age.

Results: The machine learning model was effective in predicting no intervention among patients with lower Patient Health Questionnaire (PHQ)-2 scores of any age, but a brief intervention among younger patients (aged 18-27 years) with PHQ-2 scores >3 and a referral to treatment for unhealthy alcohol use among older patients (between the ages of 25 and 50) with PHQ-2 scores >4.

Conclusions: The machine learning model can be an effective tool in predicting unhealthy alcohol use treatment levels and approaches.

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预测阿拉巴马州育龄妇女不健康饮酒的机器学习模型。

本研究利用机器学习模型预测育龄妇女不健康饮酒的治疗水平。方法:在这项横断面研究中，育龄妇女(n = 2397)作为AL-SBIRT(筛查、短暂干预和转诊到阿拉巴马州的治疗)项目的一部分，在阿拉巴马州的三个医疗机构中对不健康的酒精使用严重程度和抑郁症进行了2年的酒精使用筛查。估计支持向量机器学习模型可以根据抑郁评分和年龄预测不健康酒精使用评分。结果:机器学习模型在预测患者健康问卷(PHQ)-2得分较低的任何年龄的患者无干预方面是有效的，但在PHQ-2得分> - 4的年轻患者(18-27岁)中有短暂的干预，在PHQ-2得分> - 4的老年患者(25岁至50岁)中有转诊治疗。结论:机器学习模型可作为预测不健康酒精使用治疗水平和方法的有效工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Alcohol and alcoholism 医学-药物滥用

CiteScore

4.70

自引率

3.60%

发文量

审稿时长

4-8 weeks

期刊介绍： About the Journal Alcohol and Alcoholism publishes papers on the biomedical, psychological, and sociological aspects of alcoholism and alcohol research, provided that they make a new and significant contribution to knowledge in the field. Papers include new results obtained experimentally, descriptions of new experimental (including clinical) methods of importance to the field of alcohol research and treatment, or new interpretations of existing results. Theoretical contributions are considered equally with papers dealing with experimental work provided that such theoretical contributions are not of a largely speculative or philosophical nature.