Alex M. Russell, Assistant Professor, Department of Health, Human Performance and Recreation, University of Arkansas, Fayetteville, AR, United States;, Email:
Adam E. Barry, Professor, Department of Health & Kinesiology, Texas A & M University, College Station, TX, United States.
Am J Health Behav. 2021 Jul 26;45(4):695-700. doi: 10.5993/AJHB.45.4.8.
Amazon's Mechanical Turk (MTurk) has become a popular data collection tool in the addiction sciences. We sought to examine the psychometric properties of the AUDIT-C in an MTurk sample. Data collection was facilitated via MTurk (N=309; 52.8% female), where an online survey assessed demographic data, alcohol use behaviors (AUDIT-C), and alcohol-related consequences (CAPS-r). Responses to the AUDIT-C were subjected to a principal component analysis to evaluate the structure of the 3-item measure. Alcohol-related consequences were used as a measure of convergent validity. Results provided evidence for a single-factor structure. Pearson's product-moment correlation coefficients between AUDIT-C scores and CAPS-r scores produced statistically significant results (r = 0.51, p < .001). Using biological sex-based suggested cut-off scores for the AUDIT-C, hazardous drinkers (M = 19.15, SD = 8.27) demonstrated statistically significantly higher levels of alcohol-related consequences than non-hazardous drinkers (M = 12.56, SD = 5.35; t(295) = -8.34, p < .001). Reliability and stability statistics demonstrated strong internal consistency. Results demonstrate the sound psychometric properties of the AUDIT-C for an MTurk sample and provide evidence supporting the use of AUDIT-C as a screening tool to be employed with digitally accessed populations to identify and reach hazardous drinkers.
亚马逊的 Mechanical Turk (MTurk) 已成为成瘾科学中一种流行的数据收集工具。我们旨在 MTurk 样本中检验 AUDIT-C 的心理测量特性。通过 MTurk（N=309；52.8%为女性）进行数据收集，其中一项在线调查评估了人口统计学数据、饮酒行为（AUDIT-C）和与酒精相关的后果（CAPS-r）。对 AUDIT-C 的回答进行了主成分分析，以评估该 3 项测量的结构。使用酒精相关后果作为收敛有效性的衡量标准。结果提供了单因素结构的证据。AUDIT-C 分数和 CAPS-r 分数之间的皮尔逊积矩相关系数产生了具有统计学意义的结果（r = 0.51，p <.001）。使用 AUDIT-C 的基于生物性别建议的截断分数，危险饮酒者（M = 19.15，SD = 8.27）的酒精相关后果水平明显高于非危险饮酒者（M = 12.56，SD = 5.35；t(295) = -8.34，p <.001）。可靠性和稳定性统计数据显示出很强的内部一致性。结果表明，AUDIT-C 具有 MTurk 样本的良好心理测量特性，并提供了使用 AUDIT-C 作为筛查工具的证据，该工具可用于数字访问人群，以识别和接触危险饮酒者。
