Watson Poppy, Onie Sandersan
School of Psychology, Faculty of Science, UNSW Sydney, Sydney, New South Wales 2052, Australia.
Black Dog Institute, UNSW Sydney, Sydney, Australia.
Data Brief. 2023 Jan 20;47:108914. doi: 10.1016/j.dib.2023.108914. eCollection 2023 Apr.
For multi-session alcohol cognitive bias modification, a large image dataset depicting both alcohol and non-alcoholic beverages is required. We photographed a wide range of beverages and then validated them in a group of Australian community participants: 47 women and 39 men, aged from 18 to 73, who drank alcohol at least occasionally in the last year, with Alcohol Use Disorder Identification Test (AUDIT) scores ranging from 1 to 33. Participants were asked to categorize images as alcoholic vs non-alcoholic, rate the familiarity of each beverage and rate their craving for each beverage. The dataset includes all images and ratings for each image, stratified by gender and high/low AUDIT scores. Mean ratings per participant per beverage category are also provided.
对于多阶段酒精认知偏差矫正,需要一个描绘酒精饮料和非酒精饮料的大型图像数据集。我们拍摄了各种各样的饮料,然后在一组澳大利亚社区参与者中进行了验证:47名女性和39名男性,年龄在18至73岁之间,他们在过去一年中至少偶尔饮酒,酒精使用障碍识别测试(AUDIT)得分在1至33之间。参与者被要求将图像分类为酒精饮料或非酒精饮料,对每种饮料的熟悉程度进行评分,并对每种饮料的渴望程度进行评分。该数据集包括所有图像以及每个图像的评分,按性别和AUDIT得分高低进行分层。还提供了每个参与者每种饮料类别的平均评分。