a School of Journalism and Mass Communication , University of Wisconsin-Madison.
b Department of Communication Arts , University of Wisconsin-Madison.
Health Commun. 2018 Sep;33(9):1184-1193. doi: 10.1080/10410236.2017.1350906. Epub 2017 Aug 9.
Increasingly, individuals with alcohol use disorder (AUD) seek and provide support for relapse prevention in text-based online environments such as discussion forums. This paper investigates whether language use within a peer-to-peer discussion forum can predict future relapse among individuals treated for AUD. A total of 104 AUD sufferers who had completed residential treatment participated in a mobile phone-based relapse-prevention program, where they communicated via an online forum over the course of a year. We extracted patterns of language use on the forum within the first four months on study using Linguistic Inquiry and Word Count (LIWC), a dictionary-based text analysis program. Participants reported their incidence of risky drinking via a survey at 4, 8, and 12 months. A logistic regression model was built to predict the likelihood that individuals would engage in risky drinking within a year based on their language use, while controlling for baseline characteristics and rates of utilizing the mobile system. Results show that all baseline characteristics and system use factors explained just 13% of the variance in relapse, whereas a small number of linguistic cues, including swearing and cognitive mechanism words, accounted for an additional 32% of the total 45% of variance in relapse explained by the model. Effective models for predicting relapse are needed. Messages exchanged on AUD forums could provide an unobtrusive and cost-effective window into the future health outcomes of AUD sufferers, and their psychological underpinnings. As online communication expands, models that leverage user-submitted text toward predicting relapse will be increasingly scalable and actionable.
越来越多的酒精使用障碍(AUD)患者在基于文本的在线环境(如论坛)中寻求和提供预防复发的支持。本文研究了在同伴对同伴讨论论坛中使用的语言是否可以预测接受 AUD 治疗的个体未来的复发情况。共有 104 名 AUD 患者完成了住院治疗,他们参与了一项基于手机的预防复发计划,在一年的时间里通过在线论坛进行交流。我们使用基于词典的文本分析程序 Linguistic Inquiry and Word Count (LIWC),在研究的前四个月内从论坛上提取语言使用模式。参与者在 4、8 和 12 个月时通过调查报告他们的危险饮酒发生率。建立了一个逻辑回归模型,根据语言使用情况预测个体在一年内进行危险饮酒的可能性,同时控制基线特征和使用移动系统的比率。结果表明,所有基线特征和系统使用因素仅解释了复发方差的 13%,而一些语言线索,包括咒骂和认知机制词,解释了模型中复发总方差的 45%的另外 32%。需要有效的复发预测模型。在 AUD 论坛上交换的信息可以为 AUD 患者的未来健康结果及其心理基础提供一个不引人注目的、具有成本效益的窗口。随着在线交流的扩大,利用用户提交的文本预测复发的模型将越来越具有可扩展性和可操作性。