Linguistic predictors from Facebook postings of substance use disorder treatment retention versus discontinuation.
Linguistic predictors from Facebook postings of substance use disorder treatment retention versus discontinuation.
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DOI：
10.1080/00952990.2022.2091450
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发表时间：
2022-09-03
影响因子：
2.7
通讯作者：
Curtis, Brenda
中科院分区：
文献类型：
--
作者：
Liu, Tingting;Giorgi, Salvatore;Yadeta, Kenna;Schwartz, H. Andrew;Ungar, Lyle H.;Curtis, Brenda
关键词：
谁将继续接受或离开药物使用障碍（SUD）治疗的早期指标可以推动有针对性的干预措施，以支持长期康复。为了对SUD治疗结果的语言标记进行全面研究，目前的研究整合了已知具有社会心理学相关性的机器学习模型产生的特征。我们从参与者进入SUD治疗计划前两年的Facebook帖子（N = 206，39.32%女性; 55，415个帖子）中提取并分析了语言特征。通过语言查询和单词计数（LIWC）和潜在狄利克雷分配（LDA）主题建模产生的探索性功能，以及通过建立基于AI的语言模型从宗教信仰，情感和时间取向的理论领域的功能被利用。接受SUD治疗超过90天的患者使用更多与宗教、积极情绪、家庭、从属关系和现在相关的词，并使用更多第一人称单数代词（科恩d值：[-0.39，-0.57]）。在90天前停止治疗的患者讨论的主题更多样化，关注过去，使用更多的文章（Cohen的d值：[0.44，0.57]）。所有ps <0.05，Benjamini-Hochberg错误发现率校正。我们在语言分析中证实了与SUD治疗相关的保护性和风险社会心理因素的文献，表明治疗进入前的Facebook语言可用于识别SUD治疗结果的标志物。这反映了在设计和推荐SUD治疗计划时考虑这些语言特征和标记的重要性。
Early indicators of who will remain in – or leave – treatment for substance use disorder (SUD) can drive targeted interventions to support long-term recovery. To conduct a comprehensive study of linguistic markers of SUD treatment outcomes, the current study integrated features produced by machine learning models known to have social-psychology relevance. We extracted and analyzed linguistic features from participants’ Facebook posts (N = 206, 39.32% female; 55,415 postings) over the two years before they entered a SUD treatment program. Exploratory features produced by both Linguistic Inquiry and Word Count (LIWC) and Latent Dirichlet Allocation (LDA) topic modeling and the features from theoretical domains of religiosity, affect, and temporal orientation via established AI-based linguistic models were utilized. Patients who stayed in the SUD treatment for over 90 days used more words associated with religion, positive emotions, family, affiliations, and the present, and used more first-person singular pronouns (Cohen’s d values: [−0.39, −0.57]). Patients who discontinued their treatment before 90 days discussed more diverse topics, focused on the past, and used more articles (Cohen’s d values: [0.44, 0.57]). All ps < .05 with Benjamini-Hochberg False Discovery Rate correction. We confirmed the literature on protective and risk social-psychological factors linking to SUD treatment in language analysis, showing that Facebook language before treatment entry could be used to identify the markers of SUD treatment outcomes. This reflects the importance of taking these linguistic features and markers into consideration when designing and recommending SUD treatment plans.
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影响因子：
2.8
作者：
Brancu, Mira;Jobes, David;Fratto, Timothy A.
通讯作者：
Fratto, Timothy A.
影响因子：
2.9
作者：
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DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
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通讯作者：
HOCHBERG, Y
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2
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影响因子：
6
作者：
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通讯作者：
Jordan, MI