Background: Behavioral activation (BA) is rooted in the behavioral theory of depression, which states that increased exposure to meaningful, rewarding activities is a critical factor in the treatment of depression. Assessing constructs relevant to BA currently requires the administration of standardized instruments, such as the Behavioral Activation for Depression Scale (BADS), which places a burden on patients and providers, among other potential limitations. Previous work has shown that depressed and nondepressed individuals may use language differently and that automated tools can detect these differences. The increasing use of online, chat-based mental health counseling presents an unparalleled resource for automated longitudinal linguistic analysis of patients with depression, with the potential to illuminate the role of reward exposure in recovery. Objective: This work investigated how linguistic indicators of planning and participation in enjoyable activities identified in online, text-based counseling sessions relate to depression symptomatology over time. Methods: Using distributional semantics methods applied to a large corpus of text-based online therapy sessions, we devised a set of novel BA-related categories for the Linguistic Inquiry and Word Count (LIWC) software package. We then analyzed the language used by 10,000 patients in online therapy chat logs for indicators of activation and other depression-related markers using LIWC. Results: Despite their conceptual and operational differences, both previously established LIWC markers of depression and our novel linguistic indicators of activation were strongly associated with depression scores (Patient Health Questionnaire [PHQ]-9) and longitudinal patient trajectories. Emotional tone; pronoun rates; words related to sadness, health, and biology; and BA-related LIWC categories appear to be complementary, explaining more of the variance in the PHQ score together than they do independently. Conclusions: This study enables further work in automated diagnosis and assessment of depression, the refinement of BA psychotherapeutic strategies, and the development of predictive models for decision support.

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中文翻译：

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行为激活和抑郁症状学：基于文本的治疗会话中语言指标的纵向评估

背景：行为激活（BA）植根于抑郁症的行为理论，该理论指出，增加接触有意义、有益的活动是治疗抑郁症的关键因素。评估与 BA 相关的构建目前需要使用标准化工具，例如抑郁行为激活量表 (BADS)，这给患者和提供者带来了负担，以及其他潜在的限制。先前的研究表明，抑郁症和非抑郁症患者使用语言的方式可能有所不同，并且自动化工具可以检测到这些差异。基于聊天的在线心理健康咨询的使用越来越多，为抑郁症患者的自动纵向语言分析提供了无与伦比的资源，并有可能阐明奖励暴露在康复中的作用。目的：这项工作调查了在线文本咨询课程中确定的计划和参与愉快活动的语言指标如何随着时间的推移与抑郁症症状相关。方法：使用分布式语义方法应用于基于文本的在线治疗会话的大型语料库，我们为语言查询和字数统计（LIWC）软件包设计了一组新颖的 BA 相关类别。然后，我们使用 LIWC 分析了 10,000 名患者在在线治疗聊天日志中使用的语言，以了解激活指标和其他抑郁相关标记。结果：尽管概念和操作上存在差异，但先前建立的抑郁症 LIWC 标记和我们新的激活语言指标均与抑郁评分（患者健康问卷 [PHQ]-9）和纵向患者轨迹密切相关。情绪基调；代词率；与悲伤、健康和生物学相关的词语；与 BA 相关的 LIWC 类别似乎是互补的，共同解释 PHQ 分数的方差比单独解释更多。结论：这项研究有助于进一步开展抑郁症的自动诊断和评估、BA 心理治疗策略的完善以及决策支持预测模型的开发。

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