Eberhardt Steffen T, Schaffrath Jana, Moggia Danilo, Schwartz Brian, Jaehde Martin, Rubel Julian A, Baur Tobias, André Elisabeth, Lutz Wolfgang
Trier University, Trier, Germany.
Osnabrück University, Osnabrück, Germany.
Psychother Res. 2025 Feb;35(2):174-189. doi: 10.1080/10503307.2024.2322522. Epub 2024 Feb 28.
Given the importance of emotions in psychotherapy, valid measures are essential for research and practice. As emotions are expressed at different levels, multimodal measurements are needed for a nuanced assessment. Natural Language Processing (NLP) could augment the measurement of emotions. The study explores the validity of sentiment analysis in psychotherapy transcripts.
We used a transformer-based NLP algorithm to analyze sentiments in 85 transcripts from 35 patients. Construct and criterion validity were evaluated using self- and therapist reports and process and outcome measures via correlational, multitrait-multimethod, and multilevel analyses.
The results provide indications in support of the sentiments' validity. For example, sentiments were significantly related to self- and therapist reports of emotions in the same session. Sentiments correlated significantly with in-session processes (e.g., coping experiences), and an increase in positive sentiments throughout therapy predicted better outcomes after treatment termination.
Sentiment analysis could serve as a valid approach to assessing the emotional tone of psychotherapy sessions and may contribute to the multimodal measurement of emotions. Future research could combine sentiment analysis with automatic emotion recognition in facial expressions and vocal cues via the Nonverbal Behavior Analyzer (NOVA). Limitations (e.g., exploratory study with numerous tests) and opportunities are discussed.
鉴于情绪在心理治疗中的重要性，有效的测量方法对于研究和实践至关重要。由于情绪在不同层面表达，因此需要多模态测量来进行细致入微的评估。自然语言处理（NLP）可以增强对情绪的测量。本研究探讨了心理治疗记录中情感分析的有效性。
我们使用基于Transformer的NLP算法分析了35名患者的85份记录中的情感。通过相关性分析、多特质多方法分析和多层次分析，使用自我报告和治疗师报告以及过程和结果测量来评估结构效度和效标效度。
结果为支持情感的有效性提供了依据。例如，情感与同一会话中自我和治疗师的情绪报告显著相关。情感与会话过程（如应对经历）显著相关，并且整个治疗过程中积极情感的增加预示着治疗结束后会有更好的结果。
情感分析可以作为评估心理治疗会话情绪基调的有效方法，并可能有助于情绪的多模态测量。未来的研究可以通过非言语行为分析器（NOVA）将情感分析与面部表情和声音线索中的自动情绪识别相结合。讨论了局限性（如进行了大量测试的探索性研究）和机遇。
