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Language-based AI modeling of personality traits and pathology from life narrative interviews. 基于语言的人工智能对生活叙事访谈中人格特征和病理的建模。
IF 3.1 Q2 PSYCHIATRY Pub Date : 2026-01-01 Epub Date: 2025-09-29 DOI: 10.1037/abn0001047
Joshua R Oltmanns, Ritik Khandelwal, Jerry Ma, Jocelyn Brickman, Tu Do, Rasiq Hussain, Mehak Gupta

Advances in artificial intelligence (AI) hold promise for clarifying personality disorder (PD) models, research methodology, understanding, and clinical treatment. This study models personality and personality pathology using natural language. A representative community sample of N = 1,409 older adults from St. Louis (33% Black, 65% White, and 2% other) completed life narrative interviews lasting on average 20 min. Language from the interviews was then used to train and test language-based personality models on scores from the NEO-Personality Inventory-Revised and the Structured Interview for DSM-IV Personality. Criteria measures were used for multimethod construct validation of the language models including self-report measures of physical functioning and depressive symptoms and informant-report measures of personality, general health status, and social functioning. Language models were developed using fine-tuning of the parameters of the RoBERTa language model, BERTopic topic modeling, and Linguistic Inquiry and Word Count. Fine-tuned RoBERTa models predicted personality scores in testing data above r = .40, approaching what is considered a large effect size for convergent validity tests between two self-reports of the same construct. Life narrative language was more readily mapped onto the five-factor model trait domains than onto DSM PD categories, aside from moderate support for borderline pathology. The language-based five-factor model scores were supported by multimethod criteria correlations including informant-report personality scores in the testing data. Findings demonstrate the potential promise of language-based AI to refine conceptual frameworks of PD and provide automatic personality assessment and prediction in research and clinical practice. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

人工智能(AI)的进步有望澄清人格障碍(PD)模型、研究方法、理解和临床治疗。本研究使用自然语言对人格和人格病理进行建模。来自圣路易斯的代表性社区样本N = 1,409名老年人(33%黑人,65%白人,2%其他)完成了平均持续20分钟的生活叙述访谈。访谈中的语言随后被用于训练和测试基于语言的人格模型,这些模型的得分来自新人格量表修订和DSM-IV人格结构化访谈。标准测量用于语言模型的多方法结构验证,包括身体功能和抑郁症状的自我报告测量以及人格、一般健康状况和社会功能的举报人报告测量。语言模型是通过对RoBERTa语言模型、BERTopic主题建模和语言查询和单词计数的参数进行微调而开发的。经过微调的RoBERTa模型在r = 0.40以上的测试数据中预测人格分数,接近被认为是相同结构的两个自我报告之间的收敛效度测试的大效应量。除了对边缘性病理的适度支持外,生活叙事语言更容易映射到五因素模型特征域,而不是DSM PD类别。基于语言的五因素模型得分得到多方法标准相关性的支持,包括测试数据中的举报人-报告人格得分。研究结果表明,基于语言的人工智能有可能在研究和临床实践中完善PD的概念框架,并提供自动人格评估和预测。(PsycInfo Database Record (c) 2025 APA,版权所有)。
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引用次数: 0
The interplay of personality functioning and affect–event dynamics in predicting future impairment and depression: A large mobile mental health ambulatory assessment study. 人格功能和影响-事件动力学在预测未来障碍和抑郁中的相互作用:一项大型流动心理健康门诊评估研究。
Q2 PSYCHIATRY Pub Date : 2025-12-18 DOI: 10.1037/abn0001050
André Kerber, Johannes Zimmermann, Johannes C. Ehrenthal, Annette Brose, Tobias Nolte, Sebastian Burchert, Sophia Heinzmann, Ina Beintner, Christine Knaevelsrud
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引用次数: 0
Revitalizing personality disorder research. 重振人格障碍研究。
Q2 PSYCHIATRY Pub Date : 2025-12-18 DOI: 10.1037/abn0001064
Christopher J. Hopwood, Aleksandra Kaurin, Aaron L. Pincus
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引用次数: 0
Supplemental Material for The Interplay of Personality Functioning and Affect–Event Dynamics in Predicting Future Impairment and Depression: A Large Mobile Mental Health Ambulatory Assessment Study 人格功能和影响-事件动力学在预测未来损害和抑郁中的相互作用:一项大型流动心理健康门诊评估研究
Q2 PSYCHIATRY Pub Date : 2025-12-11 DOI: 10.1037/abn0001050.supp
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引用次数: 0
Day-level negative outcomes of failed control over drinking. 一天内无法控制饮酒的负面结果。
Q2 PSYCHIATRY Pub Date : 2025-12-11 DOI: 10.1037/abn0001093
Jennifer E. Merrill, Benjamin L. Berey, Elizabeth R. Aston, Holly K. Boyle, Olivia A. Belitsos, Nathan Didier
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引用次数: 0
The role of posttraumatic stress disorder symptoms in pain severity, interference, and variability after sexual assault: An ecological momentary assessment study. 创伤后应激障碍症状在性侵犯后疼痛严重程度、干扰和变异性中的作用:一项生态瞬时评估研究
Q2 PSYCHIATRY Pub Date : 2025-12-11 DOI: 10.1037/abn0001083
Nicole A. Short, Mattea Pezza, Lauren D. Reyes, Jenny Black, Karen Serrano, Samuel A. McLean
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引用次数: 0
Supplemental Material for The Role of Posttraumatic Stress Disorder Symptoms in Pain Severity, Interference, and Variability After Sexual Assault: An Ecological Momentary Assessment Study 性侵犯后创伤后应激障碍症状在疼痛严重程度、干扰和变异性中的作用:一项生态瞬时评估研究
Q2 PSYCHIATRY Pub Date : 2025-12-08 DOI: 10.1037/abn0001083.supp
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引用次数: 0
Supplemental Material for Day-Level Negative Outcomes of Failed Control Over Drinking 饮酒控制失败的日水平负面结果补充材料
Q2 PSYCHIATRY Pub Date : 2025-12-08 DOI: 10.1037/abn0001093.supp
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引用次数: 0
The effects of children’s state and trait empathy on the observational learning of fear. 儿童状态和特质共情对恐惧观察学习的影响。
Q2 PSYCHIATRY Pub Date : 2025-11-13 DOI: 10.1037/abn0000920
Chris Askew, Lauren Day, Charlotte Mills
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引用次数: 0
“Dark,” but useful: Why the term still matters—Commentary on Chester et al. (2025). “黑暗”,但有用:为什么这个词仍然重要——评论切斯特等人(2025)。
Q2 PSYCHIATRY Pub Date : 2025-11-03 DOI: 10.1037/abn0001075
Javier I. Borráz-León, Markus J. Rantala, Peter K. Jonason
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引用次数: 0
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Journal of psychopathology and clinical science
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