Background

Recent research on artificial intelligence has demonstrated that natural language can be used to provide valid indicators of psychopathology. The present study examined artificial intelligence-based language predictors (ALPs) of seven trauma-related mental and physical health outcomes in responders to the World Trade Center disaster.

Methods

The responders (N = 174, M_age = 55.4 years) provided daily voicemail updates over 14 days. Algorithms developed using machine learning in large social media discovery samples were applied to the voicemail transcriptions to derive ALP scores for several risk factors (depressivity, anxiousness, anger proneness, stress, and personality). Responders also completed self-report assessments of these risk factors at baseline and trauma-related mental and physical health outcomes at two-year follow-up (including symptoms of depression, posttraumatic stress disorder, sleep disturbance, respiratory problems, and GERD).

Results

Voicemail ALPs were significantly associated with a majority of the trauma-related outcomes at two-year follow-up, over and above corresponding baseline self-reports. ALPs showed significant convergence with corresponding self-report scales, but also considerable uniqueness from each other and from self-report scales.

Limitations

The study has a relatively short follow-up period relative to trauma occurrence and a limited sample size.

Conclusions

This study shows evidence that ALPs may provide a novel, objective, and clinically useful approach to forecasting, and may in the future help to identify individuals at risk for negative health outcomes.

中文翻译：

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两年创伤相关结果的人工智能语言预测因子

 背景

最近的人工智能研究表明，自然语言可以用来提供有效的精神病理学指标。本研究检查了基于人工智能的语言预测器（ALP），对世贸中心灾难响应者的七种与创伤相关的心理和身体健康结果进行了研究。

 方法

响应者（ N = 174， M_年龄= 55.4 岁）提供了 14 天内的每日语音邮件更新。在大型社交媒体发现样本中使用机器学习开发的算法被应用于语音邮件转录，以得出多种风险因素（抑郁、焦虑、易怒、压力和个性）的 ALP 分数。应答者还完成了对这些基线风险因素的自我报告评估，以及两年随访时与创伤相关的心理和身体健康结果（包括抑郁症状、创伤后应激障碍、睡眠障碍、呼吸问题和胃食管反流病）。

 结果

在两年的随访中，语音信箱 ALP 与大多数创伤相关结果显着相关，超出了相应的基线自我报告。 ALP 与相应的自我报告量表表现出显着的趋同性，但彼此之间以及自我报告量表也有相当大的独特性。

 局限性

该研究相对于创伤发生的随访期相对较短，且样本量有限。

 结论

这项研究表明，ALP 可能提供一种新颖、客观且在临床上有用的预测方法，并且可能在未来帮助识别面临负面健康结果风险的个人。