Towards Intelligent Clinically-Informed Language Analyses of People with Bipolar Disorder and Schizophrenia

Ankit Aich, Avery Quynh, Varsha Badal, Amy Pinkham, Philip Harvey, Colin Depp, Natalie Parde


Abstract
NLP offers a myriad of opportunities to support mental health research. However, prior work has almost exclusively focused on social media data, for which diagnoses are difficult or impossible to validate. We present a first-of-its-kind dataset of manually transcribed interactions with people clinically diagnosed with bipolar disorder and schizophrenia, as well as healthy controls. Data was collected through validated clinical tasks and paired with diagnostic measures. We extract 100+ temporal, sentiment, psycholinguistic, emotion, and lexical features from the data and establish classification validity using a variety of models to study language differences between diagnostic groups. Our models achieve strong classification performance (maximum F1=0.93-0.96), and lead to the discovery of interesting associations between linguistic features and diagnostic class. It is our hope that this dataset will offer high value to clinical and NLP researchers, with potential for widespread broader impacts.
Anthology ID:
2022.findings-emnlp.208
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2022
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2871–2887
Language:
URL:
https://aclanthology.org/2022.findings-emnlp.208
DOI:
10.18653/v1/2022.findings-emnlp.208
Bibkey:
Cite (ACL):
Ankit Aich, Avery Quynh, Varsha Badal, Amy Pinkham, Philip Harvey, Colin Depp, and Natalie Parde. 2022. Towards Intelligent Clinically-Informed Language Analyses of People with Bipolar Disorder and Schizophrenia. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 2871–2887, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
Towards Intelligent Clinically-Informed Language Analyses of People with Bipolar Disorder and Schizophrenia (Aich et al., Findings 2022)
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PDF:
https://aclanthology.org/2022.findings-emnlp.208.pdf
Note:
 2022.findings-emnlp.208.note.pdf