Novel Use of Natural Language Processing (NLP) to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid
Joint Authors
Cook, Benjamin L.
Progovac, Ana M.
Chen, Pei
Mullin, Brian
Hou, Sherry
Baca-García, Enrique
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-26
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Natural language processing (NLP) and machine learning were used to predict suicidal ideation and heightened psychiatric symptoms among adults recently discharged from psychiatric inpatient or emergency room settings in Madrid, Spain.
Participants responded to structured mental and physical health instruments at multiple follow-up points.
Outcome variables of interest were suicidal ideation and psychiatric symptoms (GHQ-12).
Predictor variables included structured items (e.g., relating to sleep and well-being) and responses to one unstructured question, “how do you feel today?” We compared NLP-based models using the unstructured question with logistic regression prediction models using structured data.
The PPV, sensitivity, and specificity for NLP-based models of suicidal ideation were 0.61, 0.56, and 0.57, respectively, compared to 0.73, 0.76, and 0.62 of structured data-based models.
The PPV, sensitivity, and specificity for NLP-based models of heightened psychiatric symptoms (GHQ-12 ≥ 4) were 0.56, 0.59, and 0.60, respectively, compared to 0.79, 0.79, and 0.85 in structured models.
NLP-based models were able to generate relatively high predictive values based solely on responses to a simple general mood question.
These models have promise for rapidly identifying persons at risk of suicide or psychological distress and could provide a low-cost screening alternative in settings where lengthy structured item surveys are not feasible.
American Psychological Association (APA)
Cook, Benjamin L.& Progovac, Ana M.& Chen, Pei& Mullin, Brian& Hou, Sherry& Baca-García, Enrique. 2016. Novel Use of Natural Language Processing (NLP) to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid. Computational and Mathematical Methods in Medicine،Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100215
Modern Language Association (MLA)
Cook, Benjamin L.…[et al.]. Novel Use of Natural Language Processing (NLP) to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid. Computational and Mathematical Methods in Medicine No. 2016 (2016), pp.1-8.
https://search.emarefa.net/detail/BIM-1100215
American Medical Association (AMA)
Cook, Benjamin L.& Progovac, Ana M.& Chen, Pei& Mullin, Brian& Hou, Sherry& Baca-García, Enrique. Novel Use of Natural Language Processing (NLP) to Predict Suicidal Ideation and Psychiatric Symptoms in a Text-Based Mental Health Intervention in Madrid. Computational and Mathematical Methods in Medicine. 2016. Vol. 2016, no. 2016, pp.1-8.
https://search.emarefa.net/detail/BIM-1100215
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1100215