A Framework for Applying Natural Language Processing in Digital Health Interventions.

Journal of Medical Internet Research
Burkhardt FunkC Barr Taylor

Abstract

Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources: (1) open correspondence between users and the trained practitioners supporting them through a messaging system and (2) text data recorded during the intervention by users, such as diary entries. Natural language processing (NLP) offers methods for analyzing text, augmenting the understanding of intervention effects, and informing therapeutic decision making. This study aimed to present a technical framework that supports the automated analysis of both types of text data often present in DHIs. This framework generates text features and helps to build statistical models to predict target variables, including user engagement, symptom change, and therapeutic outcomes. We first discussed various NLP techniques and demonstrated how they are implemented in the presented framework. We then applied the framework in a case study of the Healthy Body Image Program, a Web-based intervention trial for eating disorders (EDs). A total of 372 participants who screened positive for an ED received a DHI aimed at reducing ED psychopa...Continue Reading

References

Jun 7, 2011·Biomedical Informatics Insights·John PestianAntoon Leenaars
Aug 7, 2013·Clinical Psychology & Psychotherapy·Matthew PriceKenneth J Ruggiero
Jul 18, 2015·Science·Julia Hirschberg, Christopher D Manning
May 10, 2016·Current Diabetes Reports·Allison VorderstrasseConstance Johnson
Aug 20, 2016·IEEE Journal of Biomedical and Health Informatics·Mark HoogendoornPeter Szolovits
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Apr 5, 2019·Proceedings of the SIGCHI Conference on Human Factors in Computing Systems·Alicia L NoblesLaura E Barnes

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Citations

Nov 27, 2020·JMIR Mental Health·Shiri Sadeh-Sharvit, Steven D Hollon
Aug 28, 2021·International Journal of Environmental Research and Public Health·Ignacio Rodríguez-RodríguezDomingo-Javier Pardo-Quiles

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Software Mentioned

R package glmnet
Digital Health Interventions Text Analytics ( DHITA )
Hunspell
R
Word2Vec
SBED
DHITA
Apache OpenNLP library
LASSO
GloVe

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