Identifying Symptom Clusters in Women Experiencing Preterm Birth

Ting He; Casey Overby

doi:10.1145/3233547.3233629

Identifying Symptom Clusters in Women Experiencing Preterm Birth

Ting He, Casey Overby

School of Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Preterm birth affected about 10% infants born in the U.S. in 2016. This project was a secondary analysis of data drawn from a preterm birth prediction study to assess whether psychological symptom clusters exist among pregnant women. A symptom cluster exists when two or more symptoms co-occur, are related to each other, and are stable. We found one psychological symptom pair that satisfied these conditions: anxiety & self-esteem. This finding has potential to help guide symptom assessment among pregnant women.

Original language	English (US)
Title of host publication	ACM-BCB 2018 - Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
Publisher	Association for Computing Machinery, Inc
Number of pages	1
ISBN (Electronic)	9781450357944
DOIs	https://doi.org/10.1145/3233547.3233629
State	Published - Aug 15 2018
Event	9th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2018 - Washington, United States Duration: Aug 29 2018 → Sep 1 2018

Other

Other	9th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2018
Country/Territory	United States
City	Washington
Period	8/29/18 → 9/1/18

Keywords

Correlation
Preterm birth
Symptom clusters

ASJC Scopus subject areas

Computer Science Applications
Software
Health Informatics
Biomedical Engineering

Access to Document

10.1145/3233547.3233629

Cite this

He, T & Overby, C 2018, Identifying Symptom Clusters in Women Experiencing Preterm Birth. in ACM-BCB 2018 - Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. Association for Computing Machinery, Inc, 9th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM-BCB 2018, Washington, United States, 8/29/18. https://doi.org/10.1145/3233547.3233629

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AB - Preterm birth affected about 10% infants born in the U.S. in 2016. This project was a secondary analysis of data drawn from a preterm birth prediction study to assess whether psychological symptom clusters exist among pregnant women. A symptom cluster exists when two or more symptoms co-occur, are related to each other, and are stable. We found one psychological symptom pair that satisfied these conditions: anxiety & self-esteem. This finding has potential to help guide symptom assessment among pregnant women.

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Y2 - 29 August 2018 through 1 September 2018

ER -

Identifying Symptom Clusters in Women Experiencing Preterm Birth

Abstract

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Keywords

ASJC Scopus subject areas

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