Cargando…
Application of latent semantic analysis for open-ended responses in a large, epidemiologic study
BACKGROUND: The Millennium Cohort Study is a longitudinal cohort study designed in the late 1990s to evaluate how military service may affect long-term health. The purpose of this investigation was to examine characteristics of Millennium Cohort Study participants who responded to the open-ended que...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3198753/ https://www.ncbi.nlm.nih.gov/pubmed/21974837 http://dx.doi.org/10.1186/1471-2288-11-136 |
_version_ | 1782214486403317760 |
---|---|
author | Leleu, Travis D Jacobson, Isabel G LeardMann, Cynthia A Smith, Besa Foltz, Peter W Amoroso, Paul J Derr, Marcia A Ryan, Margaret AK Smith, Tyler C |
author_facet | Leleu, Travis D Jacobson, Isabel G LeardMann, Cynthia A Smith, Besa Foltz, Peter W Amoroso, Paul J Derr, Marcia A Ryan, Margaret AK Smith, Tyler C |
author_sort | Leleu, Travis D |
collection | PubMed |
description | BACKGROUND: The Millennium Cohort Study is a longitudinal cohort study designed in the late 1990s to evaluate how military service may affect long-term health. The purpose of this investigation was to examine characteristics of Millennium Cohort Study participants who responded to the open-ended question, and to identify and investigate the most commonly reported areas of concern. METHODS: Participants who responded during the 2001-2003 and 2004-2006 questionnaire cycles were included in this study (n = 108,129). To perform these analyses, Latent Semantic Analysis (LSA) was applied to a broad open-ended question asking the participant if there were any additional health concerns. Multivariable logistic regression was performed to examine the adjusted odds of responding to the open-text field, and cluster analysis was executed to understand the major areas of concern for participants providing open-ended responses. RESULTS: Participants who provided information in the open-ended text field (n = 27,916), had significantly lower self-reported general health compared with those who did not provide information in the open-ended text field. The bulk of responses concerned a finite number of topics, most notably illness/injury, exposure, and exercise. CONCLUSION: These findings suggest generalized topic areas, as well as identify subgroups who are more likely to provide additional information in their response that may add insight into future epidemiologic and military research. |
format | Online Article Text |
id | pubmed-3198753 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31987532011-10-23 Application of latent semantic analysis for open-ended responses in a large, epidemiologic study Leleu, Travis D Jacobson, Isabel G LeardMann, Cynthia A Smith, Besa Foltz, Peter W Amoroso, Paul J Derr, Marcia A Ryan, Margaret AK Smith, Tyler C BMC Med Res Methodol Research Article BACKGROUND: The Millennium Cohort Study is a longitudinal cohort study designed in the late 1990s to evaluate how military service may affect long-term health. The purpose of this investigation was to examine characteristics of Millennium Cohort Study participants who responded to the open-ended question, and to identify and investigate the most commonly reported areas of concern. METHODS: Participants who responded during the 2001-2003 and 2004-2006 questionnaire cycles were included in this study (n = 108,129). To perform these analyses, Latent Semantic Analysis (LSA) was applied to a broad open-ended question asking the participant if there were any additional health concerns. Multivariable logistic regression was performed to examine the adjusted odds of responding to the open-text field, and cluster analysis was executed to understand the major areas of concern for participants providing open-ended responses. RESULTS: Participants who provided information in the open-ended text field (n = 27,916), had significantly lower self-reported general health compared with those who did not provide information in the open-ended text field. The bulk of responses concerned a finite number of topics, most notably illness/injury, exposure, and exercise. CONCLUSION: These findings suggest generalized topic areas, as well as identify subgroups who are more likely to provide additional information in their response that may add insight into future epidemiologic and military research. BioMed Central 2011-10-05 /pmc/articles/PMC3198753/ /pubmed/21974837 http://dx.doi.org/10.1186/1471-2288-11-136 Text en Copyright ©2011 Leleu et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Leleu, Travis D Jacobson, Isabel G LeardMann, Cynthia A Smith, Besa Foltz, Peter W Amoroso, Paul J Derr, Marcia A Ryan, Margaret AK Smith, Tyler C Application of latent semantic analysis for open-ended responses in a large, epidemiologic study |
title | Application of latent semantic analysis for open-ended responses in a large, epidemiologic study |
title_full | Application of latent semantic analysis for open-ended responses in a large, epidemiologic study |
title_fullStr | Application of latent semantic analysis for open-ended responses in a large, epidemiologic study |
title_full_unstemmed | Application of latent semantic analysis for open-ended responses in a large, epidemiologic study |
title_short | Application of latent semantic analysis for open-ended responses in a large, epidemiologic study |
title_sort | application of latent semantic analysis for open-ended responses in a large, epidemiologic study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3198753/ https://www.ncbi.nlm.nih.gov/pubmed/21974837 http://dx.doi.org/10.1186/1471-2288-11-136 |
work_keys_str_mv | AT leleutravisd applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy AT jacobsonisabelg applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy AT leardmanncynthiaa applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy AT smithbesa applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy AT foltzpeterw applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy AT amorosopaulj applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy AT derrmarciaa applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy AT ryanmargaretak applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy AT smithtylerc applicationoflatentsemanticanalysisforopenendedresponsesinalargeepidemiologicstudy |