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Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing

BACKGROUND: The sheer number of measures evaluating mobility and inconsistencies in terminology make it challenging to extract potential core domains and items. Automating a portion of the data synthesis would allow us to cover a much larger volume of studies and databases in a smaller fraction of t...

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Autores principales: Alhasani, Rehab, Godbout, Mathieu, Durand, Audrey, Auger, Claudine, Lamontagne, Anouk, Ahmed, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733317/
https://www.ncbi.nlm.nih.gov/pubmed/36494770
http://dx.doi.org/10.1186/s12883-022-02938-1
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author Alhasani, Rehab
Godbout, Mathieu
Durand, Audrey
Auger, Claudine
Lamontagne, Anouk
Ahmed, Sara
author_facet Alhasani, Rehab
Godbout, Mathieu
Durand, Audrey
Auger, Claudine
Lamontagne, Anouk
Ahmed, Sara
author_sort Alhasani, Rehab
collection PubMed
description BACKGROUND: The sheer number of measures evaluating mobility and inconsistencies in terminology make it challenging to extract potential core domains and items. Automating a portion of the data synthesis would allow us to cover a much larger volume of studies and databases in a smaller fraction of the time compared to the usual process. Thus, the objective of this study was to identify a comprehensive outcome set and develop preliminary banks of items of mobility among individuals with acquired brain injury (ABI) using Natural Language Processing (NLP). METHODS: An umbrella review of 47 reviews evaluating the content of mobility measures among individuals with ABI was conducted. A search was performed on 5 databases between 2000 and 2020. Two independent reviewers retrieved copies of the measures and extracted mobility domains and items. A pre-trained BERT model (state-of-the-art model for NLP) provided vector representations for each sentence. Using the International Classification of Functioning, Disability, and Health Framework (ICF) ontology as a guide for clustering, a k-means algorithm was used to retrieve clusters of similar sentences from their embeddings. The resulting embedding clusters were evaluated using the Silhouette score and fine-tuned according to expert input. RESULTS: The study identified 246 mobility measures, including 474 domains and 2109 items. Encoding the clusters using the ICF ontology and expert knowledge helped in regrouping the items in a way that is more closely related to mobility terminology. Our best results identified banks of items that were used to create a 24 comprehensive outcome sets of mobility, including Upper Extremity Mobility, Emotional Function, Balance, Motor Control, Self-care, Social Life and Relationships, Cognition, Walking, Postural Transition, Recreation, and Leisure Activities, Activities of Daily Living, Physical Functioning, Communication, Work/Study, Climbing, Sensory Functions, General Health, Fatigue, Functional Independence, Pain, Alcohol and Drugs Use, Transportation, Sleeping, and Finances. CONCLUSION: The banks of items of mobility domains represent a first step toward establishing a comprehensive outcome set and a common language of mobility to develop the ontology. It enables researchers and healthcare professionals to begin exposing the content of mobility measures as a way to assess mobility comprehensively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12883-022-02938-1.
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spelling pubmed-97333172022-12-10 Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing Alhasani, Rehab Godbout, Mathieu Durand, Audrey Auger, Claudine Lamontagne, Anouk Ahmed, Sara BMC Neurol Research Article BACKGROUND: The sheer number of measures evaluating mobility and inconsistencies in terminology make it challenging to extract potential core domains and items. Automating a portion of the data synthesis would allow us to cover a much larger volume of studies and databases in a smaller fraction of the time compared to the usual process. Thus, the objective of this study was to identify a comprehensive outcome set and develop preliminary banks of items of mobility among individuals with acquired brain injury (ABI) using Natural Language Processing (NLP). METHODS: An umbrella review of 47 reviews evaluating the content of mobility measures among individuals with ABI was conducted. A search was performed on 5 databases between 2000 and 2020. Two independent reviewers retrieved copies of the measures and extracted mobility domains and items. A pre-trained BERT model (state-of-the-art model for NLP) provided vector representations for each sentence. Using the International Classification of Functioning, Disability, and Health Framework (ICF) ontology as a guide for clustering, a k-means algorithm was used to retrieve clusters of similar sentences from their embeddings. The resulting embedding clusters were evaluated using the Silhouette score and fine-tuned according to expert input. RESULTS: The study identified 246 mobility measures, including 474 domains and 2109 items. Encoding the clusters using the ICF ontology and expert knowledge helped in regrouping the items in a way that is more closely related to mobility terminology. Our best results identified banks of items that were used to create a 24 comprehensive outcome sets of mobility, including Upper Extremity Mobility, Emotional Function, Balance, Motor Control, Self-care, Social Life and Relationships, Cognition, Walking, Postural Transition, Recreation, and Leisure Activities, Activities of Daily Living, Physical Functioning, Communication, Work/Study, Climbing, Sensory Functions, General Health, Fatigue, Functional Independence, Pain, Alcohol and Drugs Use, Transportation, Sleeping, and Finances. CONCLUSION: The banks of items of mobility domains represent a first step toward establishing a comprehensive outcome set and a common language of mobility to develop the ontology. It enables researchers and healthcare professionals to begin exposing the content of mobility measures as a way to assess mobility comprehensively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12883-022-02938-1. BioMed Central 2022-12-09 /pmc/articles/PMC9733317/ /pubmed/36494770 http://dx.doi.org/10.1186/s12883-022-02938-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Alhasani, Rehab
Godbout, Mathieu
Durand, Audrey
Auger, Claudine
Lamontagne, Anouk
Ahmed, Sara
Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing
title Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing
title_full Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing
title_fullStr Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing
title_full_unstemmed Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing
title_short Informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing
title_sort informing the development of an outcome set and banks of items to measure mobility among individuals with acquired brain injury using natural language processing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9733317/
https://www.ncbi.nlm.nih.gov/pubmed/36494770
http://dx.doi.org/10.1186/s12883-022-02938-1
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