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Social listening – revealing Parkinson’s disease over day and night
BACKGROUND: Nocturnal symptoms in Parkinson’s disease are often treated after management of daytime manifestations. In order to better understand the unmet needs of nocturnal symptoms management, we analyzed the characteristics and burden of nocturnal symptoms from patients’ perspectives and explore...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780378/ https://www.ncbi.nlm.nih.gov/pubmed/33397315 http://dx.doi.org/10.1186/s12883-020-02024-4 |
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author | Zhang, Hui Meng, Fanwen Li, Xingyu Ning, Yali Cai, Meng |
author_facet | Zhang, Hui Meng, Fanwen Li, Xingyu Ning, Yali Cai, Meng |
author_sort | Zhang, Hui |
collection | PubMed |
description | BACKGROUND: Nocturnal symptoms in Parkinson’s disease are often treated after management of daytime manifestations. In order to better understand the unmet needs of nocturnal symptoms management, we analyzed the characteristics and burden of nocturnal symptoms from patients’ perspectives and explored their changes over time. Overall symptoms (occurring at day or night) were collected to compare whether the unmet needs related to nocturnal symptoms and to overall symptoms are different. METHODS: We used a Social Listening big-data technique to analyze large amounts of Parkinson’s disease symptoms in dialogues available from social media platforms in 2016 to 2018. These symptoms were classified as either overall symptoms or nocturnal symptoms. We used share of voice (SOV) of symptoms as a proportion of total dialogues per year to reflect the characteristics of symptoms. Negative sentiment score of symptoms was analyzed to find out their related burden. RESULTS: We found the SOV for overall motor symptoms was 79% and had not increased between 2016 and 2018 (79%, p = 0.5). The SOV for non-motor symptoms was 69% and had grown by 7% in 2018 (p < 0.01). The SOV for motor complications was 9% and had increased by 6% in 2018 (p < 0.01). The SOV of motor symptoms was larger than non-motor symptoms and motor complications (p < 0.01). The SOV of non-motor symptoms was larger than motor complications (p < 0.01). For nocturnal symptoms, 45% of the analyzed PD population reported nocturnal symptoms in 2018, growing by 6% (p < 0.01). The SOV for nocturnal-occurring motor symptoms was higher than most non-motor symptoms. However, non-motor symptoms had the higher increases and evoked higher negative sentiment regardless of whether they occurred during the day or night. For symptoms that can occur at either day or night, each nocturnal symptom was rated with a higher negative sentiment score than the same symptom during the day. CONCLUSIONS: The growing SOV and the greater negative sentiment of nocturnal symptoms suggest management of nocturnal symptoms is an unmet need of patients. A greater emphasis on detecting and treating nocturnal symptoms with 24-h care is encouraged. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12883-020-02024-4. |
format | Online Article Text |
id | pubmed-7780378 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77803782021-01-05 Social listening – revealing Parkinson’s disease over day and night Zhang, Hui Meng, Fanwen Li, Xingyu Ning, Yali Cai, Meng BMC Neurol Research Article BACKGROUND: Nocturnal symptoms in Parkinson’s disease are often treated after management of daytime manifestations. In order to better understand the unmet needs of nocturnal symptoms management, we analyzed the characteristics and burden of nocturnal symptoms from patients’ perspectives and explored their changes over time. Overall symptoms (occurring at day or night) were collected to compare whether the unmet needs related to nocturnal symptoms and to overall symptoms are different. METHODS: We used a Social Listening big-data technique to analyze large amounts of Parkinson’s disease symptoms in dialogues available from social media platforms in 2016 to 2018. These symptoms were classified as either overall symptoms or nocturnal symptoms. We used share of voice (SOV) of symptoms as a proportion of total dialogues per year to reflect the characteristics of symptoms. Negative sentiment score of symptoms was analyzed to find out their related burden. RESULTS: We found the SOV for overall motor symptoms was 79% and had not increased between 2016 and 2018 (79%, p = 0.5). The SOV for non-motor symptoms was 69% and had grown by 7% in 2018 (p < 0.01). The SOV for motor complications was 9% and had increased by 6% in 2018 (p < 0.01). The SOV of motor symptoms was larger than non-motor symptoms and motor complications (p < 0.01). The SOV of non-motor symptoms was larger than motor complications (p < 0.01). For nocturnal symptoms, 45% of the analyzed PD population reported nocturnal symptoms in 2018, growing by 6% (p < 0.01). The SOV for nocturnal-occurring motor symptoms was higher than most non-motor symptoms. However, non-motor symptoms had the higher increases and evoked higher negative sentiment regardless of whether they occurred during the day or night. For symptoms that can occur at either day or night, each nocturnal symptom was rated with a higher negative sentiment score than the same symptom during the day. CONCLUSIONS: The growing SOV and the greater negative sentiment of nocturnal symptoms suggest management of nocturnal symptoms is an unmet need of patients. A greater emphasis on detecting and treating nocturnal symptoms with 24-h care is encouraged. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12883-020-02024-4. BioMed Central 2021-01-04 /pmc/articles/PMC7780378/ /pubmed/33397315 http://dx.doi.org/10.1186/s12883-020-02024-4 Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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 Zhang, Hui Meng, Fanwen Li, Xingyu Ning, Yali Cai, Meng Social listening – revealing Parkinson’s disease over day and night |
title | Social listening – revealing Parkinson’s disease over day and night |
title_full | Social listening – revealing Parkinson’s disease over day and night |
title_fullStr | Social listening – revealing Parkinson’s disease over day and night |
title_full_unstemmed | Social listening – revealing Parkinson’s disease over day and night |
title_short | Social listening – revealing Parkinson’s disease over day and night |
title_sort | social listening – revealing parkinson’s disease over day and night |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7780378/ https://www.ncbi.nlm.nih.gov/pubmed/33397315 http://dx.doi.org/10.1186/s12883-020-02024-4 |
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