Extracting big data from the internet to support the development of a new patient-reported outcome measure for breast implant illness: a proof of concept study.
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| Title: | Extracting big data from the internet to support the development of a new patient-reported outcome measure for breast implant illness: a proof of concept study. |
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| Authors: | Hu, Sophia (AUTHOR), Liu, Jinjie (AUTHOR), Cornacchi, Sylvie D. (AUTHOR), Klassen, Anne F. (AUTHOR), Pusic, Andrea L. (AUTHOR), Kaur, Manraj N. (AUTHOR) |
| Source: | Quality of Life Research. Jul2024, Vol. 33 Issue 7, p1975-1983. 9p. |
| Subjects: | Breast implants, Patient reported outcome measures, Internet forums, Big data, Proof of concept, Patient experience |
| Abstract: | Purpose: Individuals with health conditions often use online patient forums to share their experiences. These patient data are freely available and have rarely been used in patient-reported outcomes (PRO) research. Web scraping, the automated identification and coding of webpage data, can be employed to collect patient experiences for PRO research. The objective of this study was to assess the feasibility of using web scraping to support the development of a new PRO measure for breast implant illness (BII). Methods: Nine publicly available BII-specific web forums were chosen post-consultation with two prominent BII advocacy leaders. The Python Selenium and Pandas packages were used to automate extraction of de-identified text from the individual posts/comments into a spreadsheet. Data were coded using a line-by-line approach and constant comparison was used to create top-level domains and sub-domains. Results: 6362 unique codes were identified and organized into four top-level domains of information needs, symptom experiences, life impact of BII, and care experiences. Information needs of women included seeking/sharing information pre-breast implant surgery, post-breast implant surgery, while contemplating explant surgery, and post-explant surgery. Symptoms commonly described by women included fatigue, brain fog, and musculoskeletal symptoms. Many comments described BII's impact on daily activities and psychosocial wellbeing. Lastly, some comments described negative care experiences and experiences related to advocating for themselves to providers. Conclusion: This proof-of-concept study demonstrated the feasibility of employing web scraping as a cost-effective, efficient method to understand the experiences of women with BII. These data will be used to inform the development of a BII-specific PROM. [ABSTRACT FROM AUTHOR] |
| Copyright of Quality of Life Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 177877591 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Extracting big data from the internet to support the development of a new patient-reported outcome measure for breast implant illness: a proof of concept study. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hu%2C+Sophia%22">Hu, Sophia</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Jinjie%22">Liu, Jinjie</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cornacchi%2C+Sylvie+D%2E%22">Cornacchi, Sylvie D.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Klassen%2C+Anne+F%2E%22">Klassen, Anne F.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pusic%2C+Andrea+L%2E%22">Pusic, Andrea L.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kaur%2C+Manraj+N%2E%22">Kaur, Manraj N.</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Quality+of+Life+Research%22">Quality of Life Research</searchLink>. Jul2024, Vol. 33 Issue 7, p1975-1983. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Breast+implants%22">Breast implants</searchLink><br /><searchLink fieldCode="DE" term="%22Patient+reported+outcome+measures%22">Patient reported outcome measures</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+forums%22">Internet forums</searchLink><br /><searchLink fieldCode="DE" term="%22Big+data%22">Big data</searchLink><br /><searchLink fieldCode="DE" term="%22Proof+of+concept%22">Proof of concept</searchLink><br /><searchLink fieldCode="DE" term="%22Patient+experience%22">Patient experience</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: Individuals with health conditions often use online patient forums to share their experiences. These patient data are freely available and have rarely been used in patient-reported outcomes (PRO) research. Web scraping, the automated identification and coding of webpage data, can be employed to collect patient experiences for PRO research. The objective of this study was to assess the feasibility of using web scraping to support the development of a new PRO measure for breast implant illness (BII). Methods: Nine publicly available BII-specific web forums were chosen post-consultation with two prominent BII advocacy leaders. The Python Selenium and Pandas packages were used to automate extraction of de-identified text from the individual posts/comments into a spreadsheet. Data were coded using a line-by-line approach and constant comparison was used to create top-level domains and sub-domains. Results: 6362 unique codes were identified and organized into four top-level domains of information needs, symptom experiences, life impact of BII, and care experiences. Information needs of women included seeking/sharing information pre-breast implant surgery, post-breast implant surgery, while contemplating explant surgery, and post-explant surgery. Symptoms commonly described by women included fatigue, brain fog, and musculoskeletal symptoms. Many comments described BII's impact on daily activities and psychosocial wellbeing. Lastly, some comments described negative care experiences and experiences related to advocating for themselves to providers. Conclusion: This proof-of-concept study demonstrated the feasibility of employing web scraping as a cost-effective, efficient method to understand the experiences of women with BII. These data will be used to inform the development of a BII-specific PROM. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Quality of Life Research is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=177877591 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11136-024-03672-6 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 1975 Subjects: – SubjectFull: Breast implants Type: general – SubjectFull: Patient reported outcome measures Type: general – SubjectFull: Internet forums Type: general – SubjectFull: Big data Type: general – SubjectFull: Proof of concept Type: general – SubjectFull: Patient experience Type: general Titles: – TitleFull: Extracting big data from the internet to support the development of a new patient-reported outcome measure for breast implant illness: a proof of concept study. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hu, Sophia – PersonEntity: Name: NameFull: Liu, Jinjie – PersonEntity: Name: NameFull: Cornacchi, Sylvie D. – PersonEntity: Name: NameFull: Klassen, Anne F. – PersonEntity: Name: NameFull: Pusic, Andrea L. – PersonEntity: Name: NameFull: Kaur, Manraj N. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: Jul2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 09629343 Numbering: – Type: volume Value: 33 – Type: issue Value: 7 Titles: – TitleFull: Quality of Life Research Type: main |
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