Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling
Objective There is a paucity of research examining patient experiences of cochlear implants. We sought to use natural language processing methods to explore patient experiences and concerns in the online cochlear implant (CI) community. Materials and Methods Cross‐sectional study of posts on the onl...
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| Veröffentlicht in: | Clinical otolaryngology 2023-05, Vol.48 (3), p.442-450 |
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| container_title | Clinical otolaryngology |
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| creator | Williams, Christopher Y. K. Li, Rosia X. Luo, Michael Y. Bance, Manohar |
| description | Objective
There is a paucity of research examining patient experiences of cochlear implants. We sought to use natural language processing methods to explore patient experiences and concerns in the online cochlear implant (CI) community.
Materials and Methods
Cross‐sectional study of posts on the online Reddit r/CochlearImplants forum from 1 March 2015 to 11 November 2021. Natural language processing using the BERTopic automated topic modelling technique was employed to cluster posts into semantically similar topics. Topic categorisation was manually validated by two independent reviewers and Cohen's kappa calculated to determine inter‐rater reliability between machine vs human and human vs human categorisation.
Results
We retrieved 987 posts from 588 unique Reddit users on the r/CochlearImplants forum. Posts were initially categorised by BERTopic into 16 different Topics, which were increased to 23 Topics following manual inspection. The most popular topics related to CI connectivity (n = 112), adults considering getting a CI (n = 107), surgery‐related posts (n = 89) and day‐to‐day living with a CI (n = 85). Cohen's kappa among all posts was 0.62 (machine vs. human) and 0.72 (human vs. human), and among categorised posts was 0.85 (machine vs. human) and 0.84 (human vs. human).
Conclusions
This cross‐sectional study of social media discussions among the online cochlear implant community identified common attitudes, experiences and concerns of patients living with, or seeking, a cochlear implant. Our validation of natural language processing methods to categorise topics shows that automated analysis of similar Otolaryngology‐related content is a viable and accurate alternative to manual qualitative approaches. |
| doi_str_mv | 10.1111/coa.14037 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2766064251</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2801802409</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3487-ebfd96128a0a2285d36d98d0bbe2ffb6eca4ea209af12412f4284d1d7ac851873</originalsourceid><addsrcrecordid>eNp1kc1uFSEYhonR2FpdeAOGxI0uTgsMh2HcnZzUn6RJN7qefAPftDQMjMBoz85LcO3leSXSc2oXJrLhDXl4-HkJecnZKa_jzEQ45ZI17SNyzFvZraTU6vFDbvUReZbzDWOyYS1_So4apeRaNO0x-XV-O_uYXLiiMxSHoVC8nTHVZDBTCJaaWGMKmbpAyzXSGLwLSLfRXHuERN00e6j7TJymJbiye0c31KSY8-8fPzOa4mIAT3NZ7G4v_AbeWbhbpnGksJQ4QUFLS5ydoVO06OsJV8_JkxF8xhf38wn58v788_bj6uLyw6ft5mJlGqnbFQ6j7RQXGhgIode2UbbTlg0DinEcFBqQCIJ1MHIhuRil0NJy24LRa67b5oS8OXjnFL8umEs_uWzqHSBgXHIvWqWYkmLNK_r6H_QmLqm-rlKacc2EZF2l3h6o_SckHPs5uQnSruesvyusr4X1-8Iq--reuAwT2gfyb0MVODsA353H3f9N_fZyc1D-Ae19o2k</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2801802409</pqid></control><display><type>article</type><title>Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Williams, Christopher Y. K. ; Li, Rosia X. ; Luo, Michael Y. ; Bance, Manohar</creator><creatorcontrib>Williams, Christopher Y. K. ; Li, Rosia X. ; Luo, Michael Y. ; Bance, Manohar</creatorcontrib><description>Objective
There is a paucity of research examining patient experiences of cochlear implants. We sought to use natural language processing methods to explore patient experiences and concerns in the online cochlear implant (CI) community.
Materials and Methods
Cross‐sectional study of posts on the online Reddit r/CochlearImplants forum from 1 March 2015 to 11 November 2021. Natural language processing using the BERTopic automated topic modelling technique was employed to cluster posts into semantically similar topics. Topic categorisation was manually validated by two independent reviewers and Cohen's kappa calculated to determine inter‐rater reliability between machine vs human and human vs human categorisation.
Results
We retrieved 987 posts from 588 unique Reddit users on the r/CochlearImplants forum. Posts were initially categorised by BERTopic into 16 different Topics, which were increased to 23 Topics following manual inspection. The most popular topics related to CI connectivity (n = 112), adults considering getting a CI (n = 107), surgery‐related posts (n = 89) and day‐to‐day living with a CI (n = 85). Cohen's kappa among all posts was 0.62 (machine vs. human) and 0.72 (human vs. human), and among categorised posts was 0.85 (machine vs. human) and 0.84 (human vs. human).
Conclusions
This cross‐sectional study of social media discussions among the online cochlear implant community identified common attitudes, experiences and concerns of patients living with, or seeking, a cochlear implant. Our validation of natural language processing methods to categorise topics shows that automated analysis of similar Otolaryngology‐related content is a viable and accurate alternative to manual qualitative approaches.</description><identifier>ISSN: 1749-4478</identifier><identifier>EISSN: 1749-4486</identifier><identifier>DOI: 10.1111/coa.14037</identifier><identifier>PMID: 36645237</identifier><language>eng</language><publisher>England: Wiley Subscription Services, Inc</publisher><subject>Adult ; Automation ; Cochlea ; cochlear implant ; Cochlear Implantation ; Cochlear Implants ; Cross-Sectional Studies ; Humans ; Inspection ; Language ; Modelling ; Natural language processing ; Otolaryngology ; patient experience ; Patient Outcome Assessment ; Reproducibility of Results ; topic modelling ; Transplants & implants</subject><ispartof>Clinical otolaryngology, 2023-05, Vol.48 (3), p.442-450</ispartof><rights>2023 The Authors. published by John Wiley & Sons Ltd.</rights><rights>2023 The Authors. Clinical Otolaryngology published by John Wiley & Sons Ltd.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3487-ebfd96128a0a2285d36d98d0bbe2ffb6eca4ea209af12412f4284d1d7ac851873</cites><orcidid>0000-0001-8867-1623 ; 0000-0001-8050-3617</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fcoa.14037$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fcoa.14037$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,1416,27922,27923,45572,45573</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36645237$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Williams, Christopher Y. K.</creatorcontrib><creatorcontrib>Li, Rosia X.</creatorcontrib><creatorcontrib>Luo, Michael Y.</creatorcontrib><creatorcontrib>Bance, Manohar</creatorcontrib><title>Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling</title><title>Clinical otolaryngology</title><addtitle>Clin Otolaryngol</addtitle><description>Objective
There is a paucity of research examining patient experiences of cochlear implants. We sought to use natural language processing methods to explore patient experiences and concerns in the online cochlear implant (CI) community.
Materials and Methods
Cross‐sectional study of posts on the online Reddit r/CochlearImplants forum from 1 March 2015 to 11 November 2021. Natural language processing using the BERTopic automated topic modelling technique was employed to cluster posts into semantically similar topics. Topic categorisation was manually validated by two independent reviewers and Cohen's kappa calculated to determine inter‐rater reliability between machine vs human and human vs human categorisation.
Results
We retrieved 987 posts from 588 unique Reddit users on the r/CochlearImplants forum. Posts were initially categorised by BERTopic into 16 different Topics, which were increased to 23 Topics following manual inspection. The most popular topics related to CI connectivity (n = 112), adults considering getting a CI (n = 107), surgery‐related posts (n = 89) and day‐to‐day living with a CI (n = 85). Cohen's kappa among all posts was 0.62 (machine vs. human) and 0.72 (human vs. human), and among categorised posts was 0.85 (machine vs. human) and 0.84 (human vs. human).
Conclusions
This cross‐sectional study of social media discussions among the online cochlear implant community identified common attitudes, experiences and concerns of patients living with, or seeking, a cochlear implant. Our validation of natural language processing methods to categorise topics shows that automated analysis of similar Otolaryngology‐related content is a viable and accurate alternative to manual qualitative approaches.</description><subject>Adult</subject><subject>Automation</subject><subject>Cochlea</subject><subject>cochlear implant</subject><subject>Cochlear Implantation</subject><subject>Cochlear Implants</subject><subject>Cross-Sectional Studies</subject><subject>Humans</subject><subject>Inspection</subject><subject>Language</subject><subject>Modelling</subject><subject>Natural language processing</subject><subject>Otolaryngology</subject><subject>patient experience</subject><subject>Patient Outcome Assessment</subject><subject>Reproducibility of Results</subject><subject>topic modelling</subject><subject>Transplants & implants</subject><issn>1749-4478</issn><issn>1749-4486</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp1kc1uFSEYhonR2FpdeAOGxI0uTgsMh2HcnZzUn6RJN7qefAPftDQMjMBoz85LcO3leSXSc2oXJrLhDXl4-HkJecnZKa_jzEQ45ZI17SNyzFvZraTU6vFDbvUReZbzDWOyYS1_So4apeRaNO0x-XV-O_uYXLiiMxSHoVC8nTHVZDBTCJaaWGMKmbpAyzXSGLwLSLfRXHuERN00e6j7TJymJbiye0c31KSY8-8fPzOa4mIAT3NZ7G4v_AbeWbhbpnGksJQ4QUFLS5ydoVO06OsJV8_JkxF8xhf38wn58v788_bj6uLyw6ft5mJlGqnbFQ6j7RQXGhgIode2UbbTlg0DinEcFBqQCIJ1MHIhuRil0NJy24LRa67b5oS8OXjnFL8umEs_uWzqHSBgXHIvWqWYkmLNK_r6H_QmLqm-rlKacc2EZF2l3h6o_SckHPs5uQnSruesvyusr4X1-8Iq--reuAwT2gfyb0MVODsA353H3f9N_fZyc1D-Ae19o2k</recordid><startdate>202305</startdate><enddate>202305</enddate><creator>Williams, Christopher Y. K.</creator><creator>Li, Rosia X.</creator><creator>Luo, Michael Y.</creator><creator>Bance, Manohar</creator><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>M7Z</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8867-1623</orcidid><orcidid>https://orcid.org/0000-0001-8050-3617</orcidid></search><sort><creationdate>202305</creationdate><title>Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling</title><author>Williams, Christopher Y. K. ; Li, Rosia X. ; Luo, Michael Y. ; Bance, Manohar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3487-ebfd96128a0a2285d36d98d0bbe2ffb6eca4ea209af12412f4284d1d7ac851873</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Adult</topic><topic>Automation</topic><topic>Cochlea</topic><topic>cochlear implant</topic><topic>Cochlear Implantation</topic><topic>Cochlear Implants</topic><topic>Cross-Sectional Studies</topic><topic>Humans</topic><topic>Inspection</topic><topic>Language</topic><topic>Modelling</topic><topic>Natural language processing</topic><topic>Otolaryngology</topic><topic>patient experience</topic><topic>Patient Outcome Assessment</topic><topic>Reproducibility of Results</topic><topic>topic modelling</topic><topic>Transplants & implants</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Williams, Christopher Y. K.</creatorcontrib><creatorcontrib>Li, Rosia X.</creatorcontrib><creatorcontrib>Luo, Michael Y.</creatorcontrib><creatorcontrib>Bance, Manohar</creatorcontrib><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biochemistry Abstracts 1</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical otolaryngology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Williams, Christopher Y. K.</au><au>Li, Rosia X.</au><au>Luo, Michael Y.</au><au>Bance, Manohar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling</atitle><jtitle>Clinical otolaryngology</jtitle><addtitle>Clin Otolaryngol</addtitle><date>2023-05</date><risdate>2023</risdate><volume>48</volume><issue>3</issue><spage>442</spage><epage>450</epage><pages>442-450</pages><issn>1749-4478</issn><eissn>1749-4486</eissn><abstract>Objective
There is a paucity of research examining patient experiences of cochlear implants. We sought to use natural language processing methods to explore patient experiences and concerns in the online cochlear implant (CI) community.
Materials and Methods
Cross‐sectional study of posts on the online Reddit r/CochlearImplants forum from 1 March 2015 to 11 November 2021. Natural language processing using the BERTopic automated topic modelling technique was employed to cluster posts into semantically similar topics. Topic categorisation was manually validated by two independent reviewers and Cohen's kappa calculated to determine inter‐rater reliability between machine vs human and human vs human categorisation.
Results
We retrieved 987 posts from 588 unique Reddit users on the r/CochlearImplants forum. Posts were initially categorised by BERTopic into 16 different Topics, which were increased to 23 Topics following manual inspection. The most popular topics related to CI connectivity (n = 112), adults considering getting a CI (n = 107), surgery‐related posts (n = 89) and day‐to‐day living with a CI (n = 85). Cohen's kappa among all posts was 0.62 (machine vs. human) and 0.72 (human vs. human), and among categorised posts was 0.85 (machine vs. human) and 0.84 (human vs. human).
Conclusions
This cross‐sectional study of social media discussions among the online cochlear implant community identified common attitudes, experiences and concerns of patients living with, or seeking, a cochlear implant. Our validation of natural language processing methods to categorise topics shows that automated analysis of similar Otolaryngology‐related content is a viable and accurate alternative to manual qualitative approaches.</abstract><cop>England</cop><pub>Wiley Subscription Services, Inc</pub><pmid>36645237</pmid><doi>10.1111/coa.14037</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-8867-1623</orcidid><orcidid>https://orcid.org/0000-0001-8050-3617</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Clinical otolaryngology, 2023-05, Vol.48 (3), p.442-450 |
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| language | eng |
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| source | MEDLINE; Wiley Online Library Journals Frontfile Complete |
| subjects | Adult Automation Cochlea cochlear implant Cochlear Implantation Cochlear Implants Cross-Sectional Studies Humans Inspection Language Modelling Natural language processing Otolaryngology patient experience Patient Outcome Assessment Reproducibility of Results topic modelling Transplants & implants |
| title | Exploring patient experiences and concerns in the online Cochlear implant community: A cross‐sectional study and validation of automated topic modelling |
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