Social Media Influence Does Not Reflect Scholarly or Clinical Activity in Real Life
BACKGROUND:Social media has become a major source of communication in medicine. We aimed to understand the relationship between physicians’ social media influence and their scholarly and clinical activity. METHODS:We identified attending US electrophysiologists on Twitter. We compared physician Twit...
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| Veröffentlicht in: | Circulation. Arrhythmia and electrophysiology 2020-11, Vol.13 (11), p.e008847-e008847 |
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| container_title | Circulation. Arrhythmia and electrophysiology |
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| creator | Zenger, Brian Swink, J. Michael Turner, Jeffrey L. Bunch, T. Jared Ryan, John J. Shah, Rashmee U. Turakhia, Mintu P. Piccini, Jonathan P. Steinberg, Benjamin A. |
| description | BACKGROUND:Social media has become a major source of communication in medicine. We aimed to understand the relationship between physicians’ social media influence and their scholarly and clinical activity.
METHODS:We identified attending US electrophysiologists on Twitter. We compared physician Twitter activity to (1) scholarly publication record (h-index) and (2) clinical volume according to Centers for Medicare and Medicaid Services. The ratio of observed versus expected (obs/exp) Twitter followers was calculated based on each scholarly (K-index) and clinical activity.
RESULTS:We identified 284 physicians, with mean Twitter age of 5.0 (SD, 3.1) years and median 568 followers (25th, 75th195, 1146). They had a median 34.5 peer-reviewed articles (25th, 75th14, 105), 401 citations (25th, 75th102, 1677), and h-index 9 (25th, 75th4, 19.8). The median K-index was 0.4 (25th, 75th0.15, 1.0), ranging from 0.0008 to 29.2. The median number of electrophysiology procedures was 77 (25th, 75th0, 160) and evaluation and management visits 264 (25th, 75th59, 516) in 2017. The top 1% electrophysiologists for followers accounted for 20% of all followers, 17% of status updates, had a mean h-index of 6 (versus 15 for others, P=0.3), and accounted for 1% of procedural and evaluation and management volumes. They had a mean K-index of 21 (versus 0.77 for others, P |
| doi_str_mv | 10.1161/CIRCEP.120.008847 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7674208</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2449262651</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4907-b3ee21402198cd2b556c5eaf1745f6d9f15a18a5557febaeac30cbdf55c7a8fb3</originalsourceid><addsrcrecordid>eNp9kVtv1DAQhSMEoqXwA3hBeeQly4wvubwgVaHASstFXXi2HO-YNXjjYiet9t9jlLaCl8qybI2_czyaUxQvEVaINb7p15f9xdcVMlgBtK1oHhWn2AmsOLTi8d0dRXdSPEvpJ0CNLdZPixPOIa8WTovtNhinffmJdk6X69H6mUZD5btAqfwcpvKSrCczlVuzD15HfyxDLHvvRmey7NxM7tpNx9KNmcyFjbP0vHhitU_04vY8K76_v_jWf6w2Xz6s-_NNZUQHTTVwIoYCGHat2bFBytpI0hYbIW296yxKja2WUjaWBk3acDDDzkppGt3agZ8Vbxffq3k40M7QOEXt1VV0Bx2PKmin_n8Z3V79CNeqqRvBoM0Gr28NYvg9U5rUwSVD3uuRwpwUE6JjNaslZhQX1MSQUiR7_w2C-huGWsJQOQy1hJE1r_7t715xN_0MyAW4CX6imH75-Yai2udBTvsHjcUDOkDOG9HxigEDRACo8oaG_wHZAKb-</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2449262651</pqid></control><display><type>article</type><title>Social Media Influence Does Not Reflect Scholarly or Clinical Activity in Real Life</title><source>MEDLINE</source><source>American Heart Association Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Zenger, Brian ; Swink, J. Michael ; Turner, Jeffrey L. ; Bunch, T. Jared ; Ryan, John J. ; Shah, Rashmee U. ; Turakhia, Mintu P. ; Piccini, Jonathan P. ; Steinberg, Benjamin A.</creator><creatorcontrib>Zenger, Brian ; Swink, J. Michael ; Turner, Jeffrey L. ; Bunch, T. Jared ; Ryan, John J. ; Shah, Rashmee U. ; Turakhia, Mintu P. ; Piccini, Jonathan P. ; Steinberg, Benjamin A.</creatorcontrib><description>BACKGROUND:Social media has become a major source of communication in medicine. We aimed to understand the relationship between physicians’ social media influence and their scholarly and clinical activity.
METHODS:We identified attending US electrophysiologists on Twitter. We compared physician Twitter activity to (1) scholarly publication record (h-index) and (2) clinical volume according to Centers for Medicare and Medicaid Services. The ratio of observed versus expected (obs/exp) Twitter followers was calculated based on each scholarly (K-index) and clinical activity.
RESULTS:We identified 284 physicians, with mean Twitter age of 5.0 (SD, 3.1) years and median 568 followers (25th, 75th195, 1146). They had a median 34.5 peer-reviewed articles (25th, 75th14, 105), 401 citations (25th, 75th102, 1677), and h-index 9 (25th, 75th4, 19.8). The median K-index was 0.4 (25th, 75th0.15, 1.0), ranging from 0.0008 to 29.2. The median number of electrophysiology procedures was 77 (25th, 75th0, 160) and evaluation and management visits 264 (25th, 75th59, 516) in 2017. The top 1% electrophysiologists for followers accounted for 20% of all followers, 17% of status updates, had a mean h-index of 6 (versus 15 for others, P=0.3), and accounted for 1% of procedural and evaluation and management volumes. They had a mean K-index of 21 (versus 0.77 for others, P<0.0001) and clinical obs/exp follower ratio of 17.9 and 18.1 for procedures and evaluation and management (P<0.001 each, versus others [0.81 for each]).
CONCLUSIONS:Electrophysiologists are active on Twitter, with modest influence often representative of scholarly and clinical activity. However, the most influential physicians appear to have relatively modest scholarly and clinical activity.</description><identifier>ISSN: 1941-3149</identifier><identifier>EISSN: 1941-3084</identifier><identifier>DOI: 10.1161/CIRCEP.120.008847</identifier><identifier>PMID: 33030380</identifier><language>eng</language><publisher>United States: American Heart Association, Inc</publisher><subject>Authorship ; Biomedical Research ; Cardiac Electrophysiology ; Electrophysiologic Techniques, Cardiac ; Humans ; Peer Influence ; Periodicals as Topic ; Scholarly Communication ; Social Media ; Workload</subject><ispartof>Circulation. Arrhythmia and electrophysiology, 2020-11, Vol.13 (11), p.e008847-e008847</ispartof><rights>American Heart Association, Inc.</rights><rights>2020 American Heart Association, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4907-b3ee21402198cd2b556c5eaf1745f6d9f15a18a5557febaeac30cbdf55c7a8fb3</citedby><cites>FETCH-LOGICAL-c4907-b3ee21402198cd2b556c5eaf1745f6d9f15a18a5557febaeac30cbdf55c7a8fb3</cites><orcidid>0000-0002-9203-5512 ; 0000-0002-7823-8540 ; 0000-0002-8546-9785 ; 0000-0001-5349-0136 ; 0000-0003-0772-2404 ; 0000-0001-8025-0904 ; 0000-0002-0039-9184 ; 0000-0002-4729-7820</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,3674,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33030380$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zenger, Brian</creatorcontrib><creatorcontrib>Swink, J. Michael</creatorcontrib><creatorcontrib>Turner, Jeffrey L.</creatorcontrib><creatorcontrib>Bunch, T. Jared</creatorcontrib><creatorcontrib>Ryan, John J.</creatorcontrib><creatorcontrib>Shah, Rashmee U.</creatorcontrib><creatorcontrib>Turakhia, Mintu P.</creatorcontrib><creatorcontrib>Piccini, Jonathan P.</creatorcontrib><creatorcontrib>Steinberg, Benjamin A.</creatorcontrib><title>Social Media Influence Does Not Reflect Scholarly or Clinical Activity in Real Life</title><title>Circulation. Arrhythmia and electrophysiology</title><addtitle>Circ Arrhythm Electrophysiol</addtitle><description>BACKGROUND:Social media has become a major source of communication in medicine. We aimed to understand the relationship between physicians’ social media influence and their scholarly and clinical activity.
METHODS:We identified attending US electrophysiologists on Twitter. We compared physician Twitter activity to (1) scholarly publication record (h-index) and (2) clinical volume according to Centers for Medicare and Medicaid Services. The ratio of observed versus expected (obs/exp) Twitter followers was calculated based on each scholarly (K-index) and clinical activity.
RESULTS:We identified 284 physicians, with mean Twitter age of 5.0 (SD, 3.1) years and median 568 followers (25th, 75th195, 1146). They had a median 34.5 peer-reviewed articles (25th, 75th14, 105), 401 citations (25th, 75th102, 1677), and h-index 9 (25th, 75th4, 19.8). The median K-index was 0.4 (25th, 75th0.15, 1.0), ranging from 0.0008 to 29.2. The median number of electrophysiology procedures was 77 (25th, 75th0, 160) and evaluation and management visits 264 (25th, 75th59, 516) in 2017. The top 1% electrophysiologists for followers accounted for 20% of all followers, 17% of status updates, had a mean h-index of 6 (versus 15 for others, P=0.3), and accounted for 1% of procedural and evaluation and management volumes. They had a mean K-index of 21 (versus 0.77 for others, P<0.0001) and clinical obs/exp follower ratio of 17.9 and 18.1 for procedures and evaluation and management (P<0.001 each, versus others [0.81 for each]).
CONCLUSIONS:Electrophysiologists are active on Twitter, with modest influence often representative of scholarly and clinical activity. However, the most influential physicians appear to have relatively modest scholarly and clinical activity.</description><subject>Authorship</subject><subject>Biomedical Research</subject><subject>Cardiac Electrophysiology</subject><subject>Electrophysiologic Techniques, Cardiac</subject><subject>Humans</subject><subject>Peer Influence</subject><subject>Periodicals as Topic</subject><subject>Scholarly Communication</subject><subject>Social Media</subject><subject>Workload</subject><issn>1941-3149</issn><issn>1941-3084</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kVtv1DAQhSMEoqXwA3hBeeQly4wvubwgVaHASstFXXi2HO-YNXjjYiet9t9jlLaCl8qybI2_czyaUxQvEVaINb7p15f9xdcVMlgBtK1oHhWn2AmsOLTi8d0dRXdSPEvpJ0CNLdZPixPOIa8WTovtNhinffmJdk6X69H6mUZD5btAqfwcpvKSrCczlVuzD15HfyxDLHvvRmey7NxM7tpNx9KNmcyFjbP0vHhitU_04vY8K76_v_jWf6w2Xz6s-_NNZUQHTTVwIoYCGHat2bFBytpI0hYbIW296yxKja2WUjaWBk3acDDDzkppGt3agZ8Vbxffq3k40M7QOEXt1VV0Bx2PKmin_n8Z3V79CNeqqRvBoM0Gr28NYvg9U5rUwSVD3uuRwpwUE6JjNaslZhQX1MSQUiR7_w2C-huGWsJQOQy1hJE1r_7t715xN_0MyAW4CX6imH75-Yai2udBTvsHjcUDOkDOG9HxigEDRACo8oaG_wHZAKb-</recordid><startdate>202011</startdate><enddate>202011</enddate><creator>Zenger, Brian</creator><creator>Swink, J. Michael</creator><creator>Turner, Jeffrey L.</creator><creator>Bunch, T. Jared</creator><creator>Ryan, John J.</creator><creator>Shah, Rashmee U.</creator><creator>Turakhia, Mintu P.</creator><creator>Piccini, Jonathan P.</creator><creator>Steinberg, Benjamin A.</creator><general>American Heart Association, Inc</general><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>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-9203-5512</orcidid><orcidid>https://orcid.org/0000-0002-7823-8540</orcidid><orcidid>https://orcid.org/0000-0002-8546-9785</orcidid><orcidid>https://orcid.org/0000-0001-5349-0136</orcidid><orcidid>https://orcid.org/0000-0003-0772-2404</orcidid><orcidid>https://orcid.org/0000-0001-8025-0904</orcidid><orcidid>https://orcid.org/0000-0002-0039-9184</orcidid><orcidid>https://orcid.org/0000-0002-4729-7820</orcidid></search><sort><creationdate>202011</creationdate><title>Social Media Influence Does Not Reflect Scholarly or Clinical Activity in Real Life</title><author>Zenger, Brian ; Swink, J. Michael ; Turner, Jeffrey L. ; Bunch, T. Jared ; Ryan, John J. ; Shah, Rashmee U. ; Turakhia, Mintu P. ; Piccini, Jonathan P. ; Steinberg, Benjamin A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4907-b3ee21402198cd2b556c5eaf1745f6d9f15a18a5557febaeac30cbdf55c7a8fb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Authorship</topic><topic>Biomedical Research</topic><topic>Cardiac Electrophysiology</topic><topic>Electrophysiologic Techniques, Cardiac</topic><topic>Humans</topic><topic>Peer Influence</topic><topic>Periodicals as Topic</topic><topic>Scholarly Communication</topic><topic>Social Media</topic><topic>Workload</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zenger, Brian</creatorcontrib><creatorcontrib>Swink, J. Michael</creatorcontrib><creatorcontrib>Turner, Jeffrey L.</creatorcontrib><creatorcontrib>Bunch, T. Jared</creatorcontrib><creatorcontrib>Ryan, John J.</creatorcontrib><creatorcontrib>Shah, Rashmee U.</creatorcontrib><creatorcontrib>Turakhia, Mintu P.</creatorcontrib><creatorcontrib>Piccini, Jonathan P.</creatorcontrib><creatorcontrib>Steinberg, Benjamin A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Circulation. Arrhythmia and electrophysiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zenger, Brian</au><au>Swink, J. Michael</au><au>Turner, Jeffrey L.</au><au>Bunch, T. Jared</au><au>Ryan, John J.</au><au>Shah, Rashmee U.</au><au>Turakhia, Mintu P.</au><au>Piccini, Jonathan P.</au><au>Steinberg, Benjamin A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Social Media Influence Does Not Reflect Scholarly or Clinical Activity in Real Life</atitle><jtitle>Circulation. Arrhythmia and electrophysiology</jtitle><addtitle>Circ Arrhythm Electrophysiol</addtitle><date>2020-11</date><risdate>2020</risdate><volume>13</volume><issue>11</issue><spage>e008847</spage><epage>e008847</epage><pages>e008847-e008847</pages><issn>1941-3149</issn><eissn>1941-3084</eissn><abstract>BACKGROUND:Social media has become a major source of communication in medicine. We aimed to understand the relationship between physicians’ social media influence and their scholarly and clinical activity.
METHODS:We identified attending US electrophysiologists on Twitter. We compared physician Twitter activity to (1) scholarly publication record (h-index) and (2) clinical volume according to Centers for Medicare and Medicaid Services. The ratio of observed versus expected (obs/exp) Twitter followers was calculated based on each scholarly (K-index) and clinical activity.
RESULTS:We identified 284 physicians, with mean Twitter age of 5.0 (SD, 3.1) years and median 568 followers (25th, 75th195, 1146). They had a median 34.5 peer-reviewed articles (25th, 75th14, 105), 401 citations (25th, 75th102, 1677), and h-index 9 (25th, 75th4, 19.8). The median K-index was 0.4 (25th, 75th0.15, 1.0), ranging from 0.0008 to 29.2. The median number of electrophysiology procedures was 77 (25th, 75th0, 160) and evaluation and management visits 264 (25th, 75th59, 516) in 2017. The top 1% electrophysiologists for followers accounted for 20% of all followers, 17% of status updates, had a mean h-index of 6 (versus 15 for others, P=0.3), and accounted for 1% of procedural and evaluation and management volumes. They had a mean K-index of 21 (versus 0.77 for others, P<0.0001) and clinical obs/exp follower ratio of 17.9 and 18.1 for procedures and evaluation and management (P<0.001 each, versus others [0.81 for each]).
CONCLUSIONS:Electrophysiologists are active on Twitter, with modest influence often representative of scholarly and clinical activity. However, the most influential physicians appear to have relatively modest scholarly and clinical activity.</abstract><cop>United States</cop><pub>American Heart Association, Inc</pub><pmid>33030380</pmid><doi>10.1161/CIRCEP.120.008847</doi><orcidid>https://orcid.org/0000-0002-9203-5512</orcidid><orcidid>https://orcid.org/0000-0002-7823-8540</orcidid><orcidid>https://orcid.org/0000-0002-8546-9785</orcidid><orcidid>https://orcid.org/0000-0001-5349-0136</orcidid><orcidid>https://orcid.org/0000-0003-0772-2404</orcidid><orcidid>https://orcid.org/0000-0001-8025-0904</orcidid><orcidid>https://orcid.org/0000-0002-0039-9184</orcidid><orcidid>https://orcid.org/0000-0002-4729-7820</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Circulation. Arrhythmia and electrophysiology, 2020-11, Vol.13 (11), p.e008847-e008847 |
| issn | 1941-3149 1941-3084 |
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| source | MEDLINE; American Heart Association Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Authorship Biomedical Research Cardiac Electrophysiology Electrophysiologic Techniques, Cardiac Humans Peer Influence Periodicals as Topic Scholarly Communication Social Media Workload |
| title | Social Media Influence Does Not Reflect Scholarly or Clinical Activity in Real Life |
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