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Infertility influencers: an analysis of information and influence in the fertility webspace

PURPOSE: To examine fertility-related social media accounts and influencers on two social media platforms. METHODS: The search function of Twitter (TW) and Instagram (IG) was used to generate a list of accounts with the terms: fertility, infertility, ttc, egg freezing, ivf, endometriosis, and reprod...

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Autores principales: Blakemore, Jennifer K., Bayer, Arielle H., Smith, Meghan B., Grifo, James A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205373/
https://www.ncbi.nlm.nih.gov/pubmed/32382959
http://dx.doi.org/10.1007/s10815-020-01799-2
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author Blakemore, Jennifer K.
Bayer, Arielle H.
Smith, Meghan B.
Grifo, James A.
author_facet Blakemore, Jennifer K.
Bayer, Arielle H.
Smith, Meghan B.
Grifo, James A.
author_sort Blakemore, Jennifer K.
collection PubMed
description PURPOSE: To examine fertility-related social media accounts and influencers on two social media platforms. METHODS: The search function of Twitter (TW) and Instagram (IG) was used to generate a list of accounts with the terms: fertility, infertility, ttc, egg freezing, ivf, endometriosis, and reproductive. Accounts not in English, in private, with no posts in > 1 year, or with content unrelated to search terms were excluded. Accounts were assessed for author type; REI board certification (REI-BC); influencer (INF) status (> 10 K followers on IG; verified check mark on TW); account demographics; and content in last 5 posts. Statistical analysis included unpaired t tests, a classification and regression tree (CART) analysis, and stepwise multiple logistic regression. RESULTS: Seven hundred ten accounts were identified and 537 (278 TW, 259 IG) were included. Account types included societies, clinics, physicians, patients, groups, and “other.” Instagram content (1290 posts reviewed) was primarily personal stories (31.7%) or inspiration/support (23.7%). Twitter content (1390 posts reviewed) was mostly promotion (28.2%) and research/education (20.2%). Thirty-nine accounts (12.5%) were influencers. Fertility influencers were most often awareness/support accounts (59.8% TW, 25.0% IG), patients (12.8% TW, 25% IG), or other (17.9% TW, 21.0% IG). Only 7.7% TW and 7.1% IG INFs were board-certified REI physicians. The best predictor for classification as an influencer was high activity (> 50 posts/month TW, > 10 posts/month IG). CONCLUSION: As patients increasingly utilize social media to obtain and engage with health information, it is critical to understand the fertility-related SM landscape. This understanding may help to successfully enhance relationships with patients and ensure dissemination of accurate information.
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spelling pubmed-72053732020-05-08 Infertility influencers: an analysis of information and influence in the fertility webspace Blakemore, Jennifer K. Bayer, Arielle H. Smith, Meghan B. Grifo, James A. J Assist Reprod Genet Assisted Reproduction Technologies PURPOSE: To examine fertility-related social media accounts and influencers on two social media platforms. METHODS: The search function of Twitter (TW) and Instagram (IG) was used to generate a list of accounts with the terms: fertility, infertility, ttc, egg freezing, ivf, endometriosis, and reproductive. Accounts not in English, in private, with no posts in > 1 year, or with content unrelated to search terms were excluded. Accounts were assessed for author type; REI board certification (REI-BC); influencer (INF) status (> 10 K followers on IG; verified check mark on TW); account demographics; and content in last 5 posts. Statistical analysis included unpaired t tests, a classification and regression tree (CART) analysis, and stepwise multiple logistic regression. RESULTS: Seven hundred ten accounts were identified and 537 (278 TW, 259 IG) were included. Account types included societies, clinics, physicians, patients, groups, and “other.” Instagram content (1290 posts reviewed) was primarily personal stories (31.7%) or inspiration/support (23.7%). Twitter content (1390 posts reviewed) was mostly promotion (28.2%) and research/education (20.2%). Thirty-nine accounts (12.5%) were influencers. Fertility influencers were most often awareness/support accounts (59.8% TW, 25.0% IG), patients (12.8% TW, 25% IG), or other (17.9% TW, 21.0% IG). Only 7.7% TW and 7.1% IG INFs were board-certified REI physicians. The best predictor for classification as an influencer was high activity (> 50 posts/month TW, > 10 posts/month IG). CONCLUSION: As patients increasingly utilize social media to obtain and engage with health information, it is critical to understand the fertility-related SM landscape. This understanding may help to successfully enhance relationships with patients and ensure dissemination of accurate information. Springer US 2020-05-07 2020-06 /pmc/articles/PMC7205373/ /pubmed/32382959 http://dx.doi.org/10.1007/s10815-020-01799-2 Text en © Springer Science+Business Media, LLC, part of Springer Nature 2020
spellingShingle Assisted Reproduction Technologies
Blakemore, Jennifer K.
Bayer, Arielle H.
Smith, Meghan B.
Grifo, James A.
Infertility influencers: an analysis of information and influence in the fertility webspace
title Infertility influencers: an analysis of information and influence in the fertility webspace
title_full Infertility influencers: an analysis of information and influence in the fertility webspace
title_fullStr Infertility influencers: an analysis of information and influence in the fertility webspace
title_full_unstemmed Infertility influencers: an analysis of information and influence in the fertility webspace
title_short Infertility influencers: an analysis of information and influence in the fertility webspace
title_sort infertility influencers: an analysis of information and influence in the fertility webspace
topic Assisted Reproduction Technologies
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205373/
https://www.ncbi.nlm.nih.gov/pubmed/32382959
http://dx.doi.org/10.1007/s10815-020-01799-2
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