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10.1007/s10815-020-01799-2 http://scihub22266oqcxt.onion/10.1007/s10815-020-01799-2 32382959!7205373!32382959     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32382959&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Assist+Reprod+Genet 2020 ; 37 (6): 1371-1378 Nephropedia Template TP {{tp|p=32382959|t=2020. Infertility influencers: an analysis of information and influence in the fertility webspace |pdf=|usr=}}{{32382959}} gab.com Text Infertility influencers: an analysis of information and influence in the fertility webspace JO: J Assist Reprod Genet http://www.kidney.de/pget.php?&tw=1&pmid=32382959 #FOAvip 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. Twit Text FOAVip Infertility influencers: an analysis of information and influence in the fertility webspace ????J Assist Reprod Genet http://www.kidney.de/pget.php?&tw=1&pmid=32382959 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32382959 #FOAvip English Wikipedia <ref>{{Cite pmid|32382959}}</ref> Infertility influencers: an analysis of information and influence in the fertility webspace #MMPMID32382959 Blakemore JK; Bayer AH; Smith MB; Grifo JA J Assist Reprod Genet 2020[Jun]; 37 (6): 1371-1378 PMID32382959show ga 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. |*Social Media[MESH] |Adult[MESH] |Female[MESH] |Fertility/*physiology[MESH] |Health Information Exchange/*trends[MESH] |Humans[MESH] |Internet/*trends[MESH] |Male[MESH] |Middle Aged[MESH]Infertility influencers: an analysis of information and influence in t(epmc).pdf DeepDyve Pubget Overpricing