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10.2196/28118 http://scihub22266oqcxt.onion/10.2196/28118 33939625!8117955!33939625     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Internet+Res 2021 ; 23 (5): e28118 Nephropedia Template TP {{tp|p=33939625|t=2021. Understanding Behavioral Intentions Toward COVID-19 Vaccines: Theory-Based Content Analysis of Tweets |pdf=|usr=}}{{33939625}} gab.com Text Understanding Behavioral Intentions Toward COVID-19 Vaccines: Theory-Based Content Analysis of Tweets JO: J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=33939625 #FOAvip BACKGROUND: Acceptance rates of COVID-19 vaccines have still not reached the required threshold to achieve herd immunity. Understanding why some people are willing to be vaccinated and others are not is a critical step to develop efficient implementation strategies to promote COVID-19 vaccines. OBJECTIVE: We conducted a theory-based content analysis based on the capability, opportunity, motivation-behavior (COM-B) model to characterize the factors influencing behavioral intentions toward COVID-19 vaccines mentioned on the Twitter platform. METHODS: We collected tweets posted in English from November 1-22, 2020, using a combination of relevant keywords and hashtags. After excluding retweets, we randomly selected 5000 tweets for manual coding and content analysis. We performed a content analysis informed by the adapted COM-B model. RESULTS: Of the 5000 COVID-19 vaccine-related tweets that were coded, 4796 (95.9%) were posted by unique users. A total of 97 tweets carried positive behavioral intent, while 182 tweets contained negative behavioral intent. Of these, 28 tweets were mapped to capability factors, 155 tweets were related to motivation, 23 tweets were related to opportunities, and 74 tweets did not contain any useful information about the reasons for their behavioral intentions (kappa=0.73). Some tweets mentioned two or more constructs at the same time. Tweets that were mapped to capability (P<.001), motivation (P<.001), and opportunity (P=.03) factors were more likely to indicate negative behavioral intentions. CONCLUSIONS: Most behavioral intentions regarding COVID-19 vaccines were related to the motivation construct. The themes identified in this study could be used to inform theory-based and evidence-based interventions to improve acceptance of COVID-19 vaccines. Twit Text FOAVip Understanding Behavioral Intentions Toward COVID-19 Vaccines: Theory-Based Content Analysis of Tweets ????J Med Internet Res http://www.kidney.de/pget.php?&tw=1&pmid=33939625 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33939625 #FOAvip English Wikipedia <ref>{{Cite pmid|33939625}}</ref> Understanding Behavioral Intentions Toward COVID-19 Vaccines: Theory-Based Content Analysis of Tweets #MMPMID33939625 Liu S; Liu J J Med Internet Res 2021[May]; 23 (5): e28118 PMID33939625show ga BACKGROUND: Acceptance rates of COVID-19 vaccines have still not reached the required threshold to achieve herd immunity. Understanding why some people are willing to be vaccinated and others are not is a critical step to develop efficient implementation strategies to promote COVID-19 vaccines. OBJECTIVE: We conducted a theory-based content analysis based on the capability, opportunity, motivation-behavior (COM-B) model to characterize the factors influencing behavioral intentions toward COVID-19 vaccines mentioned on the Twitter platform. METHODS: We collected tweets posted in English from November 1-22, 2020, using a combination of relevant keywords and hashtags. After excluding retweets, we randomly selected 5000 tweets for manual coding and content analysis. We performed a content analysis informed by the adapted COM-B model. RESULTS: Of the 5000 COVID-19 vaccine-related tweets that were coded, 4796 (95.9%) were posted by unique users. A total of 97 tweets carried positive behavioral intent, while 182 tweets contained negative behavioral intent. Of these, 28 tweets were mapped to capability factors, 155 tweets were related to motivation, 23 tweets were related to opportunities, and 74 tweets did not contain any useful information about the reasons for their behavioral intentions (kappa=0.73). Some tweets mentioned two or more constructs at the same time. Tweets that were mapped to capability (P<.001), motivation (P<.001), and opportunity (P=.03) factors were more likely to indicate negative behavioral intentions. CONCLUSIONS: Most behavioral intentions regarding COVID-19 vaccines were related to the motivation construct. The themes identified in this study could be used to inform theory-based and evidence-based interventions to improve acceptance of COVID-19 vaccines. |COVID-19 Vaccines/*administration & dosage[MESH] |Humans[MESH] |SARS-CoV-2/immunology/isolation & purification[MESH] |Social Media/*statistics & numerical data[MESH]Understanding Behavioral Intentions Toward COVID-19 Vaccines: Theory-B(epmc).pdf DeepDyve Pubget Overpricing