Abstract：
OBJECTIVE: In May 2009, we created a Facebook page for radiology education. While we shared a host of learning materials such as case images, quiz questions, and medical illustrations, we also posted world news, music, and memes. In February 2023, we eliminated everything from the site not related to radiology education. Our aim was to determine how focusing on radiology education alone would affect audience growth for our Facebook page.
METHODS: We exported our Facebook post data for the dates March 1, 2023 through February 29, 2024, to represent the full calendar year after we revised our content presentation, which we compared to data from November 1, 2020 to October 31, 2021. The mean and standard deviation for each post type\'s reach for 2023/24 were analyzed and compared against the 2020/21 statistics, and Wilcoxon rank sum tests were used to obtain p-values. Linear regressions for each year were performed to understand the relationship between reach and engagement.
RESULTS: A total of 4,270 posts were included in our new analysis. Our average number of posts per day decreased from 24.8 to 11.71, reducing by more than half the amount of content shared to our social media page. Our posts had a mean overall reach of 4,660-compared to 1,743 in 2021 (p=0.0000). There was a statistically significant increase in reach for posts on artificial intelligence, case images, medical illustrations, pearls, quiz images, quiz videos, slideshow images, and both types of instructional videos (p<0.005). For both 2021 and 2024, the linear regression slopes were positive (y=0.0687x-65.0279 and y=0.006334x+21.3425, respectively).
CONCLUSIONS: Facebook and other social media have been found to be helpful sources for radiology education. Our experience and statistics with radiology education via social media may help other radiology educators better curate their own pages. To optimize experiences for students, professionals, and other users, and to reach more people, we found that providing readily accessible radiology education is preferred to the social aspects of social media.
METHODS: We exported our Facebook post data for the dates March 1, 2023 through February 29, 2024, to represent the full calendar year after we revised our content presentation, which we compared to data from November 1, 2020 to October 31, 2021. The mean and standard deviation for each post type\'s reach for 2023/24 were analyzed and compared against the 2020/21 statistics, and Wilcoxon rank sum tests were used to obtain p-values. Linear regressions for each year were performed to understand the relationship between reach and engagement.
RESULTS: A total of 4,270 posts were included in our new analysis. Our average number of posts per day decreased from 24.8 to 11.71, reducing by more than half the amount of content shared to our social media page. Our posts had a mean overall reach of 4,660-compared to 1,743 in 2021 (p=0.0000). There was a statistically significant increase in reach for posts on artificial intelligence, case images, medical illustrations, pearls, quiz images, quiz videos, slideshow images, and both types of instructional videos (p<0.005). For both 2021 and 2024, the linear regression slopes were positive (y=0.0687x-65.0279 and y=0.006334x+21.3425, respectively).
CONCLUSIONS: Facebook and other social media have been found to be helpful sources for radiology education. Our experience and statistics with radiology education via social media may help other radiology educators better curate their own pages. To optimize experiences for students, professionals, and other users, and to reach more people, we found that providing readily accessible radiology education is preferred to the social aspects of social media.
摘要：
目的：2009年5月，我们创建了一个放射学教育的Facebook页面。虽然我们分享了大量的学习材料，比如案例图像，测验问题,和医学插图，我们还发布了世界新闻，音乐,和模因。2023年2月，我们从网站上删除了与放射学教育无关的所有内容。我们的目标是确定仅专注于放射学教育将如何影响我们Facebook页面的受众增长。
方法：我们导出了2023年3月1日至2024年2月29日的Facebook帖子数据，以代表我们修改内容演示后的整个日历年。我们将其与2020年11月1日至2021年10月31日的数据进行了比较。对2023/24年每种岗位类型的均值和标准差进行了分析，并与2020/21年的统计数据进行了比较，和Wilcoxon秩和检验用于获得p值。进行了每年的线性回归，以了解覆盖范围和参与度之间的关系。
结果：我们的新分析中包含了4,270个帖子。我们每天的平均帖子数量从24.8减少到11.71，减少了共享到我们社交媒体页面的内容数量的一半以上。我们的帖子的平均总体覆盖率为4,660，而2021年为1,743（p=0.0000）。在统计上，人工智能职位的影响力显着增加，案例图像,医学插图,珍珠,测验图像,测验视频,幻灯片图像，和两种类型的教学视频（p<0.005）。对于2021年和2024年,线性回归斜率均为正(分别为y=0.0687x-65.0279和y=0.006334x+21.3425)。
结论：已发现Facebook和其他社交媒体是放射学教育的有用来源。我们通过社交媒体进行放射学教育的经验和统计数据可能有助于其他放射学教育者更好地整理自己的页面。为了优化学生的体验，专业人士,和其他用户，为了接触到更多的人，我们发现，提供易于访问的放射学教育比社交媒体的社交方面更受欢迎。
方法：我们导出了2023年3月1日至2024年2月29日的Facebook帖子数据，以代表我们修改内容演示后的整个日历年。我们将其与2020年11月1日至2021年10月31日的数据进行了比较。对2023/24年每种岗位类型的均值和标准差进行了分析，并与2020/21年的统计数据进行了比较，和Wilcoxon秩和检验用于获得p值。进行了每年的线性回归，以了解覆盖范围和参与度之间的关系。
结果：我们的新分析中包含了4,270个帖子。我们每天的平均帖子数量从24.8减少到11.71，减少了共享到我们社交媒体页面的内容数量的一半以上。我们的帖子的平均总体覆盖率为4,660，而2021年为1,743（p=0.0000）。在统计上，人工智能职位的影响力显着增加，案例图像,医学插图,珍珠,测验图像,测验视频,幻灯片图像，和两种类型的教学视频（p<0.005）。对于2021年和2024年,线性回归斜率均为正(分别为y=0.0687x-65.0279和y=0.006334x+21.3425)。
结论：已发现Facebook和其他社交媒体是放射学教育的有用来源。我们通过社交媒体进行放射学教育的经验和统计数据可能有助于其他放射学教育者更好地整理自己的页面。为了优化学生的体验，专业人士,和其他用户，为了接触到更多的人，我们发现，提供易于访问的放射学教育比社交媒体的社交方面更受欢迎。
