Kauffman Lilly, Lopez-Ramirez Felipe, Weisberg Edmund M, Fishman Elliot K
The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, 601 North Caroline Street, JHOC 3250, Baltimore, MD 21287, USA.
The Russell H. Morgan Department of Radiology and Radiological Science, 600 N. Caroline Street, Baltimore, MD 21287, USA.
Curr Probl Diagn Radiol. 2025 Mar-Apr;54(2):170-175. doi: 10.1067/j.cpradiol.2024.08.005. Epub 2024 Aug 14.
In January 2016, we created an Instagram page for radiology education. Numerous publications in different fields have reported that Instagram "reels," introduced in 2020 as a short-form video feature, are more popular than image posts. These findings and our familiarity with Instagram prompted us to analyze our own data to better understand how image posts compared with reels when used in the context of radiology education.
For each post category, metric values were extracted from the Instagram platform and analyzed as continuous variables, reported as medians with interquartile ranges (IQR). Metrics were compared between image categories using the Kruskal-Wallis test, with resulting p-values adjusted for multiple comparisons using the Bonferroni correction. Corrected p-values of less than 0.05 were considered statistically significant.
We included 128 images and 96 reels in the analysis. Images generally reached a larger audience, with a median of 18,745 [IQR: 13,478-27,243] impressions vs. 11,972 [IQR: 9,310.0-13,844.5] for reels (p < 0.01). Images also tended to be shared more frequently (median 19 vs. 20, p < 0.01), liked more often (median 480 vs. 296, p < 0.01), and saved more by users (median 138 vs. 84, p < 0.01) than reels, respectively. Both images and reels received a similar number of comments, with a median of 3 comments for both (p > 0.99). We also explored the performance differences of image post subcategories. Within images, our "You Make the Call!" (YMTC) questions (n = 23) displayed higher performance metrics across the board than the three other types of image posts combined (n = 105). When compared, the median number of impressions for YMTC images was 36,735 [IQR: 31,343-40,742] vs. 15,992 [IQR:12,774-21,873] for other types of images (p < 0.01). YMTC images were shared more often (median 25 vs. 17, p < 0.01), received more likes (median 809 vs. 445, p < 0.01) and saves (median 206 vs. 119, p < 0.01) than non-YMTC images, respectively. User engagement showed slightly different trends with YMTC reels being the most liked, while quiz reels receiving the most comments and talking clips being the most saved.
Our findings on the use of Instagram in radiology education suggest that static images perform much better than reels. Consequently, we recommend to radiology educators seeking to establish an Instagram presence that using static image posts is an appropriate approach for reaching a radiology audience, particularly with image posts that engage an audience with participatory opportunities such as answering quiz-like questions aimed at making a diagnosis.
2016年1月，我们创建了一个用于放射学教育的Instagram页面。不同领域的众多出版物报道称，2020年推出的Instagram“短片”作为一种短视频功能，比图片帖子更受欢迎。这些发现以及我们对Instagram的熟悉程度促使我们分析自己的数据，以更好地了解在放射学教育背景下使用时，图片帖子与短片相比情况如何。
对于每个帖子类别，从Instagram平台提取指标值并作为连续变量进行分析，报告为中位数及四分位间距（IQR）。使用Kruskal-Wallis检验比较图片类别之间的指标，所得p值使用Bonferroni校正进行多重比较调整。校正后p值小于0.05被认为具有统计学意义。
我们在分析中纳入了128张图片和96个短片。图片通常能触达更多受众，图片的中位数展示量为18,745[IQR：13,478 - 27,243]，而短片为11,972[IQR：9,310.0 - 13,844.5](p < 0.01)。图片也往往被分享得更频繁（中位数19次对20次，p < 0.01），被点赞得更多（中位数480次对296次，p < 0.01），并且被用户保存得更多（中位数138次对84次，p < 0.0 |）。图片和短片收到的评论数量相似，两者的中位数均为3条评论(p > 0.99)。我们还探讨了图片帖子子类别的表现差异。在图片中，我们的“你来判断！”（YMTC）问题（n = 23）在各项指标上的表现总体高于其他三种类型的图片帖子总和（n = 105）。相比之下，YMTC图片的中位数展示量为36,735[IQR：31,343 - 40,742]，而其他类型图片为15,992[IQR：12,774 - 21,873](p < 0.01)。YMTC图片比非YMTC图片被分享得更频繁（中位数25次对17次，p < 0.01），获得更多点赞（中位数809次对445次，p < 0.01）和保存（中位数206次对119次，p < 0.01）。用户参与度呈现出略有不同的趋势，其中YMTC短片最受点赞，而问答短片收到的评论最多，讲解片段被保存得最多。
我们关于在放射学教育中使用Instagram的研究结果表明，静态图片比短片表现要好得多。因此，我们建议寻求在Instagram上开展业务的放射学教育工作者，使用静态图片帖子是接触放射学受众的合适方法，特别是那些通过参与机会（如回答类似诊断测验问题）吸引受众的图片帖子。
