The impact of a dedicated social media strategy on enhancing surgical education

Social media (SoMe) comprises online applications enabling real-time, multimedia communication and collaboration. Its expanding use in medicine, including evidence of improved short-term knowledge and enhanced communication for trainees, suggests value for surgical education. In surgery, and particularly within colorectal surgery, Twitter has been used to disseminate findings globally, engage diverse investigators, and increase visibility of academic work. Despite growing adoption, limited research has quantified whether SoMe increases the reach and impact of journal-published surgical research. Traditional bibliometrics (citations, impact factor, h-index, SJR) do not capture social media engagement. Alternative metrics (Altmetrics) now track downloads, mentions, and social shares, offering insights into public impact and predicting citations. For journals, SoMe may increase study engagement, stakeholder connection, article reads, and citation rates, potentially influencing impact factor. However, most prior work focuses on article-level influence rather than journal-level strategy. This study’s primary aim was to evaluate the impact of a dedicated SoMe strategy on engagement metrics for an international journal (Colorectal Disease). A secondary aim was to quantify the influence of SoMe on evidence-based medicine and surgical education. The hypothesis was that a dedicated SoMe strategy would increase traffic to the journal’s research in a measurable, generalisable, and reproducible manner.

Design: Retrospective analysis of social media engagement metrics for the Twitter account of the journal Colorectal Disease (@ColorectalDis) over June 2015–April 2021. Intervention: A targeted social media (SoMe) strategy implemented from September 2018 included daily posting, consistent branding, and a structured weekly tweet plan, led by dedicated SoMe editors and team members. Periods: Phase 1 (pre-intervention): June 2015–September 2018 (39 months). Phase 2 (post-intervention): September 2018–April 2021 (32 months). Data sources and metrics: Twitter Analytics and Twitonomy were used to quantify user engagement and account activity. Altmetrics and journal web analytics captured website interactions, journal traffic, and article downloads. Definitions followed platform standards (e.g., impressions, engagements, engagement rate [engagements/impressions×100], URL clicks). Outcomes: (1) Account activity (tweets posted, impressions); (2) Engagement (total engagements, engagement rate, URL clicks); (3) Account growth (mean new followers per month). Traditional journal metrics (new subscribers, submissions, impact factor) and article downloads were also assessed. Analysis: Descriptive statistics (frequencies, percentages). Comparative analyses between phases used Student’s paired t-tests with alpha < 0.05. Ethics: No protected health information used; exempt from IRB. Lack of existing EQUATOR guidance for SoMe metrics noted; this work may inform standardisation.

• Activity increased after SoMe strategy: mean tweets/month rose from 5.51 (Phase 1) to 28.79 (Phase 2); total tweets increased (215 vs 835 over periods reported); impressions rose from 269,152 (Phase 1) to 4,721,198 (Phase 2), with impressions per tweet increasing from 1,251.87 to 4,802.85. - Engagement improved markedly: total engagements increased from 10,934 (Phase 1) to 236,369 (Phase 2); engagements per tweet rose from 50.86 to 240.46; engagement rate increased from 4.06% to 5.01%; URL clicks increased from 3,533 to 30,863 (ninefold). - Account growth: mean new followers/month increased from 38 (Phase 1) to 213 (Phase 2) (p < 0.01); total followers reached 12,283 by April 30, 2021. - Interactions with posted articles were significantly higher post-SoMe (4,096,167 vs 269,152; p < 0.01). - Article downloads increased nearly twentyfold post-intervention (210,449 vs 10,934; p < 0.01). - Traditional journal metrics improved post-SoMe: new subscribers increased by 11% (p < 0.01); article submissions increased by 24% (p < 0.01); impact factor increased by 0.9 (p < 0.01). - Overall, from inception to analysis, 1,198 original tweets generated nearly 5 million impressions and over 230,000 engagements.

The findings demonstrate that a structured social media strategy substantially increases Twitter activity, engagement, and account growth, translating into greater interactions with journal content, more article downloads, and improvements in traditional journal metrics, including subscribers, submissions, and impact factor. These results support the hypothesis that a dedicated SoMe program enhances the reach and educational impact of surgical research at the journal level, not just for individual articles. The study contextualizes Twitter as a preferred professional platform among surgeons, offering rapid, efficient dissemination and interaction with evidence. It emphasizes the importance of multimodal SoMe approaches (e.g., visual abstracts, theme-based chats, editor takeovers) that foster dialogue with authors and promote evidence translation into practice. The journal’s increased follower base and engagement position it as an influencer within colorectal academia, where amplification relies not only on large accounts but also on distributed user engagement. Responsible SoMe practices are essential to mitigate risks such as misinformation, echo chambers, and security issues, and to prevent burnout among content creators. Overall, sustained, data-informed SoMe strategies can help journals remain relevant, expand educational impact, and potentially influence citation-based metrics.

A designated social media strategy is necessary for journals to maintain relevance and engage stakeholders effectively. Implementing a structured SoMe program on Twitter markedly increased access to journal content, user engagement, article downloads, and website traffic, providing evidence that SoMe activity can advance surgical research dissemination and education. As SoMe continues to shape academic influence, alternative metrics will gain importance alongside traditional bibliometrics. Future work should refine best practices across platforms (e.g., visual abstracts, Instagram, curated chats), evaluate long-term causal links to citation metrics, and explore generalisability across specialties and journals.

• Language and audience bias: The follower distribution showed a predisposition to English-speaking countries; geolocation data were available for only about one-fifth of followers, limiting representativeness. - Diversity and echo chamber risk: Although the editorial team is diverse, further broadening perspectives could reduce echo chamber effects. - Confounding factors for impact factor: Changes in impact factor may be influenced by article mix, public interest, and increased submissions, independent of SoMe activity. - Comparative data constraints: Lack of access to other surgical accounts’ analytics prevented cross-account comparison. - Causality: Unable to definitively attribute improvements solely to the SoMe strategy versus concurrent general growth in SoMe popularity and platform-wide engagement trends.