JMIR Publications

ABSTRACT

Background:

Research dissemination is a vital step in bridging the gap between the publication of cutting-edge research and its adoption into clinical practice. Social media is gaining increasing prominence in academic medicine as an additional way to accelerate research dissemination by more directly engaging with clinicians. However, guidance on best practices for launching professional social media accounts is lacking for research organizations and medical institutions. Our study aims to help close this gap by providing a structured roadmap based on our research network’s experience of creating and maintaining a Twitter account for research dissemination.

Objective:

To provide a roadmap for organizations aiming to create a professional Twitter account for research dissemination.

Methods:

This was a mixed methods study analyzing the Pediatric Emergency Care Applied Research Network (PECARN) Twitter team's four-year experience (2020-2023) with building a social media account. Using the Nominal Group Technique (NGT) qualitative approach, we recorded insights from the six team members' experiences in a round-robin fashion until response saturation. Additionally, we analyzed internal Slack communications to identify key developmental events. Together, these were then prioritized by consensus to elucidate key developmental events that enhanced both social media and scientific engagement. This process was informed by quantitative data from Twitter performance metrics and Altmetric Attention Scores for journal publications. Together, these elements informed the design of a logic model framework.

Results:

The NGT generated 63 thematic statements which included issues such as organizational structure, content strategy, technologies, analytics, organizational priorities, and challenges. These statements coalesced into the 7 domains (priorities, assumptions, inputs, outputs, outcomes, and external factors) that comprise the logic model. Inputs included organizational support (e.g., executive-level champion, funding), specialized personnel (e.g., content writer, analytics manager), and operational technologies (e.g., communications, data analytics tools). Outputs encompassed targeted activities, such as engaging with other Twitter accounts, publishing high-quality tweets highlighting scholarly work, and developing a dynamic operations manual for the Twitter team. Measured outcomes included various metrics at the tweet level (impressions, engagements), account level (profile visits, follower count and type), and journal article level (Altmetrics Attention Score). Our findings suggest that incorporation of polls, graphics, and URL links to have the strongest impact on impressions and engagements.

Conclusions:

Our logic model roadmap, based on our practical multi-year experience and data-driven strategies, can serve as a guide for research organizations or medical institutions aiming to incorporate Twitter or other social media platforms for research dissemination.