Using Publication Monitoring and Social Media to Help NIDILRR’s Disability Research Reach its Audience
- NIDILRR funds a wide range of disability and rehabilitation research, but wasn’t sure to what extent it was reaching people.
- Using tools including natural language processing, Abt analyzed grantee publications and social media to understand the reach of NIDILRR-funded research.
- Abt suggested tools ranging from data visualization to traditional and social media monitoring to track and increase awareness of NIDILRR’s findings.
The National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) is the federal government’s primary disability research organization. (NIDILRR is part of the Administration for Community Living (ACL)). NIDILRR funds research, demonstrations, training, and technical assistance to maximize the inclusion and integration of individuals with disabilities into society, providing supports for employment, independent living, families, and economic and social self-sufficiency. Its funding enables broad research across disabilities and injuries that are important to the American public. However, the breadth of NIDILRR's research support is not apparent, because most research only reaches a narrow audience: readers of specialized scientific journals. NIDILRR wanted to understand the extent to which its research reaches key stakeholders, especially people with disabilities, and ways to increase the reach. The agency also wanted to understand the breadth of previous evaluations of its funding mechanisms to optimize the development of future evaluations. To that end, NIDILRR contracted Abt Global to:
- Characterize the published output of its grantees, including identifying the most impactful and highly cited findings;
- Analyze NIDILRR content on social media platforms; and
- Perform an analysis of past evaluations.
For the citations analysis, we:
- Characterized 5,246 grantee publications between 2014 and 2021 by key characteristics of interest to NIDILRR;
- Identified highly cited publications and top journals in which NIDILRR grantees most frequently publish; and
- Applied Topic Modeling (a natural language processing method) to a subset of 2,717 articles to identify main themes of NIDILRR-funded research.
For the social media presence analysis, we collected and analyzed data on the social media accounts of 312 grantees and conducted a study of #NIDILRR tweets.
We also conducted a mixed-methods meta-evaluation by reviewing 18 evaluations previously commissioned by NIDILRR and interviewing NIDILRR staff.
We learned that across all of its funding mechanisms, NIDILRR-funded research yields approximately 600 publications per year. They cover broad topics, such as traumatic brain injury (TBI), spinal cord injury (SCI), burn injury, autism, intellectual disability, chronic pain, robotics, and telehealth. In addition to #NIDILRR, grantees’ top Twitter content is posted under employment, disability, research, and knowledge translation hashtags.
Based on our analyses, Abt made actionable recommendations to increase the visibility, accessibility, and attractiveness of NIDILRR-funded research content, and to strengthen future NIDILRR evaluations and development of recommendations.