5335 Days of Implementation Science: Using Natural Language Processing to Examine Publication Trends and Topics

Abstract

Introduction: Moving evidence-based practices into the hands of practitioners requires the synthesis and translation of research literature. However, the growing pace of scientific publications across disciplines makes it increasingly difficult to stay abreast of research literature. Natural Language Processing (NLP) methods are emerging as a valuable strategy for conducting content analyses of academic literature. We sought to apply NLP to identify publication trends in the flagship journal field, Implementation Science, including key topic clusters and the distribution of topics over time. A parallel study objective was to demonstrate how NLP can be used in research synthesis. Methods: We examined 1711 Implementation Science abstracts published from February 22, 2006 to October 1, 2020. We retrieved the study data using PubMed’s Application Programming Interface (API) to assemble a database. Following standard preprocessing steps, we use topic modeling with latent Dirichlet Allocation (LDA) to cluster the abstracts following a minimization algorithm.Results: We examined 30 topics and computed topic model statistics of quality. Analyses revealed that published articles largely reflect i) characteristics of research, or ii) domains of practice. Emergent topic clusters encompassed key terms both salient and common to implementation science. HIV and stroke(s) represent the most commonly published clinical areas. Systematic reviews have grown in topic prominence and coherence, whereas articles pertaining to knowledge translation (KT) have dropped in prominence since 2013. Articles on HIV and implementation effectiveness have increased in topic exclusivity over time. Discussion. We demonstrated how NLP can be used as a synthesis and translation method to identify trends and topics across a large number of (over 1700) articles. With applicability to a variety of research domains, NLP is a promising approach to accelerate the dissemination and uptake of research literature. For future research in implementation science, we encourage the inclusion of more equity-focused studies to expand the impact of implementation science on disadvantaged communities.

Data Velocity in HIV-Related Implementation Research: Estimating Time From Funding to Publication

“…4,5 Implementation research (IR), defined by the United States (U.S.) National Institutes of Health (NIH) as the "scientific study of the use of strategies to adopt and integrate evidencebased health interventions (EBIs) into clinical and community settings to improve individual and population health," has rapidly expanded within recent years to answer the questions of "how." 1,[6][7][8] To realize the potential of implementation science approaches and IR to achieve the Ending the HIV Epidemic in the United States (EHE) goals by 2030, 9 research must be rapid, relevant, and rigorous. 10 IR that is rigorous but not rapid may lack relevance on publication if the guidelines and strategies have evolved or the evidence base has already surpassed the intervention being promoted or the strategies tested to facilitate adoption.…”

“…1–3 Indeed, the full benefits of HIV prevention and treatment interventions have not been observed due to challenges scaling interventions to effective programs. 4,5 Implementation research (IR), defined by the United States (U.S.) National Institutes of Health (NIH) as the ‟scientific study of the use of strategies to adopt and integrate evidence-based health interventions (EBIs) into clinical and community settings to improve individual and population health,” has rapidly expanded within recent years to answer the questions of ‟how.” 1,6–8…”

Description of organizational and clinician characteristics of primary dementia care in Canada: a multi-method study

“…Evidence-based practice (EBP) is a key approach to improving the quality of patient care and service delivery in health care systems around the world, but it still faces implementation challenges in daily practice, in particular in primary care [1], which is also called the researchpractice gap [2]. The implementation of evidence-based recommendations into daily practice is impacted by various factors, including organizational and clinician characteristics, that interplay and influence implementation effectiveness and sustainability [3,4].…”