Background: Recruiting participants into clinical trials continues to be a challenge, which can result in study delay or termination. Recent studies have used social media to enhance recruitment outcomes. An assessment of the literature on the use of social media for this purpose is required.Objective: This study aims to answer the following questions: (1) How is the use of social media, in combination with traditional approaches to enhance clinical trial recruitment and enrollment, represented in the literature? and (2) Do the data on recruitment and enrollment outcomes presented in the literature allow for comparison across studies?Methods: We conducted a comprehensive literature search across 7 platforms to identify clinical trials that combined social media and traditional methods to recruit patients. Study and participant characteristics, recruitment methods, and recruitment outcomes were evaluated and compared.Results: We identified 2371 titles and abstracts through our systematic search. Of these, we assessed 95 full papers and determined that 33 studies met the inclusion criteria. A total of 17 studies reported enrollment outcomes, of which 9 achieved or exceeded their enrollment target. The proportion of participants enrolled from social media in these studies ranged from 0% to 49%. Across all 33 studies, the proportion of participants recruited and enrolled from social media varied greatly. A total of 9 studies reported higher enrollment rates from social media than any other methods, and 4 studies reported the lowest cost per enrolled participant from social media.Conclusions: While the assessment of the use of social media to improve clinical trial participation is hindered by reporting inconsistencies, preliminary data suggest that social media can increase participation and reduce per-participant cost. The adoption of consistent standards for reporting recruitment and enrollment outcomes is required to advance our understanding and use of social media to support clinical trial success.

Community-based participatory research (CBPR) partnerships exist as complex, dynamic relationships that incorporate shared decision that supports trust development between communities and academics. Within CBPR, the interest in understanding the concept of trust has grown with the realization that, without trust, CBPR relationships fracture. A barrier to monitoring the trust health of a partnership is the lack of a shared operationalization of the concept, its antecedents, and measurement tools. To address these barriers, a six-category trust typology was created as a developmental theory of trust progress. To advance the theory, this article reports on the quantitative structural elements of the trust typology, identifies variability in trust correlates, and creates an empirical foundation for the trust types. Using Engage for Equity data, trust covariates included measures of synergy, CBPR principles, participation, and influence. Structural equation models were used to assess associations between trust types and the latent constructs measured by the items in each measure. The findings demonstrate that the six trust types generally operate on a continuum. Specifically, it does appear that trust deficit, role-based trust, functional trust, proxy trust, and reflective trust are on a single continuum from low to high. Scale scores for reflective trust and proxy trust were consistently and statistically significantly higher than those for functional trust, role-based, neutral, and trust deficit. These results support the construct validity of the trust typology as representing “higher levels” of trust phases. Due to the dynamic nature of partnerships, regular monitoring of partnership trust types can serve as a proxy for partnership functioning.

Importance Complex medication regimens pose self-management challenges, particularly among populations with low levels of health literacy. Objective To test medication management tools delivered through a commercial electronic health record (EHR) with and without a nurse-led education intervention. Design, Setting, and Participants This 3-group cluster randomized clinical trial was performed in community health centers in Chicago, Illinois. Participants included 794 patients with hypertension who self-reported using 3 or more medications concurrently (for any purpose). Data were collected from April 30, 2012, through February 29, 2016, and analyzed by intention to treat. Interventions Clinics were randomly assigned to to groups: electronic health record–based medication management tools (medication review sheets at visit check-in, lay medication information sheets printed after visits; EHR-alone group), EHR-based tools plus nurse-led medication management support (EHR plus education group), or usual care. Main Outcomes and Measures Outcomes at 12 months included systolic blood pressure (primary outcome), medication reconciliation, knowledge of drug indications, understanding of medication instructions and dosing, and self-reported medication adherence. Medication outcomes were assessed for all hypertension prescriptions, all prescriptions to treat chronic disease, and all medications. Results Among the 794 participants (68.6% women; mean [SD] age, 52.7 [9.6] years), systolic blood pressure at 12 months was greater in the EHR-alone group compared with the usual care group by 3.6 mm Hg (95% CI, 0.3 to 6.9 mm Hg). Systolic blood pressure in the EHR plus education group was not significantly lower compared with the usual care group (difference, −2.0 mm Hg; 95% CI, −5.2 to 1.3 mm Hg) but was lower compared with the EHR-alone group (−5.6 mm Hg; 95% CI, −8.8 to −2.4 mm Hg). At 12 months, hypertension medication reconciliation was improved in the EHR-alone group (adjusted odds ratio [OR], 1.8; 95% CI, 1.1 to 2.9) and the EHR plus education group (adjusted odds ratio [OR], 2.0; 95% CI, 1.3 to 3.3) compared with usual care. Understanding of medication instructions and dosing was greater in the EHR plus education group than the usual care group for hypertension medications (OR, 2.3; 95% CI, 1.1 to 4.8) and all medications combined (OR, 1.7; 95% CI, 1.0 to 2.8). Compared with usual care, the EHR tools alone and EHR plus education interventions did not improve hypertension medication adherence (OR, 0.9; 95% CI, 0.6-1.4 for both) or knowledge of chronic drug indications (OR for EHR tools alone, 1.0 [95% CI, 0.6 to 1.5] and OR for EHR plus education, 1.1 [95% CI, 0.7-1.7]). Conclusions and Relevance The study found that EHR tools in isolation improved medication reconciliation but worsened blood pressure. Combining these tools with nurse-led support suggested improved understanding of medication instructions and dosing but did not lower blood pressure compared with usual care. Trial Registration ClinicalTrials.gov identifier:NCT01578577

Background: The institutions that comprise the Clinical and Translational Science Award (CTSA) consortium and the National Center for Advancing Translational Sciences continue to explore and develop community-engaged research strategies and to study the role of community academic partnerships in advancing the science of community engagement. Objectives: To explore CTSA institutions in relation to an Institute of Medicine recommendation that community engagement occur in all stages of translational research and be defined and evaluated consistently. Methods: A sequential multimethods study starting with an online pilot survey followed by survey respondents and site informant interviews. A revised survey was sent to the community engagement and evaluation leads at each CTSA institution, requesting a single institutional response about the definitions, indicators, and metrics of community engagement and community-engaged research. Results: A plurality of CTSA institutions selected the definition of community engagement from the Principles of Community Engagement. Although claiming unique institutional priorities create barriers to developing shared metrics, responses indicate an overall lack of attention to the development and deployment of metrics to assess community engagement in and contributions to research. Conclusions: Although definitions of community engagement differ among CTSAs, there seem to be more similarities than differences in the indicators and measures tracked and reported on across all definitions, perhaps owing to commonalities among program infrastructures and goals. Metrics will likely need to be specific to translational research stages. The assessment of community engagement within translational science will require increased institutional commitment.

The Clinical and Translational Science Award (CTSA) initiative calls on academic health centers to engage communities around a clinical research relationship measured ultimately in terms of public health. Among a few initiatives involving university accountability for advancing public interests, a small CTSA workgroup devised a community engagement (CE) logic model that organizes common activities within a university–community infrastructure to facilitate CE in research. Whereas the model focuses on the range of institutional CE inputs, it purposefully does not include an approach for assessing how CE influences research implementation and outcomes. Rather, with communities and individuals beginning to transition into new research roles, this article emphasizes studying CE through specific relationship types and assessing how expanded research teams contribute to the full spectrum of translational science. The authors propose a typology consisting of three relationship types—engagement, collaboration, and shared leadership—to provide a foundation for investigating community–academic contributions to the new CTSA research paradigm. The typology shifts attention from specific community–academic activities and, instead, encourages analyses focused on measuring the strength of relationships through variables like synergy and trust. The collaborative study of CE relationships will inform an understanding of CTSA infrastructure development in support of translational research and its goal, which is expressed in the logic model: better science, better answers, better population health.

Stakeholder engagement is acknowledged as central to dissemination and implementation (D&I) of research that generates and answers new clinical and health service research questions. There is both benefit and risk in conducting stakeholder engagement. Done wrong, it can damage trust and adversely impact study results, outcomes, and reputations. Done correctly with sensitivity, inclusion, and respect, it can significantly facilitate improvements in research prioritization, communication, design, recruitment strategies, and ultimately provide results useful to improve population and individual health. There is a recognized science of stakeholder engagement, but a general lack of knowledge that matches its strategies and approaches to particular populations of interest based on history and characteristics. This article reviews stakeholder engagement, provides several examples of its application across the range of translational research, and recommends that Clinical Translational Science Awards, with their unique geographical, systems, and historical characteristics, actively participate in deepening our understanding of stakeholder engagement science and methods within implementation and dissemination research. These recommendations include (a) development of an inventory of successful stakeholder engagement strategies; (b) coordination and intentionally testing a variety of stakeholder engagement strategies; (c) tool kit development; and (d) identification of fundamental motivators and logic models for stakeholder engagement to help align stakeholders and researchers.