Community-based organizations (CBOs) are important equity-promoting delivery channels for evidence-based interventions (EBIs). However, CBO practitioners often cannot access needed support to build EBI skills. Additionally, the capacity-building literature is hindered by inconsistent definitions, limited use of validated measures, and an emphasis on the perspectives of EBI developers versus implementers. To address these gaps, we explored commonalities and differences between CBO practitioners and academics in conceptualizing and prioritizing core EBI skills.

We utilized Group Concept Mapping, a mixed-methods approach connecting qualitative data (e.g., regarding the range of critical EBI skills) and quantitative data (e.g., sorting and ranking data regarding unique skills) to create conceptual maps integrating perspectives from diverse participants. A total of 34 practitioners and 30 academics working with cancer inequities participated in the study.

Participants nominated 581 core skills for EBI use, and our team (including practitioners and academics) identified 98 unique skills from this list. Participants sorted them into conceptual groups, yielding five clusters: (1) using data and evaluation, (2) selecting and adapting EBIs, (3) connecting with community members, (4) building diverse and equitable partnerships, and (5) managing EBI implementation. The ordering of importance and presence of skill clusters were similar across groups. Overall, importance was rated higher than presence, suggesting capacity gaps.

There are helpful commonalities between practitioners’ and academics’ views of core EBI skills in CBOs and apparent capacity gaps. However, underlying patterns suggest that differences between the groups’ perceptions warrant further exploration.

Community-based organizations (CBOs) are well-positioned to incorporate research evidence, local expertise, and contextual factors to address health inequities. However, insufficient capacity limits use of evidence-based interventions (EBIs) in these settings. Capacity-building implementation strategies are popular, but a lack of standard models and validated measures hinders progress in the field. To advance the literature, we conducted a comprehensive scoping review.

With a reference librarian, we executed a comprehensive search strategy of PubMed/Medline, Web of Science Core Collection, and EBSCO Global Health. We included articles that addressed implementation science, capacity-building, and CBOs. Of 5527 articles, 99 met our inclusion criteria, and we extracted data using a double-coding process

Of the 99 articles, 47% defined capacity explicitly, 31% defined it indirectly, and 21% did not define it. Common concepts in definitions were skills, knowledge/expertise, and resources. Of the 57 articles with quantitative analysis, 48 (82%) measured capacity, and 11 (23%) offered psychometric data for the capacity measures. Of the 99 studies, 40% focused exclusively on populations experiencing inequities and 22% included those populations to some extent. The bulk of the studies came from high-income countries.

Implementation scientists should 1) be explicit about models and definitions of capacity and strategies for building capacity, 2) specify expected multi-level implementation outcomes, 3) develop and use validated measures for quantitative work, and 4) integrate equity considerations into the conceptualization and measurement of capacity-building efforts. With these refinements, we can ensure that the necessary supports reach CBO practitioners and critical partners for addressing health inequities.

To expedite the use of evidence-based smoking cessation interventions (EBSCIs) in primary care and to thereby increase the number of successful quit attempts, a referral aid was developed. This aid aims to optimize the referral to and use of EBSCIs in primary care and to increase adherence to Dutch guidelines for smoking cessation.

Practice nurses (PNs) will be randomly allocated to an experimental condition or control condition, and will then recruit smoking patients who show a willingness to quit smoking within six months. PNs allocated to the experimental condition will provide smoking cessation guidance in accordance with the referral aid. Patients from both conditions will receive questionnaires at baseline and after six months. Cessation effectiveness will be tested via multilevel logistic regression analyses. Multiple imputations as well as intention to treat analysis will be performed. Intervention appreciation and level of informed decision-making will be compared using analysis of (co)variance. Predictors for appreciation and informed decision-making will be assessed using multiple linear regression analysis and/or structural equation modeling. Finally, a cost-effectiveness study will be conducted.

This paper describes the study design for the development and evaluation of an information and decision tool to support PNs in their guidance of smoking patients and their referral to EBSCIs. The study aims to provide insight into the (cost) effectiveness of an intervention aimed at expediting the use of EBSCIs in primary care.