BackgroundThis systematic review assessed the effectiveness of capacity building interventions relevant to public health practice. The aim is to inform and improve capacity building interventions.MethodsFour strategies were used: 1) electronic database searching; 2) reference lists of included papers; 3) key informant consultation; and 4) grey literature searching. Inclusion (e.g., published in English) and exclusion criteria (e.g., non-English language papers published earlier than 2005) are outlined with included papers focusing on capacity building, learning plans, or professional development plans within public health and related settings, such as non-governmental organizations, government, or community-based organizations relating to public health or healthcare. Outcomes of interest included changes in knowledge, skill or confidence (self-efficacy), changes in practice (application or intent), and perceived support or supportive environments, with outcomes reported at the individual, organizational or systems level(s). Quality assessment of all included papers was completed.ResultsFourteen papers were included in this review. These papers reported on six intervention types: 1) internet-based instruction, 2) training and workshops, 3) technical assistance, 4) education using self-directed learning, 5) communities of practice, and 6) multi-strategy interventions. The available literature showed improvements in one or more capacity-building outcomes of interest, mainly in terms of individual-level outcomes. The available literature was moderate in quality and showed a range of methodological issues.ConclusionsThere is evidence to inform capacity building programming and how interventions can be selected to optimize impact. Organizations should carefully consider methods for analysis of capacity building interventions offered; specifically, through which mechanisms, to whom, and for which purpose. Capacity-building interventions can enhance knowledge, skill, self-efficacy (including confidence), changes in practice or policies, behaviour change, application, and system-level capacity. However in applying available evidence, organizations should consider the outcomes of highest priority, selecting intervention(s) effective for the outcome(s) of interest. Examples are given for selecting intervention(s) to match priorities and context, knowing effectiveness evidence is only one consideration in decision making. Future evaluations should: extend beyond the individual level, assess outcomes at organizational and systems levels, include objective measures of effect, assess baseline conditions, and evaluate features most critical to the success of interventions.Electronic supplementary materialThe online version of this article (10.1186/s12889-018-5591-6) contains supplementary material, which is available to authorized users.

BackgroundThere is limited research on capacity building interventions that include theoretical foundations. The purpose of this systematic review is to identify underlying theories, models and frameworks used to support capacity building interventions relevant to public health practice. The aim is to inform and improve capacity building practices and services offered by public health organizations.MethodsFour search strategies were used: 1) electronic database searching; 2) reference lists of included papers; 3) key informant consultation; and 4) grey literature searching. Inclusion and exclusion criteria are outlined with included papers focusing on capacity building, learning plans, professional development plans in combination with tools, resources, processes, procedures, steps, model, framework, guideline, described in a public health or healthcare setting, or non-government, government, or community organizations as they relate to healthcare, and explicitly or implicitly mention a theory, model and/or framework that grounds the type of capacity building approach developed. Quality assessment were performed on all included articles. Data analysis included a process for synthesizing, analyzing and presenting descriptive summaries, categorizing theoretical foundations according to which theory, model and/or framework was used and whether or not the theory, model or framework was implied or explicitly identified.ResultsNineteen articles were included in this review. A total of 28 theories, models and frameworks were identified. Of this number, two theories (Diffusion of Innovations and Transformational Learning), two models (Ecological and Interactive Systems Framework for Dissemination and Implementation) and one framework (Bloom’s Taxonomy of Learning) were identified as the most frequently cited.ConclusionsThis review identifies specific theories, models and frameworks to support capacity building interventions relevant to public health organizations. It provides public health practitioners with a menu of potentially usable theories, models and frameworks to support capacity building efforts. The findings also support the need for the use of theories, models or frameworks to be intentional, explicitly identified, referenced and for it to be clearly outlined how they were applied to the capacity building intervention.Electronic supplementary materialThe online version of this article (10.1186/s12889-017-4919-y) contains supplementary material, which is available to authorized users.

Setting The Ontario government implemented a regulatory change to mandate the collection of socio-demographic (SD) data for individuals who tested positive for COVID-19. This change was informed by evidence of COVID-19’s disproportionate impact on marginalized communities and calls for broader collection of SD data. Given the scarcity of similar efforts, there is a significant knowledge gap around implementing standardized SD data collection in public health settings. Intervention Public Health Ontario provided collaborative support for the implementation of SD data collection, grounded in health equity principles, evidence, and best practices. We supported the addition of SD fields in Ontario’s COVID-19 data collection systems, issued data entry guidance, hosted webinars for training and learning exchange, and published a resource to support the data collection process. The current focus is on building sustainability and quality improvement through continued engagement of public health units. Outcomes By November 28, 2020, almost 80% of COVID-19 cases had information recorded for at least one SD question (individual questions, range 46.8–67.0%). We hosted three webinars for the field, and the data collection resource was viewed almost 650 times. Practitioners continue to express needs for support on applying equity principles to data analysis and interpretation, and community engagement on data collection and use. Implications Sharing knowledge on responsive implementation supports in collaboration with the field and using current evidence and guidance will strengthen public health practice for SD data collection. Laying this groundwork will also improve the likelihood of success and sustainability of these equity-focused efforts.