Implementation science has great potential to improve the health of communities and individuals who are not achieving health equity. However, implementation science can exacerbate health disparities if its use is biased toward entities that already have the highest capacities for delivering evidence-based interventions. In this article, we examine several methodologic approaches for conducting implementation research to advance equity both in our understanding of what historically disadvantaged populations would need—what we call scientific equity—and how this knowledge can be applied to produce health equity. We focus on rapid ways to gain knowledge on how to engage, design research, act, share, and sustain successes in partnership with communities. We begin by describing a principle-driven partnership process between community members and implementation researchers to overcome disparities. We then review three innovative implementation method paradigms to improve scientific and health equity and provide examples of each. The first paradigm involves making efficient use of existing data by applying epidemiologic and simulation modeling to understand what drives disparities and how they can be overcome. The second paradigm involves designing new research studies that include, but do not focus exclusively on, populations experiencing disparities in health domains such as cardiovascular disease and co-occurring mental health conditions. The third paradigm involves implementation research that focuses exclusively on populations who have experienced high levels of disparities. To date, our scientific enterprise has invested disproportionately in research that fails to eliminate health disparities. The implementation research methods discussed here hold promise for overcoming barriers and achieving health equity.Ethn Dis. 2019;29(Suppl 1):83-92; doi:10.18865/ed.29.S1.83.
What progress prevention research has made comes through strategic partnerships with communities and institutions that host this research, as well as professional and practice networks that facilitate the diffusion of knowledge about prevention. We discuss partnership issues related to the design, analysis, and implementation of prevention research and especially how rigorous designs, including random assignment, get resolved through a partnership between community stakeholders, institutions, and researchers. These partnerships shape not only study design, but they determine the data that can be collected and how results and new methods are disseminated. We also examine a second type of partnership to improve the implementation of effective prevention programs into practice. We draw on social networks to studying partnership formation and function. The experience of the Prevention Science and Methodology Group, which itself is a networked partnership between scientists and methodologists, is highlighted.
BackgroundPediatric obesity is a multi-faceted public health concern that can lead to cardiovascular diseases, cancers, and early mortality. Small changes in diet, physical activity, or BMI can significantly reduce the possibility of developing cardiometabolic risk factors. Family-based behavioral interventions are an underutilized, evidence-based approach that have been found to significantly prevent excess weight gain and obesity in children and adolescents. Poor program availability, low participation rates, and non-adherence are noted barriers to positive outcomes. Effective interventions for pediatric obesity in primary care are hampered by low family functioning, motivation, and adherence to recommendations.MethodsThis (type II) hybrid effectiveness–implementation randomized trial tests the Family Check-Up 4 Health (FCU4Health) program, which was designed to target health behavior change in children by improving family management practices and parenting skills, with the goal of preventing obesity and excess weight gain. The FCU4Health is assessment driven to tailor services and increase parent motivation. A sample of 350 families with children aged 6 to 12 years who are identified as overweight or obese (BMI ≥ 85th percentile for age and gender) will be enrolled at three primary care clinics [two Federally Qualified Healthcare Centers (FQHCs) and a children’s hospital]. All clinics serve predominantly Medicaid patients and a large ethnic minority population, including Latinos, African Americans, and American Indians who face disparities in obesity, cardiometabolic risk, and access to care. The FCU4Health will be coordinated with usual care, using two different delivery strategies: an embedded approach for the two FQHCs and a referral model for the hospital-based clinic. To assess program effectiveness (BMI, body composition, child health behaviors, parenting, and utilization of support services) and implementation outcomes (such outcomes as acceptability, adoption, feasibility, appropriateness, fidelity, and cost), we use a multi-method and multi-informant assessment strategy including electronic health record data, behavioral observation, questionnaires, interviews, and cost capture methods.DiscussionThis study has the potential to prevent excess weight gain, obesity, and health disparities in children by establishing the effectiveness of the FCU4Health and collecting information critical for healthcare decision makers to support sustainable implementation of family-based programs in primary care.Trial registrationNCT03013309 ClinicalTrials.govElectronic supplementary materialThe online version of this article (10.1186/s13012-017-0697-2) contains supplementary material, which is available to authorized users.
Careful fidelity monitoring and feedback are critical to implementing effective interventions. A wide range of procedures exist to assess fidelity; most are derived from observational assessments (Schoenwald et al, 2013). However, these fidelity measures are resource intensive for research teams in efficacy/effectiveness trials, and are often unattainable or unmanageable for the host organization to rate when the program is implemented on a large scale. We present a first step towards automated processing of linguistic patterns in fidelity monitoring of a behavioral intervention using an innovative mixed methods approach to fidelity assessment that uses rule-based, computational linguistics to overcome major resource burdens. Data come from an effectiveness trial of the Familias Unidas intervention, an evidence-based, family-centered preventive intervention found to be efficacious in reducing conduct problems, substance use and HIV sexual risk behaviors among Hispanic youth. This computational approach focuses on “joining,” which measures the quality of the working alliance of the facilitator with the family. Quantitative assessments of reliability are provided. Kappa scores between a human rater and a machine rater for the new method for measuring joining reached .83. Early findings suggest that this approach can reduce the high cost of fidelity measurement and the time delay between fidelity assessment and feedback to facilitators; it also has the potential for improving the quality of intervention fidelity ratings.
In 2019, the requisite biomedical and behavioral interventions to eliminate new HIV infections exist. "Ending the HIV Epidemic" now becomes primarily a challenge of will and implementation. This review maps the extent to which implementation research (IR) has been integrated into HIV research by reviewing the recent funding portfolio of the NIH. We searched NIH RePORTER for HIV and IR-related research projects funded from January 2013 to March 2018. The 4629 unique studies identified were screened using machine learning and manual methods. 216 abstracts met the eligibility criteria of HIV and IR. Key study characteristics were then abstracted. NIH currently funds HIV studies that are either formally IR (n = 109) or preparatory for IR (n = 107). Few (13%) projects mentioned a guiding implementation model, theory, or framework, and only 56% of all studies explicitly mentioned measuring an implementation outcome. Considering the study aims along an IR continuum, 18 (8%) studies examined barriers and facilitators, 43 (20%) developed implementation strategies, 46 (21%) piloted strategies, 73 (34%) tested a single strategy, and 35 (16%) compared strategies. A higher proportion of formal IR projects involved established interventions (e.g., integrated services) compared to newer interventions (e.g., pre-exposure prophylaxis). Prioritizing HIV-related IR in NIH and other federal funding opportunity announcements and expanded training in implementation science could have a substantial impact on ending the HIV pandemic. This review serves as a baseline by which to compare funding patterns and the sophistication of IR in HIV research over time.
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