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Abstract Background Family Navigation (FN) is an evidence-based care management intervention designed to reduce disparities in access to care by providing families with individually tailored support and care coordination. Early data suggest FN is effective, but effectiveness is significantly influenced by both contextual (e.g. setting) and individual (e.g., ethnicity) variables. To better understand how FN could be tailored to address this variability in effectiveness, we set forth to explore proposed adaptations to FN by both navigators and families who received FN. Methods This study was a nested qualitative study set within a larger randomized clinical trial of FN to improve access to autism diagnostic services in urban pediatric primary care practices in Massachusetts, Pennsylvania, and Connecticut serving low-income, racial and ethnic minority families. Following FN implementation, key informant interviews were conducted based on the Framework for Reporting Adaptations and Modifications-Expanded (FRAME) with a purposeful sample of parents of children who received FN (n = 21) and navigators (n = 7). Interviews were transcribed verbatim and were coded using framework-guided rapid analysis to categorize proposed adaptations to FN. Results Parents and navigators proposed 38 adaptations in four domains: 1) content of the intervention (n = 18), 2) context of the intervention (n = 10), 3) training and evaluation (n = 6), and 4) implementation and scale-up (n = 4). The most frequently endorsed adaptation recommendations focused on content (e.g., lengthening FN, providing parents with additional education on autism and parenting children with autism) and implementation (e.g., increasing access to navigation). Although probes targeted critical feedback, parents and navigators were overwhelmingly positive about FN. Conclusions This study builds upon prior FN effectiveness and implementation research by providing concrete areas for adaptation and refinement of the intervention. Recommendations by parents and navigators have the potential to inform improvement of existing navigation programs and development of new programs in similarly underserved populations. These findings are critical as adaptation (cultural and otherwise) is an important principle in the field of health equity. Ultimately, adaptations will need to be tested to determine clinical and implementation effectiveness. Trial registration ClinicalTrials.gov, registration number NCT02359084, February 9, 2015.

Abstract Background The Multiphase Optimization Strategy (MOST) is designed to maximize the impact of clinical healthcare interventions, which are typically multicomponent and increasingly complex. MOST often relies on factorial experiments to identify which components of an intervention are most effective, efficient, and scalable. When assigning participants to conditions in factorial experiments, researchers must be careful to select the assignment procedure that will result in balanced sample sizes and equivalence of covariates across conditions while maintaining unpredictability. Methods In the context of a MOST optimization trial with a 2x2x2x2 factorial design, we used computer simulation to empirically test five subject allocation procedures: simple randomization, stratified randomization with permuted blocks, maximum tolerated imbalance (MTI), minimal sufficient balance (MSB), and minimization. We compared these methods across the 16 study cells with respect to sample size balance, equivalence on key covariates, and unpredictability. Leveraging an existing dataset to compare these procedures, we conducted 250 computerized simulations using bootstrap samples of 304 participants. Results Simple randomization, the most unpredictable procedure, generated poor sample balance and equivalence of covariates across the 16 study cells. Stratified randomization with permuted blocks performed well on stratified variables but resulted in poor equivalence on other covariates and poor balance. MTI, MSB, and minimization had higher complexity and cost. MTI resulted in balance close to pre-specified thresholds and a higher degree of unpredictability, but poor equivalence of covariates. MSB had 19.7% deterministic allocations, poor sample balance and improved equivalence on only a few covariates. Minimization was most successful in achieving balanced sample sizes and equivalence across a large number of covariates, but resulted in 34% deterministic allocations. Small differences in proportion of correct guesses were found across the procedures. Conclusions Based on the computer simulation results and priorities within the study context, minimization with a random element was selected for the planned research study. Minimization with a random element, as well as computer simulation to make an informed randomization procedure choice, are utilized infrequently in randomized experiments but represent important technical advances that researchers implementing multi-arm and factorial studies should consider.

Abstract Background Delivery of behavioral interventions is complex, as the majority of interventions consist of multiple components used either simultaneously, sequentially, or both. The importance of clearly delineating delivery strategies within these complex interventions—and furthermore understanding the impact of each strategy on effectiveness—has recently emerged as an important facet of intervention research. Yet, few methodologies exist to prospectively test the effectiveness of delivery strategies and how they impact implementation. In the current paper, we describe a study protocol for a large randomized controlled trial in which we will use the Multiphase Optimization Strategy (MOST), a novel framework developed to optimize interventions, i.e., to test the effectiveness of intervention delivery strategies using a factorial design. We apply this framework to delivery of Family Navigation (FN), an evidence-based care management strategy designed to reduce disparities and improve access to behavioral health services, and test four components related to its implementation. Methods/design The MOST framework contains three distinct phases: Preparation, Optimization, and Evaluation. The Preparation phase for this study occurred previously. The current study consists of the Optimization and Evaluation phases. Children aged 3-to-12 years old who are detected as “at-risk” for behavioral health disorders (n = 304) at a large, urban federally qualified community health center will be referred to a Family Partner—a bicultural, bilingual member of the community with training in behavioral health and systems navigation—who will perform FN. Families will then be randomized to one of 16 possible combinations of FN delivery strategies (2 × 2 × 2× 2 factorial design). The primary outcome measure will be achieving a family-centered goal related to behavioral health services within 90 days of randomization. Implementation data on the fidelity, acceptability, feasibility, and cost of each strategy will also be collected. Results from the primary and secondary outcomes will be reviewed by our team of stakeholders to optimize FN delivery for implementation and dissemination based on effectiveness, efficiency, and cost. Discussion In this protocol paper, we describe how the MOST framework can be used to improve intervention delivery. These methods will be useful for future studies testing intervention delivery strategies and their impact on implementation. Trial registration ClinicalTrials.gov, NCT03569449. Registered on 26 June 2018.

Abstract Background Significant racial, ethnic, and socioeconomic disparities exist in access to evidence-based treatment services for children with autism spectrum disorder (ASD). Patient Navigation (PN) is a theory-based care management strategy designed to reduce disparities in access to care. The purpose of this study is to test the effectiveness of PN a strategy to reduce disparities in access to evidence-based services for vulnerable children with ASD, as well as to explore factors that impact implementation. Methods This study uses a hybrid type I randomized effectiveness/implementation design to test effectiveness and collect data on implementation concurrently. It is a two-arm comparative effectiveness trial with a target of 125 participants per arm. Participants are families of children age 15–27 months who receive a positive screen for ASD at a primary care visit at urban clinics in Massachusetts (n = 6 clinics), Connecticut (n = 1), and Pennsylvania (n = 2). The trial measures diagnostic interval (number of days from positive screen to diagnostic determination) and time to receipt of evidence-based ASD services/recommended services (number of days from date of diagnosis to receipt of services) in those with PN compared to and activated control -Conventional Care Management – which is similar to care management received in a high quality medical home. At the same time, a mixed-method implementation evaluation is being carried out. Discussion This study will examine the effectiveness of PN to reduce the time to and receipt of evidence-based services for vulnerable children with ASD, as well as factors that influence implementation. Findings will tell us both if PN is an effective approach for improving access to evidence-based care for children with ASD, and inform future strategies for dissemination. Trial registration NCT02359084 Registered February 1, 2015.