Understanding tailoring to support the implementation of evidence-based interventions in healthcare: The CUSTOMISE research programme protocol.

Although there are effective evidence-based interventions (EBIs) to prevent, treat and coordinate care for chronic conditions they may not be adopted widely and when adopted, implementation challenges can limit their impact.  Implementation strategies are "methods or techniques used to enhance the adoption, implementation, and sustainment of a clinical program or practice". There is some evidence to suggest that to be more effective,  strategies should be tailored; that is, selected and designed to address specific determinants which may influence implementation in a given context. Despite the growing popularity of tailoring the concept is ill-defined, and the way in which tailoring is applied can vary across studies or lack detail when reported. There has been less focus on the part of tailoring where stakeholders prioritise determinants and select strategies, and the way in which theory, evidence and stakeholders' perspectives should be combined to make decisions during the process. Typically, tailoring is evaluated based on the effectiveness of the tailored strategy, we do not have a clear sense of the mechanisms through which tailoring works, or how to measure the "success" of the tailoring process. We lack an understanding of how stakeholders can be involved effectively in tailoring and the influence of different approaches on the outcome of tailoring. Our research programme, CUSTOMISE (Comparing and Understanding Tailoring Methods for Implementation Strategies in healthcare) will address some of these outstanding questions and generate evidence on  the feasibility, acceptability, and efficiency of different tailoring approaches, and build capacity in implementation science in Ireland, developing and delivering training and supports for, and network of, researchers and implementation practitioners. The evidence generated across the studies conducted as part of CUSTOMISE will bring greater clarity, consistency, coherence, and transparency to tailoring, a key process in implementation science.

Proposing the observational-implementation hybrid approach: designing observational research for rapid translation.

We propose the observational-implementation hybrid approach-the incorporation of implementation science methods and measures into observational studies to collect information that would allow researchers to anticipate, estimate, or infer the effects of interventions and implementation strategies. Essentially, we propose that researchers collect implementation data early in the research pipeline, in situations where they might not typically be thinking about implementation science. We describe three broad contextual scenarios through which the observational-implementation hybrid approach would most productively be applied. The first application is for observational cohorts that individually enroll participants-either for existing (to which implementation concepts could be added) or for newly planned studies. The second application is with routinely collected program data, at either the individual or aggregate levels. The third application is to the collection of data from study participants enrolled in an observational cohort study who are also involved in interventions linked to that study (e.g., collecting data about their experiences with those interventions). Examples of relevant implementation data that could be collected as part of observational studies include factors relevant to transportability, participant preferences, and participant/provider perspectives regarding interventions and implementation strategies. The observational-implementation hybrid model provides a practical approach to make the research pipeline more efficient and to decrease the time from observational research to health impact. If this approach is widely adopted, observational and implementation science studies will become more integrated; this will likely lead to new collaborations, will encourage the expansion of epidemiological training, and, we hope, will push both epidemiologists and implementation scientists to increase the public health impact of their work.

Conceptual tensions and practical trade-offs in tailoring implementation interventions.

Tailored interventions have been shown to be effective and tailoring is a popular process with intuitive appeal for researchers and practitioners. However, the concept and process are ill-defined in implementation science. Descriptions of how tailoring has been applied in practice are often absent or insufficient in detail. This lack of transparency makes it difficult to synthesize and replicate efforts. It also hides the trade-offs for researchers and practitioners that are inherent in the process. In this article we juxtapose the growing prominence of tailoring with four key questions surrounding the process. Specifically, we ask: (1) what constitutes tailoring and when does it begin and end?; (2) how is it expected to work?; (3) who and what does the tailoring process involve?; and (4) how should tailoring be evaluated? We discuss these questions as a call to action for better reporting and further research to bring clarity, consistency, and coherence to tailoring, a key process in implementation science.

Obesity prevention practices in early care and education settings: an adaptive implementation trial.

BACKGROUND: Despite the potential for Early Care and Education (ECE) settings to promote healthy habits, a gap exists between current practices and evidence-based practices (EBPs) for obesity prevention in childhood. METHODS: We will use an enhanced non-responder trial design to determine the effectiveness and incremental cost-effectiveness of an adaptive implementation strategy for Together, We Inspire Smart Eating (WISE), while examining moderators and mediators of the strategy effect. WISE is a curriculum that aims to increase children's intake of carotenoid-rich fruits and vegetables through four evidence-based practices in the early care and education setting. In this trial, we will randomize sites that do not respond to low-intensity strategies to either (a) continue receiving low-intensity strategies or (b) receive high-intensity strategies. This design will determine the effect of an adaptive implementation strategy that adds high-intensity versus one that continues with low-intensity among non-responder sites. We will also apply explanatory, sequential mixed methods to provide a nuanced understanding of implementation mechanisms, contextual factors, and characteristics of sites that respond to differing intensities of implementation strategies. Finally, we will conduct a cost effectiveness analysis to estimate the incremental effect of augmenting implementation with high-intensity strategies compared to continuing low-intensity strategies on costs, fidelity, and child health outcomes. DISCUSSION: We expect our study to contribute to an evidence base for structuring implementation support in real-world ECE contexts, ultimately providing a guide for applying the adaptive implementation strategy in ECE for WISE scale-up. Our work will also provide data to guide implementation decisions of other interventions in ECE. Finally, we will provide the first estimate of relative value for different implementation strategies in this setting. TRIAL REGISTRATION: NCT05050539 ; 9/20/21.

A mixed-methods protocol for identifying successful sustainability strategies for nutrition and physical activity interventions in childcare.

BACKGROUND: Despite the importance of sustainability for nutrition and physical activity in public health interventions, limited studies have explored the factors that promote and inhibit evidence-based program sustainment in the childcare setting. This study protocol describes a mixed-methods approach to develop novel sustainability strategies based on real-world settings and stakeholder feedback, with the goal of providing support for future obesity prevention programs and related studies on intervention sustainability. Two interventions, Together, We Inspire Smart Eating (WISE) and The Food Friends' (FF) Fun with New Foods and Get Movin' with Might Moves, are studied to this end. METHODS: The study will deploy an explanatory, sequential mixed-methods design. First, the research team will collect a quantitative survey to assess rates of sustainment among WISE and Food Friends sites. We expect to collect 150 surveys from WISE and FF sites combined. Data from these surveys will be used to purposively sample sites for 12 to 18 site visits. Specifically, we will purposively sample low, partial, and high sustaining sites where we will conduct key informant interviews and focus groups as well as validate self-reports on sustainability. Survey content, qualitative interviews, and coding will be based on the Dynamic Sustainability Framework. We will draw on findings from the quantitative survey on predictors of sustainment and the qualitative site visits to understand varying levels of program sustainment. Then, we will utilize evidence-based quality improvement sessions to engage stakeholders in developing a multi-component sustainability strategy. DISCUSSION: This study will provide a stakeholder-informed sustainability strategy ready for testing in a full-scale trial examining effects on sustainment of evidence-based nutrition and physical activity practices in childcare. We expect this strategy to be relevant for educators and consistent with the views of administrators as a guide for future practice for the targeted nutrition and physical activity interventions and beyond.

De-implementation of detrimental feeding practices: a pilot protocol.

BACKGROUND: Early childhood educators (ECEs) often use detrimental feeding practices and are slow to implement positive feeding practices. Nevertheless, few studies have aimed to understand and change ECEs' feeding practices. This gap needs to be addressed because implementation (i.e., adding new, evidence-based practices) and de-implementation (i.e., stopping low-value or harmful practices) are distinct processes that require unique strategies. METHODS: We will develop a de-implementation strategy for detrimental feeding practices using evidence-based quality improvement (EBQI) sessions to engage stakeholders and draw on the Niven process model for de-implementation. Then, we will investigate the effects of the de-implementation strategy in a proof-of-principle study. The de-implementation strategy will be evaluated in 2 partnering childcare agencies using a pre-post, within-site design. For our primary outcome, we will interview educators throughout the school year to assess the feasibility and acceptability of the intervention and survey them with standard measures for assessing feasibility and acceptability. For secondary outcomes, we will investigate its effects on the use of detrimental and evidence-based feeding practices by teachers and impacts on child BMI and diet. DISCUSSION: The current study will establish the feasibility and acceptability of our de-implementation approach and will provide preliminary data toward 3 predicted secondary outcomes: (1) decreased detrimental feeding practices by ECEs, (2) increased adoption of and fidelity to nutrition promotion practices, and (3) improved child dietary outcomes. These results are expected to contribute to the uptake and sustainability of mealtime interventions to improve the diets of young children. Results will also apply to the field of implementation science by informing processes for developing de-implementation approaches in a community setting.

Implementation Science and Nutrition Education and Behavior: Opportunities for Integration.

Implementation science (IS) is the study of approaches designed to increase adoption and sustainability of research evidence into routine practice. This article provides an overview of IS and ideas for its integration with nutrition education and behavior practice and research. Implementation science application in nutrition education and behavior practice can inform real-word implementation efforts. Research opportunities include advancing common approaches to implementation measurement. In addition, the article provides suggestions for future studies (eg, comparative effectiveness trials comparing implementation strategies) to advance the knowledge base of both fields. An example from ongoing research is included to illustrate concepts and methods of IS.

Fidelity monitoring in complex interventions: a case study of the WISE intervention.

BACKGROUND: Researchers face many decisions in developing a measurement tool and protocol for monitoring fidelity to complex interventions. The current study uses data evaluating a nutrition education intervention, Together, We Inspire Smart Eating (WISE), in a preschool setting to explore issues of source, timing, and frequency of fidelity monitoring. METHODS: The overall study from which these data are drawn was a pre/post design with an implementation-focused process evaluation. Between 2013 and 2016, researchers monitored fidelity to evidence-based components of the WISE intervention in 49 classrooms in two Southern states. Data collectors obtained direct assessment of fidelity on a monthly basis in study classrooms. Research staff requested that educators provide indirect assessment on a weekly basis. We used mean comparisons (t-tests), correlations (Pearson's r), and scatterplots to compare the direct and indirect assessments. RESULTS: No mean comparisons were statistically different. Correlations of direct and indirect assessments of the same component for the same month ranged between - 0.51 (p = 0.01) and 0.54 (p = 0.001). Scatterplots illustrate that negative correlations can be driven by individuals who are over reporting (i.e., self-report bias) and that near zero correlations approximate the ideal situation (i.e., both raters identify high fidelity). CONCLUSION: Our findings illustrate that, on average, observed and self-reports may seem consistent despite weak correlations and individual cases of extreme over reporting by those implementing the intervention. The nature of the component to which fidelity is being monitored as well as the timing within the context of the intervention are important factors to consider when selecting the type of assessment and frequency of fidelity monitoring. TRIAL REGISTRATION: NCT03075085 Registered 20 February 2017. Trial registration corresponds to the funding that supported the writing of this manuscript, not the data collection. The original study was not a trial and was collected without registration. However, the data reported here provided foundational preliminary data for the trial.

Rural African Americans' Perspectives on Mental Health: Comparing Focus Groups and Deliberative Democracy Forums.

A number of approaches have been used to obtain community members' health perspectives. Health services researchers often conduct focus groups while political scientists and community groups may hold forums. To compare and contrast these two approaches, we conducted six focus groups (n = 50) and seven deliberative democracy forums (n = 233) to obtain the perspectives of rural African Americans on mental health problems in their community. Inductive qualitative analysis found three common themes: rural African Americans (1) understood stresses of poverty and racism were directly related to mental health, (2) were concerned about widespread mental illness stigma, and (3) thought community members could not identify mental health problems requiring treatment. Deductive analyses identified only minor differences in content between the two approaches. This single case study suggests that researchers could consider using deliberative democracy forums rather than focus groups with marginalized populations, particularly when seeking to mobilize communities to create community-initiated interventions.

Use of electronic medical record data for quality improvement in schizophrenia treatment.

An understanding of the strengths and limitations of automated data is valuable when using administrative or clinical databases to monitor and improve the quality of health care. This study discusses the feasibility and validity of using data electronically extracted from the Veterans Health Administration (VHA) computer database (VistA) to monitor guideline performance for inpatient and outpatient treatment of schizophrenia. The authors also discuss preliminary results and their experience in applying these methods to monitor antipsychotic prescribing using the South Central VA Healthcare Network (SCVAHCN) Data Warehouse as a tool for quality improvement.

Implementation outcomes of evidence-based quality improvement for depression in VA community based outpatient clinics.

BACKGROUND: Collaborative-care management is an evidence-based practice for improving depression outcomes in primary care. The Department of Veterans Affairs (VA) has mandated the implementation of collaborative-care management in its satellite clinics, known as Community Based Outpatient Clinics (CBOCs). However, the organizational characteristics of CBOCs present added challenges to implementation. The objective of this study was to evaluate the effectiveness of evidence-based quality improvement (EBQI) as a strategy to facilitate the adoption of collaborative-care management in CBOCs. METHODS: This nonrandomized, small-scale, multisite evaluation of EBQI was conducted at three VA Medical Centers and 11 of their affiliated CBOCs. The Plan phase of the EBQI process involved the localized tailoring of the collaborative-care management program to each CBOC. Researchers ensured that the adaptations were evidence based. Clinical and administrative staff were responsible for adapting the collaborative-care management program for local needs, priorities, preferences and resources. Plan-Do-Study-Act cycles were used to refine the program over time. The evaluation was based on the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) Framework and used data from multiple sources: administrative records, web-based decision-support systems, surveys, and key-informant interviews. RESULTS: Adoption: 69.0% (58/84) of primary care providers referred patients to the program. Reach: 9.0% (298/3,296) of primary care patients diagnosed with depression who were not already receiving specialty care were enrolled in the program. Fidelity: During baseline care manager encounters, education/activation was provided to 100% (298/298) of patients, barriers were assessed and addressed for 100% (298/298) of patients, and depression severity was monitored for 100% (298/298) of patients. Less than half (42.5%, 681/1603) of follow-up encounters during the acute stage were completed within the timeframe specified. During the acute phase of treatment for all trials, the Patient Health Questionnaire (PHQ9) symptom-monitoring tool was used at 100% (681/681) of completed follow-up encounters, and self-management goals were discussed during 15.3% (104/681) of completed follow-up encounters. During the acute phase of treatment for pharmacotherapy and combination trials, medication adherence was assessed at 99.1% (575/580) of completed follow-up encounters, and side effects were assessed at 92.4% (536/580) of completed follow-up encounters. During the acute phase of treatment for psychotherapy and combination trials, counseling session adherence was assessed at 83.3% (239/287) of completed follow-up encounters. Effectiveness: 18.8% (56/298) of enrolled patients remitted (symptom free) and another 22.1% (66/298) responded to treatment (50% reduction in symptom severity). Maintenance: 91.9% (10/11) of the CBOCs chose to sustain the program after research funds were withdrawn. CONCLUSIONS: Provider adoption was good, although reach into the target population was relatively low. Fidelity and maintenance were excellent, and clinical outcomes were comparable to those in randomized controlled trials. Despite the organizational barriers, these findings suggest that EBQI is an effective facilitation strategy for CBOCs. TRIAL REGISTRATION: Clinical trial # NCT00317018.

Correlates of antiretroviral and antidepressant adherence among depressed HIV-infected patients.

Although crucial for efficacy of pharmacotherapy, adherence to prescribed medication regimens for both antiretrovirals and antidepressants is often suboptimal. As many depressed HIV-infected individuals are prescribed both antiretrovirals and antidepressants, it is important to know whether correlates of nonadherence are similar or different across type of regimen. The HIV Translating Initiatives for Depression into Effective Solutions (HI-TIDES) study was a single-blinded, longitudinal, randomized controlled effectiveness trial comparing collaborative care to usual depression care at three Veterans Affairs HIV clinics. The current investigation utilized self-report baseline interview and chart-abstracted data. Participants were 225 depressed HIV-infected patients who were prescribed an antidepressant (n=146), an antiretroviral (n=192), or both (n=113). Treatment adherence over the last 4 days was dichotomized as "less than 90% adherence" or "90% or greater adherence." After identifying potential correlates of nonadherence, we used a seemingly unrelated regression (SUR) bivariate probit model, in which the probability of adherence to HIV medications and the probability of adherence to antidepressant medications are modeled jointly. Results indicated that 75.5% (n=146) of those prescribed antiretrovirals reported 90%-plus adherence to their antiretroviral prescription and 76.7% (n=112) of those prescribed antidepressants reported 90%-plus adherence to their antidepressant prescription, while 67% of those prescribed both (n=113) reported more than 90% adherence to both regimens. SUR results indicated that education, age, and HIV symptom severity were significant correlates of antiretroviral medication adherence while gender and generalized anxiety disorder diagnosis were significant correlates of adherence to antidepressant medications. In addition, antiretroviral adherence did not predict antidepressant adherence (ß=1.62, p=0.17), however, antidepressant adherence did predict antiretroviral adherence (ß=2.30, p<0.05).

How do components of evidence-based psychological treatment cluster in practice? A survey and cluster analysis.

Evidence-based psychological treatments (EBPTs) are clusters of interventions, but it is unclear how providers actually implement these clusters in practice. A disaggregated measure of EBPTs was developed to characterize clinicians' component-level evidence-based practices and to examine relationships among these practices. Survey items captured components of evidence-based treatments based on treatment integrity measures. The Web-based survey was conducted with 75 U.S. Department of Veterans Affairs (VA) substance use disorder (SUD) practitioners and 149 non-VA community-based SUD practitioners. Clinician's self-designated treatment orientations were positively related to their endorsement of those EBPT components; however, clinicians used components from a variety of EBPTs. Hierarchical cluster analysis indicated that clinicians combined and organized interventions from cognitive-behavioral therapy, the community reinforcement approach, motivational interviewing, structured family and couples therapy, 12-step facilitation, and contingency management into clusters including empathy and support, treatment engagement and activation, abstinence initiation, and recovery maintenance. Understanding how clinicians use EBPT components may lead to improved evidence-based practice dissemination and implementation.