Improving Sexual Assault and Sexual Harassment Prevention from the Bottom-up: a Pilot of Getting To Outcomes in the US Military.

While the Department of Defense (DoD) has given increased attention and priority to preventing sexual assault and sexual harassment (SA/SH), it remains a problem. To build its prevention capacity, DoD piloted Getting To Outcomes® (GTO®) from 2019 to 2022 at 10 military installations. GTO is an evidence-based planning and implementation support that has been used in many civilian contexts but has only recently been adapted for military SA/SH. The purpose of this study was to describe GTO use, identify its benefits and challenges, and discuss lessons the GTO effort yielded for prevention more broadly using a framework of organizational and program-level capacities needed for successful prevention in the military context, called the Prevention Evaluation Framework (PEF). GTO was piloted with 10 military installations ("sites") representing all Military Services, plus the Coast Guard and National Guard. GTO is comprised of a written guide, training, and ongoing coaching. The pilot's goal was for each site to use GTO to implement a SA/SH prevention program twice. Participants from each site were interviewed and data was collected on GTO steps completed, whether GTO spurred new evaluation activities and collaborations, and the degree of leadership support for GTO. Most sites completed all GTO steps at least once. Interviews showed that DoD participants believe GTO improved prevention understanding, planning, and evaluation capacity; strengthened confidence in chosen programs; and helped sites tailor programs to the military context. Barriers were the complexity of GTO, DoD personnel turnover, and the disruption that the COVID pandemic caused in sexual assault prevention program delivery. Many respondents were unsure if they would continue all of GTO after the coaching ended, but many believed they would continue at least some parts. According to the PEF, the GTO pilot revealed several additional prevention system gaps (e.g., need for leadership support) and changes needed to GTO (e.g., stronger leader and champion engagement), to support quality prevention. The military and other large organizations will need to focus on these issues to ensure prevention implementation and evaluation are conducted with quality.

Examining readiness for implementing practice changes in federally qualified health centers: A rapid qualitative study.

Implementing evidence-based interventions remains slow in federally qualified health centers (FQHCs). The purpose of this study is to qualitatively examine the R = MC2 (Readiness = motivation × innovation specific capacity × general capacity) heuristic subcomponents in the context of implementing general and colorectal cancer screening (CRCS)-related practice changes in FQHCs. We conducted 17 interviews with FQHC employees to examine (1) experiences with successful or unsuccessful practice change efforts, (2) using approaches to promote CRCS, and (3) opinions about R = MC2 subcomponents. We conducted a rapid qualitative analysis to examine the frequency, depth, and spontaneity of subcomponents. Priority, compatibility, observability (motivation), intra- and interorganizational relationships (innovation-specific capacity), and organizational structure and resource utilization (general capacity) emerged as highly relevant. For example, organizational structure was described as related to an organization's open communication during meetings to help with scheduling procedures. The results contribute to understanding organizational readiness in the FQHC setting and can be helpful when identifying and prioritizing barriers and facilitators that affect implementation.

Using cognitive interviews to improve a measure of organizational readiness for implementation.

BACKGROUND: Organizational readiness is a key factor for successful implementation of evidence-based interventions (EBIs), but a valid and reliable measure to assess readiness across contexts and settings is needed. The R = MC2 heuristic posits that organizational readiness stems from an organization's motivation, capacity to implement a specific innovation, and its general capacity. This paper describes a process used to examine the face and content validity of items in a readiness survey developed to assess organizational readiness (based on R = MC2) among federally qualified health centers (FQHC) implementing colorectal cancer screening (CRCS) EBIs. METHODS: We conducted 20 cognitive interviews with FQHC staff (clinical and non-clinical) in South Carolina and Texas. Participants were provided a subset of items from the readiness survey to review. A semi-structured interview guide was developed to elicit feedback from participants using "think aloud" and probing techniques. Participants were recruited using a purposive sampling approach and interviews were conducted virtually using Zoom and WebEx. Participants were asked 1) about the relevancy of items, 2) how they interpreted the meaning of items or specific terms, 3) to identify items that were difficult to understand, and 4) how items could be improved. Interviews were transcribed verbatim and coded in ATLAS.ti. Findings were used to revise the readiness survey. RESULTS: Key recommendations included reducing the survey length and removing redundant or difficult to understand items. Additionally, participants recommended using consistent terms throughout (e.g., other units/teams vs. departments) the survey and changing pronouns (e.g., people, we) to be more specific (e.g., leadership, staff). Moreover, participants recommended specifying ambiguous terms (e.g., define what "better" means). CONCLUSION: Use of cognitive interviews allowed for an engaged process to refine an existing measure of readiness. The improved and finalized readiness survey can be used to support and improve implementation of CRCS EBIs in the clinic setting and thus reduce the cancer burden and cancer-related health disparities.

What does it mean to be affiliated with care?: Delphi consensus on the definition of "unaffiliation" and "specialist" in sickle cell disease.

Accruing evidence reveals best practices for how to help individuals living with Sickle Cell Disease (SCD); yet, the implementation of these evidence-based practices in healthcare settings is lacking. The Sickle Cell Disease Implementation Consortium (SCDIC) is a national consortium that uses implementation science to identify and address barriers to care in SCD. The SCDIC seeks to understand how and why patients become unaffiliated from care and determine strategies to identify and connect patients to care. A challenge, however, is the lack of agreed-upon definition for what it means to be unaffiliated and what it means to be a "SCD expert provider". In this study, we conducted a Delphi process to obtain expert consensus on what it means to be an "unaffiliated patient" with SCD and to define an "SCD specialist," as no standard definition is available. Twenty-eight SCD experts participated in three rounds of questions. Consensus was defined as 80% or more of respondents agreeing. Experts reached consensus that an individual with SCD who is unaffiliated from care is "someone who has not been seen by a sickle cell specialist in at least a year." A sickle cell specialist was defined as someone with knowledge and experience in SCD. Having "knowledge" means: being knowledgeable of the 2014 NIH Guidelines, "Evidence-Based Management of SCD", trained in hydroxyurea management and transfusions, trained on screening for organ damage in SCD, trained in pain management and on SCD emergencies, and is aware of psychosocial and cognitive issues in SCD. Experiences that are expected of a SCD specialist include experience working with SCD patients, mentored by a SCD specialist, regular attendance at SCD conferences, and obtains continuing medical education on SCD every 2 years." The results have strong implications for future research, practice, and policy related to SCD by helping to lay a foundation for an new area of research (e.g., to identify subpopulations of unaffiliation and targeted interventions) and policies that support reaffiliation and increase accessibility to quality care.

Using Implementation Mapping to Build Organizational Readiness.

Organizational readiness is essential for high-quality implementation of innovations (programs, policies, practices, or processes). The R = MC2 heuristic describes three readiness components necessary for implementation-the general functioning of the organization (general capacities), the ability to deliver a particular innovation (innovation-specific capacities), and the motivation to implement the innovation. In this article, we describe how we used the Readiness Building System (RBS) for assessing, prioritizing, and improving readiness and Implementation Mapping (IM), a systematic process for planning implementation strategies, to build organizational readiness for implementation of sexual assault prevention evidence-based interventions (EBIs). While RBS provides an overarching approach for assessing and prioritizing readiness constructs (according to the R = MC2 heuristic; Readiness = Motivation x general Capacity × innovation specific Capacity), it does not provide specific guidance on the development and/or selection and tailoring of strategies to improve readiness. We used the five IM tasks to identify and prioritize specific readiness goals and develop readiness-building strategies to improve subcomponents described in the R = MC2 heuristic. This article illustrates how IM can be used synergistically with the RBS in applied contexts to plan implementation strategies that will improve organizational readiness and implementation outcomes. Specifically, we provide an example of using these two frameworks as part of the process of building organizational readiness for implementation of sexual assault prevention EBIs.

Development and pilot test of criteria defining best practices for organizational sexual assault prevention.

Sexual violence affects millions of Americans, and approximately one out of every three women and one out of every four men have experienced sexual violence during their lifetime. While prevention efforts have focused on implementing specific programmatic approaches, there has been relatively little focus on developing comprehensive and effective approaches to reduce sexual assault prevention across an organization. This study describes the development of the Prevention Evaluation Framework, an assessment targeting organizational best practices for comprehensive sexual assault prevention across multiple domains including human resources, collaborative relationships and infrastructure, use of evidence-informed approaches, quality implementation and continuous evaluation of programs/policies. Using the structured RAND/University of California, Los Angeles appropriateness method to develop the assessment, we conducted a literature review and solicited expert feedback about what a comprehensive organizational approach to sexual assault prevention should entail. We then pilot tested the assessment with 3 United States military service academies; and continued to improve and adapt the assessment to a range of organizations with input from 6 Department of Defense headquarters organizations, and 9 universities across the country. Given the nascent state of the evidence about what makes an effective organizational approach to sexual assault prevention, the assessment reflects one way of promoting quality in this evolving field. The consistency between the experts' ratings and the literature, and the relevance of the items across organizations suggest that the assessment provides important guidance to inform the development of comprehensive organizational approaches to sexual assault prevention and to the evaluation of ongoing efforts.

Implementation Science in Thailand: Design and Methods of a Geriatric Mental Health Cluster-Randomized Trial.

BACKGROUND: Thailand has a rapidly aging population yet lacks evidence for effective and scalable evidence-based psychosocial interventions to support persons living with dementia and their family caregivers. In this study of a culturally adapted and evidence-based clinical program (Reducing Disabilities in Alzheimer's Disease [RDAD]), designed to reduce behavioral and psychological symptoms of dementia in older adults, the authors test the hypothesis that an implementation support strategy, Getting To Outcomes (GTO), would produce better implementation and clinical outcomes compared with usual implementation of RDAD in Thailand. METHODS: The study uses a hybrid type III cluster-randomized design to compare eight geographical districts that receive training on both implementing the RDAD clinical intervention and on GTO implementation support strategies (intervention arm) with eight other districts that receive the same RDAD training but without training in GTO implementation support strategies (control arm). GTO is an evidence-based intervention designed to support implementers to better plan, implement, and evaluate innovative intervention programs in a novel setting. Primary outcomes, including implementation and clinical outcomes, will be assessed at baseline, month 3 (posttreatment), and month 6 (3-month follow-up). RESULTS: The research team anticipates that there will be significantly more improvements in the delivery of the RDAD intervention program in the experimental group than in the control group. NEXT STEPS: If clinical trial findings are positive, the authors plan to replicate and scale up the proposed implementation science approach across Thailand to enhance and expand mental health services for older adults with dementia.

A permutation test for assessing the presence of individual differences in treatment effects.

An important goal of personalized medicine is to identify heterogeneity in treatment effects and then use that heterogeneity to target the intervention to those most likely to benefit. Heterogeneity is assessed using the predicted individual treatment effects framework, and a permutation test is proposed to establish if significant heterogeneity is present given the covariates and predictive model or algorithm used for predicted individual treatment effects. We first show evidence for heterogeneity in the effects of treatment across an illustrative example data set. We then use simulations with two different predictive methods (linear regression model and Random Forests) to show that the permutation test has adequate type-I error control. Next, we use an example dataset as the basis for simulations to demonstrate the ability of the permutation test to find heterogeneity in treatment effects for a predicted individual treatment effects estimate as a function of both effect size and sample size. We find that the proposed test has good power for detecting heterogeneity in treatment effects when the heterogeneity was due primarily to a single predictor, or when it was spread across the predictors. Power was found to be greater for predictions from a linear model than from random forests. This non-parametric permutation test can be used to test for significant differences across individuals in predicted individual treatment effects obtained with a given set of covariates using any predictive method with no additional assumptions.

R = MC2 readiness building process: A practical approach to support implementation in local, state, and national settings.

Effective implementation of evidence-based interventions is a persistent challenge across community settings. Organizational readiness - or, the motivation and collective capacity of an entity to adopt and sustain an innovation - is important to facilitate implementation. Drawing on the R = MC2 readiness framework, we developed a readiness building process to tailor support for implementation. The process is composed of the following stages: assessment, feedback and prioritization, and strategize. In this article, we describe the application of the readiness building process through three case examples representing interventions at different ecological levels: local, state, and national. The case examples illuminate challenges and practical considerations for using the readiness building process, including the significance of on-going leadership engagement and collaboration between support system and delivery system staff. To further the research and practice of implementation readiness, we suggest examining the impact of readiness building on implementation outcomes and developing an empirically-informed repository of change management strategies matched to readiness constructs.

Development of a comprehensive measure of organizational readiness (motivation × capacity) for implementation: a study protocol.

BACKGROUND: Organizational readiness is important for the implementation of evidence-based interventions. Currently, there is a critical need for a comprehensive, valid, reliable, and pragmatic measure of organizational readiness that can be used throughout the implementation process. This study aims to develop a readiness measure that can be used to support implementation in two critical public health settings: federally qualified health centers (FQHCs) and schools. The measure is informed by the Interactive Systems Framework for Dissemination and Implementation and R = MC2 heuristic (readiness = motivation × innovation-specific capacity × general capacity). The study aims are to adapt and further develop the readiness measure in FQHCs implementing evidence-based interventions for colorectal cancer screening, to test the validity and reliability of the developed readiness measure in FQHCs, and to adapt and assess the usability and validity of the readiness measure in schools implementing a nutrition-based program. METHODS: For aim 1, we will conduct a series of qualitative interviews to adapt the readiness measure for use in FQHCs. We will then distribute the readiness measure to a developmental sample of 100 health center sites (up to 10 staff members per site). We will use a multilevel factor analysis approach to refine the readiness measure. For aim 2, we will distribute the measure to a different sample of 100 health center sites. We will use multilevel confirmatory factor analysis models to examine the structural validity. We will also conduct tests for scale reliability, test-retest reliability, and inter-rater reliability. For aim 3, we will use a qualitative approach to adapt the measure for use in schools and conduct reliability and validity tests similar to what is described in aim 2. DISCUSSION: This study will rigorously develop a readiness measure that will be applicable across two settings: FQHCs and schools. Information gained from the readiness measure can inform planning and implementation efforts by identifying priority areas. These priority areas can inform the selection and tailoring of support strategies that can be used throughout the implementation process to further improve implementation efforts and, in turn, program effectiveness.

The Effects of Sample Size on the Estimation of Regression Mixture Models.

Regression mixture models are a statistical approach used for estimating heterogeneity in effects. This study investigates the impact of sample size on regression mixture's ability to produce "stable" results. Monte Carlo simulations and analysis of resamples from an application data set were used to illustrate the types of problems that may occur with small samples in real data sets. The results suggest that (a) when class separation is low, very large sample sizes may be needed to obtain stable results; (b) it may often be necessary to consider a preponderance of evidence in latent class enumeration; (c) regression mixtures with ordinal outcomes result in even more instability; and (d) with small samples, it is possible to obtain spurious results without any clear indication of there being a problem.

Is ADHD, independent of ODD, associated with whether and why college students misuse stimulant medication?

Although previous research suggests that undergraduates with untreated or undertreated attention-deficit/hyperactivity disorder (ADHD) symptoms may have academic motives for stimulant medication misuse, no previous work has examined the relation of ADHD symptoms, controlling for comorbid oppositional defiant disorder (ODD), to misuse, or has explored how these symptoms are differentially related to motives for misuse. Among a sample of 900 students from one public university, the current study first tested whether increased ADHD symptomology (using the Current Symptoms Scale, CSS) was associated with an increased likelihood of misusing stimulant medication, controlling for comorbid ODD. We then examined whether those with increased ADHD symptomology were more likely to report academic motives for misuse. The prevalence rate of misuse in the past year was 22%. Participants who met symptom count criteria for ADHD (controlling for comorbid ODD) were 2.90 times more likely to misuse stimulant medication than those who did not. Among misusers, those who met ADHD criteria were also 2.80 times more likely to report academic motives for misuse. These results support that stimulant medication misuse is likely driven, in part, by inadequate or absent care for the executive functioning impairments associated with ADHD. Therefore, a greater focus on assessment and treatment of college students with ADHD symptoms is warranted. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Utilising the 'Getting to Outcomes®' Framework in Community Engagement for Development and Implementation of Sickle Cell Disease Newborn Screening in Kaduna State, Nigeria.

BACKGROUND: Sickle Cell Disease (SCD) has been designated by WHO as a public health problem in sub-Saharan Africa, and the development of newborn screening (NBS) is crucial to the reduction of high SCD morbidity and mortality. Strategies from the field of implementation science can be useful for supporting the translation of NBS evidence from high income countries to the unique cultural context of sub-Saharan Africa. One such strategy is community engagement at all levels of the healthcare system, and a widely-used implementation science framework, "Getting to Outcomes®" (GTO), which incorporates continuous multilevel evaluation by stakeholders about the quality of the implementation. OBJECTIVES: (1) to obtain critical information on potential barriers to NBS in the disparate ethnic groups and settings (rural and urban) in the healthcare system of Kaduna State in Nigeria; and, (2) to assist in the readiness assessment of Kaduna in the implementation of a sustainable NBS programme for SCD. METHODS: Needs assessment was conducted with stakeholder focus groups for two days in Kaduna state, Nigeria, in November 2017. RESULTS: The two-day focus group workshop had a total of 52 participants. Asking and answering the 10 GTO accountability questions provided a structured format to understand strengths and weaknesses in implementation. For example, we found a major communication gap between policy-makers and user groups. CONCLUSION: In a two-day community engagement workshop, stakeholders worked successfully together to address SCD issues, to engage with each other, to share knowledge, and to prepare to build NBS for SCD in the existing healthcare system.

Identification of predicted individual treatment effects in randomized clinical trials.

In most medical research, treatment effectiveness is assessed using the average treatment effect or some version of subgroup analysis. The practice of individualized or precision medicine, however, requires new approaches that predict how an individual will respond to treatment, rather than relying on aggregate measures of effect. In this study, we present a conceptual framework for estimating individual treatment effects, referred to as predicted individual treatment effects. We first apply the predicted individual treatment effect approach to a randomized controlled trial designed to improve behavioral and physical symptoms. Despite trivial average effects of the intervention, we show substantial heterogeneity in predicted individual treatment response using the predicted individual treatment effect approach. The predicted individual treatment effects can be used to predict individuals for whom the intervention may be most effective (or harmful). Next, we conduct a Monte Carlo simulation study to evaluate the accuracy of predicted individual treatment effects. We compare the performance of two methods used to obtain predictions: multiple imputation and non-parametric random decision trees. Results showed that, on average, both predictive methods produced accurate estimates at the individual level; however, the random decision trees tended to underestimate the predicted individual treatment effect for people at the extreme and showed more variability in predictions across repetitions compared to the imputation approach. Limitations and future directions are discussed.

The Quality of Life of Children Under Chiropractic Care Using PROMIS-25: Results from a Practice-Based Research Network.

OBJECTIVES: To characterize pediatric chiropractic and assess pediatric quality of life (QoL). DESIGN: A prospective cohort. Setting/Locations: Individual offices within a practice-based research network located throughout the United States. SUBJECTS: A convenience sample of children (8-17 years) under chiropractic care and their parents. EXPOSURE: Chiropractic spinal adjustments and adjunctive therapies. OUTCOME MEASURES: Survey instrument measuring sociodemographic information and correlates from the clinical encounter along with the Patient Reported Outcomes Measurement Information System (PROMIS)-25 to measure QoL (i.e., depression, anxiety, and pain interference). Sociodemographic and clinical correlates were analyzed using descriptive statistics (i.e., frequencies/percentages, means, and standard deviations). The PROMIS-25 data were analyzed using scoring manuals, converting raw scores to T score metric (mean = 50; SD = 10). A generalized linear mixed model was utilized to examine covariates (i.e., sex, number of visits, and motivation for care) that may have played an important role on the PROMIS outcome. RESULTS: The original data set consisted of 915 parent-child dyads. After data cleaning, a total of 881 parents (747 females, 134 males; mean age = 42.03 years) and 881 children (467 females and 414 males; mean age = 12.49 years) comprised this study population. The parents were highly educated and presented their child for mainly wellness care. The mean number of days and patient visits from baseline to comparative QoL measures was 38.12 days and 2.74 (SD = 2.61), respectively. After controlling for the effects of motivation for care, patient visits, duration of complaint, sex, and pain rating, significant differences were observed in the probability of experiencing problems (vs. no reported problems) across all QoL domains (Wald = 82.897, df = 4, p < 0.05). Post hoc comparisons demonstrated the children were less likely to report any symptoms of depression (Wald = 6.1474, df = 1, p < 0.05), anxiety (Wald = 20.603, df = 1, p < 0.05), fatigue (Wald = 22.191, df = 1, p < 0.05), and pain interference (Wald = 47.422, df = 1, p < 0.05) after a trial of chiropractic care. CONCLUSIONS: The QoL of children improved with chiropractic care as measured by PROMIS.

Forming first impressions of children: the role of attention-deficit/hyperactivity disorder symptoms and emotion dysregulation.

BACKGROUND: Previous research on peer status of children with attention-deficit/hyperactivity disorder (ADHD) has focused on already-established peer groups, rendering the specific social behaviors that influence peers' initial impressions largely unknown. Recently, theorists have argued that emotion dysregulation is a key aspect of ADHD, with empirical work finding relations between emotion dysregulation and social outcomes. Therefore, the current study focuses on the initial interactions among children varying in ADHD symptoms duringh a novel playgroup, proposing that emotion dysregulation displayed during the playgroup may serve as a possible pathway between ADHD symptoms and peers' initial negative impressions. METHODS: Participants were 233 elementary-age children ranging from 8 to 10 years old (M = 8.83, 70% male). Parents and teachers rated children's ADHD symptoms and related impairment; 51% of the children met criteria for an ADHD diagnosis. Then, children participated with unfamiliar peers in a three-hour playgroup that included three structured and two unstructured tasks. After the tasks, children and staff rated each child on social outcomes. Coders unaware of child's diagnostic status watched videos of the groups and rated each child's global emotion dysregulation during each task. RESULTS: Using multiple raters and methods, ADHD severity was associated with more negative peer ratings, through observed emotion dysregulation. Results were consistent for both parent and teacher ratings of ADHD severity as well as for both peer ratings of likeability and staff ratings of perceived peer likeability. CONCLUSIONS: When focusing on improving peers' initial impressions of children with ADHD symptoms, emotion dysregulation may be a valuable target for intervention.

Using Multilevel Regression Mixture Models to Identify Level-1 Heterogeneity in Level-2 Effects.

This paper proposes a novel exploratory approach for assessing how the effects of level-2 predictors differ across level-1 units. Multilevel regression mixture models are used to identify latent classes at level-1 that differ in the effect of one or more level-2 predictors. Monte Carlo simulations are used to demonstrate the approach with different sample sizes and to demonstrate the consequences of constraining 1 of the random effects to zero. An application of the method to evaluate heterogeneity in the effects of classroom practices on students is used to show the types of research questions which can be answered with this method and the issues faced when estimating multilevel regression mixtures.

Regression Mixture Models: Does Modeling the Covariance Between Independent Variables and Latent Classes Improve the Results?

Regression mixture models are increasingly used as an exploratory approach to identify heterogeneity in the effects of a predictor on an outcome. In this simulation study, we tested the effects of violating an implicit assumption often made in these models; that is, independent variables in the model are not directly related to latent classes. Results indicate that the major risk of failing to model the relationship between predictor and latent class was an increase in the probability of selecting additional latent classes and biased class proportions. In addition, we tested whether regression mixture models can detect a piecewise relationship between a predictor and outcome. Results suggest that these models are able to detect piecewise relations but only when the relationship between the latent class and the predictor is included in model estimation. We illustrate the implications of making this assumption through a reanalysis of applied data examining heterogeneity in the effects of family resources on academic achievement. We compare previous results (which assumed no relation between independent variables and latent class) to the model where this assumption is lifted. Implications and analytic suggestions for conducting regression mixture based on these findings are noted.

Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study.

Regression mixture models are a novel approach to modeling the heterogeneous effects of predictors on an outcome. In the model-building process, often residual variances are disregarded and simplifying assumptions are made without thorough examination of the consequences. In this simulation study, we investigated the impact of an equality constraint on the residual variances across latent classes. We examined the consequences of constraining the residual variances on class enumeration (finding the true number of latent classes) and on the parameter estimates, under a number of different simulation conditions meant to reflect the types of heterogeneity likely to exist in applied analyses. The results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted on the estimated class sizes and showed the potential to greatly affect the parameter estimates in each class. These results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions are made.

A practical implementation science heuristic for organizational readiness: R = MC2.

There are many challenges when an innovation (i.e., a program, process, or policy that is new to an organization) is actively introduced into an organization. One critical component for successful implementation is the organization's readiness for the innovation. In this article, we propose a practical implementation science heuristic, abbreviated as R= MC2 . We propose that organizational readiness involves: 1) the motivation to implement an innovation, 2) the general capacities of an organization, and 3) the innovation-specific capacities needed for a particular innovation. Each of these components can be assessed independently and be used formatively. The heuristic can be used by organizations to assess readiness to implement and by training and technical assistance providers to help build organizational readiness. We present an illustration of the heuristic by showing how behavioral health organizations differ in readiness to implement a peer specialist initiative. Implications for research and practice of organizational readiness are discussed.