This special issue of Intellectual and Developmental Disabilities (IDD) provides summary reviews of and expert commentaries on what is known, what points of debate exist, and what remains unknown about important outcome areas related to community living and participation for people with intellectual and developmental disabilities (IDD) in the United States. The areas of focus (e.g., social inclusion, families, employment, health and wellness, and self-determination and choice) were identified as critical to the enhancement and promotion of community living and participation of persons with IDD by service systems, organizations, and practitioners. Articles also focused on important methodological considerations of research in these areas, such as issues concerning self-report data, population data sets, and measurement of quality of life. System and individual predictors of outcomes were addressed along with how policy makers should use such information in formulating policy and services. Together, the articles demonstrate the complexity of the issues and their related research, policy, and practice implications.
Across these articles, there are several overarching themes that emerge related to research, policy, and practice in community living and participation. This commentary is intended to provide some concluding thoughts on these emerging themes.
In the best case, applied research produces evidence that is directly actionable for policy makers and practitioners. Likewise, there is increasing pressure for states to develop evidence-based policy. Moseley, Kleinert, Sheppard-Jones, and Hall (2013, this issue) describe how a strong, ongoing partnership between researchers and IDD policy makers in Kentucky led to state policy decisions being guided by research data on service-user outcomes. As researchers, we need to partner with policy makers (among others) in setting research agendas if we aim to provide policy or practice-relevant research.
Policy-relevant research should have the highest degree of methodological rigor that is practical. However, as is indicated in the papers in this special issue, much IDD research on community living and participation uses nonrepresentative samples. Efforts in future research should strive to make samples more representative, particularly in terms of race, ethnicity, class, and age of participants (Amado, Stancliffe, McCarron, & McCallion, 2013, this issue; Hewitt, Agosta, Heller, Williams, & Reinke, 2013, this issue; Wehmeyer & Abery, 2013, this issue). There is the additional need in many topical areas of research for better representation of people with more severe and complex disabilities as many samples tend to focus on the experiences of people with higher levels of cognitive and physical functioning. Efforts to include more people with significant functional needs are complicated by the challenges of obtaining valid self-reported data from all participants (Emerson, Felce, & Stancliffe, 2013, this issue).
Additionally, most research in the IDD field only includes sample members who receive formal services (e.g., residential or employment). Studies also need to include people with IDD who do not receive formal supports (Hewitt et al., 2013, this issue; Ticha, Hewitt, Nord, & Larson, 2013, this issue). When coupled with the difficulties in service access experienced by many people with IDD, this represents a major gap in our ability to understand the needs, experiences, and outcomes of people with IDD. Secondary analysis of population-based surveys by IDD researchers may represent one important way to include in research people with IDD who are not using IDD services. However, as noted by Emerson et al. (2013, this issue), there remain significant challenges in identifying participants with IDD in such surveys together with problems of underrepresentation of these individuals because of sampling methodology or perceived difficulties with consent and responding.
Comparisons to the General Population
Data sets that allow for direct comparisons of people with IDD to the general population are useful in drawing conclusions about where disparities exist. To this end, using similar definitions from large general-population surveys (e.g., American Community Survey, Census) in IDD surveys would make comparison to the general population easier. Likewise, including clearer disability descriptors in these population-based surveys would make it easier to identify participants with IDD and thus enable valid comparisons with the general population.
Disparities in many domains of life (health, education, and work outcomes; quality of life; community participation) continue to exist for people with IDD. While there have been improvements in recent years, practitioners and policy makers must remember that people with IDD are marginalized as indicated in the areas of health and wellness (Anderson, Humphries, McDermott, Marks, & Larson, 2013, this issue), employment (Nord, Luecking, Mank, Kiernan, & Wray, 2013, this issue), and social inclusion (Amado et al., 2013, this issue). Policies and practices designed to reduce such disparities are essential. Balancing the need for individualization of service delivery with the need for large-scale interventions to reduce disparities will remain a challenge for policy makers.
Differences Between U.S. States
As noted by Ticha et al. (2013, this issue), there are marked between-state differences in U.S. expenditures on and provision of IDD services. Related is the need for cross-system comparisons (e.g., between U.S. state IDD systems) of service-user outcomes. Such comparisons could involve widely used outcome-assessment instruments, such as the National Core Indicators (NCI) in the United States and other national surveys in other countries. Harnessing such instruments could provide direct feedback on which state policies and service configurations have positive or negative effects on which outcomes for people with IDD. Unfortunately, varying conceptualizations of key variables such as “family support” or “living arrangement” and “quality of life” as pointed out in the articles by Hewitt et al. (2013, this issue); Ticha et al. (2013, this issue); and Brown, Hatton, and Emerson (2013, this issue) make such research challenging. Forging agreement on key variable definitions could result in more valid comparisons of outcomes between state IDD systems.
A number of longitudinal IDD data sets have been used to inform policy and practice in the United States for several decades, notably the Projects of National Significance (PNS) discussed by Ticha et al. (2013, this issue). These separate data sets provide information on specific issues about state IDD systems, such as residential services, employment, and IDD service expenditures. Research that integrates NCI outcomes data with data elements from other PNS data sets may also be useful for policy-relevant analyses. State-level data from the PNS projects (e.g., use of ICF/DD services, percentage of services delivered in family home, per capita spending on services, percentage of people in supported employment programs) could be used as independent variables in research that examines NCI outcomes data (e.g., social inclusion, choice, employment outcomes, health outcomes) across states.
Ticha et al. (2013, this issue) described the growth in the number of people with IDD receiving publicly funded services while living in the home of a family member. The authors of several other articles discussed the need to begin to conduct intervention or applied research with individuals with IDD who live in family homes or in their own home. Conducting research in single units (vs. congregate-care units) presents challenges for researchers in recruiting sufficient sample sizes, access to participants, and efficient use of research dollars. These challenges come at a time when funding is shrinking due to budget cuts in agencies that fund IDD research.
Many articles in this special issue discuss the importance of context (e.g., geographic location, community, relationships, culture, race, ethnicity) in supporting outcomes, such as health, self-determination, social inclusion, and employment. Honoring context and individualization of supports and services within these contexts, through policy and service, can be a challenge for large systems.
Several papers in this special issue give examples of interventions and initiatives that have been successful on a small scale but have not been implemented more widely (e.g., Amado et al., 2013, this issue; Anderson et al., 2013, this issue; Hewitt et al., 2013, this issue; Moseley et al., 2013, this issue; Nord et al., 2013, this issue; and Wehmeyer & Abery, 2013, this issue). Today, researchers are often required to identify their plans for ensuring sustainability of such demonstration efforts, but it is increasingly clear that there is a need to go beyond demonstration by scaling up successful interventions and by researching effective ways to achieve this scale up. It is noteworthy that the U.S. National Institute on Disability and Rehabilitation Research (NIDRR) has adopted a stages-of-research framework for its disability research funding. The NIDRR 2013 framework includes a Scale-up Evaluation stage that “examines the challenges to successful replications and the circumstances and activities that contribute to successful wide-scale adoption of interventions” (p. 20, 304). This stage focuses on evaluating the effectiveness of widespread implementation of evidence-based practices and on identifying effective ways to achieve broad-scale implementation.
The Kentucky approach described by Moseley et al. (2013, this issue) provides an illustrative but all too rare example of careful use of representative outcome data to guide and evaluate statewide policy and practice. It remains to be seen if improved outcomes in the targeted areas will follow the changes in Kentucky's IDD services and funding. A key implication for researchers arising from this approach is that several conditions may be needed for scale-up to be attempted. These include (a) representative research data identifying a widespread problem requiring intervention; (b) availability of a relevant, well-developed, and potentially scalable intervention with clear, existing research evidence of efficacy; and (c) ongoing collection of data on relevant outcomes to evaluate the effectiveness of the scaled-up intervention. In Kentucky, the NCI program is providing ongoing data about outcomes regarding points (a) and (c). In the case of Kentucky's initiative on health and wellness, among other interventions, the Health Matters Curriculum (Marks, Sisirak, & Heller, 2010) has been chosen for broad implementation. This curriculum has been developed and tested over many years by researchers at the University of Illinois at Chicago (Anderson et. al., 2013, this issue). The curriculum has published manuals, and there is a developed capacity to provide train-the-trainer workshops across Kentucky to enable statewide scaling up.
Taking successful interventions to a broader implementation level will require investments and state leadership to promote and evaluate the effectiveness of such efforts on a large scale (Moseley et al., 2013, this issue). Too often, such interventions are left up to individual providers and families to embrace and implement as a component of their individual contracts with states. Take-up by organizations and families and scale-up to the state and national levels are significant challenges and are likely not going to be embraced unless there are substantial policy incentives and leadership to promote use and success. Moreover, the success of such scale-up efforts in terms of (a) delivery of the intervention with adequate procedural integrity and (b) improved outcomes for people with IDD must be demonstrated through research and evaluation and not simply assumed.
Additionally, several papers mentioned the need for cost/benefit analysis of various interventions to show policy makers that programs are cost-effective as well as effective in increasing personal outcomes. Cost/benefit methodologies should be considered with greater frequency when evaluating policy and by researchers in intervention studies.
Policy to develop and stabilize the direct-support workforce (including family caregiver support and paid supports) as discussed in the Hewitt et al. (2013, this issue), Anderson et al. (2013, this issue), and Wehmeyer and Abery (2013, this issue) articles is necessary if improvements in personal outcomes for people with IDD are to occur. Training, information exchanges, salary, and benefits for direct-support workers may be considered as long-term investments in service infrastructure in order to stabilize and strengthen the support system for people with IDD. Policy that supports this development for family supporters and paid direct-support workers should be considered vital to the service system (e.g., Amado et al., 2013, this issue; Anderson et al., 2013, this issue; and Nord et al., 2013, this issue).
Many articles identified access to services as a continued problem for people with IDD and their families whether services are related to health care, community inclusion, or employment support. Successful interventions have limited utility if large numbers of people with IDD are not able to access these interventions. This is also a policy issue as some of the access difficulty in the United States resides in reliance on Medicaid as a primary vehicle for the delivery of services and supports and as such necessitates procedures that make service for people with IDD an unprofitable endeavor for many practitioners.
In this issue of IDD, the information in the articles suggests that we have some strategies, tools, and knowledge with which there is evidence of efficacy, that is, evidence that the intervention is feasible and can result in better outcomes, such as successful participation of people with IDD in their communities. However, where available, this evidence is often drawn from small-scale demonstration projects and the like. We have very little evidence of the effectiveness of such interventions when scaled up. There is a need to better understand how to successfully scale up interventions that show promise in improving various aspects of community living and participation for people with IDD.
One of the greatest challenges to connecting the research, policy, and practice is a pervasive lack of effective dissemination and promotion efforts related to research. Researchers are very good at disseminating their findings to other researchers, but the translation of research needs to account for target audiences other than academics. Researchers should be mindful of ways to publish translational research for advocates, policy makers, and service providers in formats that are directly applicable to their needs. Findings should be made accessible both in form and function and ideally should arise from programs of research in which these stakeholders have been involved directly in setting research priorities.
The interconnectedness between research, policy, practice, and the ultimate outcome of improved community living and participation for people with IDD is complex. Challenges in methods; samples; access to comparison data sets; and putting research findings in the hands of policy makers, policy advocates, and practitioners are difficult for researchers. Understanding research findings and their implications for services, taking findings, and creating systems and services that allow for scale up are challenging for policy makers and policy advocates. Finding, understanding, and using research to inform practice, train direct-support professionals, and improve services is a challenge for practitioners. There is not a natural place and time where these worlds all intersect. As a community of interested stakeholders who want people with IDD to have access to services and supports that improve their participation in community life, we need to embrace the complexities in front of us with an ongoing commitment to make the interconnectedness of these issues related to research, policy, and practice more obvious.
The Special Issue Editors
Amy Hewitt, Roger J. Stancliffe, Eric Emerson