We need innovation to address our chronic disease burden, and design thinking has emerged as a promising tool. But as someone who has a background in community health promotion, I can’t help but wonder: how is design thinking, when applied in community settings to promote community and population health, different from or similar to community engaged research?
This question becomes more pertinent with growing interest in academic-industrial partnerships to advance the impact of our evidence-based interventions, particularly in behavioral health (Hingle et, al 2018). While these sorts of partnerships may have had a longer history in engineering, biomedical science, and technology, with the changing health care, prevention and technology fields, behavioral science finds itself in a growing marketplace with opportunity to advance implementation of our work. By leveraging partnerships with industry and with technology experts in academia, behavioral scientists may find themselves in a pivotal position to advance population health goals. (Stey, et al, JAMA, 2018)
As academic and industry partnerships come together, they will ultimately need to answer the question for what is the return on investment (ROI)? How can get individuals, communities, systems to actually use the work we have created and impact behavior change and health? From an Implementation Science perspective, how can we enhance reach of our interventions, and better understand the processes for enhancing our implementation outcomes of interest, adaptation, sustainability, etc.
As industry and academic partnerships advance, there are two parallel and overlapping approaches to designing and developing interventions which offer important perspectives. These two approaches are Human Centered Design (HCD) from engineering, design, and technology industries and Community based Participatory Health Research (CBPR) from public health. Both of these approaches, while from different fields, offer a place of common ground and orientation and create opportunities for advancing implementation of behavioral interventions.
Here are a few definitions:
Human-centered design (HCD) is a design and management framework that develops solutions to problems by involving the human perspective in all steps of the problem-solving process. Human involvement typically takes place in observing the problem within context, brainstorming, conceptualizing, developing, and implementing the solution.
Community based participatory research (CBPR) is a partnership approach to research that equitably involves, for example, community members, organizational representatives, and researchers in all aspects of the research process and in which all partners contribute expertise and share decision making and ownership. The aim of CBPR is to increase knowledge and understanding of a given phenomenon and integrate the knowledge gained with interventions and policy and social change to improve the health and quality of life of community members.
To kick this off, I sought to compare the two approaches around some high-level concepts that are relevant for implementation science. There are many concepts I am leaving out of this table, and certainly if you dig into the methodologies, many more parallels and differences can be found.
| Human Centered Design* | Community-based Participatory Research | |
|---|---|---|
| Philosophy | Focuses on the people for which the intervention is intended and the people and system whom the intervention will touch. Goal is to solve the basic problem… not the symptom. | The orientation is towards social justice, social determinants of health and advancement of equity and empowerment of community as part of the research team. |
| Context | Essential to design of the intervention. Recognizes the role of context as the system in which the intervention will have to interact and operate. | Essential to the identification of need for the intervention, as identified by community stakeholders. Context informs and acknowledges the culture, history, orientation and power of the community. |
| Patient, Community, Stakeholder Engagement | The user experience are key data points and can drive the research, but may stop short of engaging the community as collaborative decision makers in the process of development | Community members are viewed as collaborators (co-designers, co-producers) from start to finish of the research project, with recognition that they are experts given culture, history and lived experiences. Research may include engagement to identify or document a phenomenon or need through data and shared interpretation. |
| Data Collection | Emphasis on iterative data collection using mixed methods approaches throughout multiple phases of the process | Methods can be mixed methods and often informed and approved by a community advisory board or community representatives. |
| Formulation of hypotheses and research questions | While ‘client’ driven, a design team works to have clients participate in the development of hypotheses as well as inform and rapidly iterate on hypotheses and prototypes | Community driven with partnership with researchers. Any changes made have to be approved by the community stakeholders. |
| Iterative process during intervention development | Iterative process is employed for creation of a product and testing (particularly in a lean start up design) | All partners must determine there is an issue and what the action or intervention will be. The iterative process may not happen with community partners unless explicitly part of the study design. However, it could happen with co-creation before the intervention is created. The distinguishing characteristic is likely that it may not be as nimble in human centered design approaches. |
| Implementation of intervention | Each phase is meant to be iterative and cyclical, and as a consequence an intervention can be implemented multiple times. Repetition and iteration are seen as essential with feedback loops of data informing the next cycle of development and to inform whether the intervention was successful. HCD practitioners often view program adoption as a key area to understand fully before even starting the research or developing the intervention. | Implementation of the intervention may not be the explicit aim of the research, unless the researcher and community identify it and mutually agree on this data collection and emphasis. The intervention developed would also belong to the community. |
* I focus on human centered design (versus user-centered design) because of its empathic approach to the human experience, which may be more consistent with inherent values for health care applications.
This table is a high-level comparison, and certainly you can see many areas of overlap and nuanced similarities and differences. The two approaches are complimentary, and CBPR and HCD research and practitioners can work together to learn from each other, exchange methodologies, and ultimately, enhance our abilities to co-design and implement investments in evidence-based interventions. Some have argued that implementation models have not been participatory and do not promote innovation. Allowing for inclusion of human factors in the design could allow for better adoption, acceptability and compliance by allowing for faster iterations (failing early and often) to break social norms, move beyond the status quo and work “in the real world.” Community engagement is important for stakeholder buy in and the research process to reflect the voice, history and start to balance the power dynamic between researchers and communities, in particular when addressing health disparities.
The bottom line is that design thinking for interventions may be something that our public health CBPR practitioners have been doing, but there are nuanced differences and the two can inform each other. One way of doing so may be that community members become part of a design team, or in a research project, a design approach can be taken in co-development of the intervention prior to testing and delivery. A HCD approach may borrow from CBPR and consider including community representatives as part of the design team to develop an implementation process that recognizes the system in which it will be embedded, to rapidly experiment, iterate and innovate on solutions.
Is HCD like CBPR? I think HCD and CBRP are probably in the same family of approaches. They stress participant's involvement and producing solutions to problems (although, for CBPR, sometimes it means, just documenting or studying a problem), stress context, engagement of the end user on data collection methods and hypotheses. Where the difference lies is in the rapid cycle iterative emphasis in HCD, the “fail fast” approach, typical in innovation spaces, but may be harder to accomplish in a traditional CBPR methodology. HCD is typically applied in integrating or developing a new technology or other tools to address health or other social problems, and as a consequence, perhaps due to the nature of rapid cycle prototyping in technology fields, it has received greater acceptance from the field for this approach. But as academic and industry partnership grows, we may be seeing merging of CBPR and HCD design approaches as engagement of consumers becomes a core value in health care, while rapid cycle testing for development will be required to meet the needs and demands of the marketplace.
If you are interested in learning more about how to integrate these two approaches in your work there are a few opportunities at NCI. The NCI SPRINT program (Speeding Research Tested Interventions into Practice), encourages participants to take a lean start up approach to thinking about implementing their research interventions into practice. The lean start up approach is within the suite of approaches in design thinking. If you are interested in learning more, and you have an evidence based intervention, please consider applying to this competitive program. If you are a mid-career scientist and interested in advancing mhealth work and thinking about HCD and CBPR consider the Short-term Mentored Career Enhancement Awards in Mobile and Wireless Health Technology and Data Analytics: Cross-Training at the intersection of Behavioral and Social Sciences and STEM Disciplines (PAR-18-882: K18 Independent Clinical Trial Required OR PAR-18-881: K18 Independent Clinical Trial Not Allowed).
Do you agree? What would you add to this discourse? How can this be applied to your work as you think about Implementation of your research into practice?
Share your comments or tweet me @aprilyoh 
References:
Stey A, Kanzaria H, Brook R. How disruptive innovation by business and technology firms could improve population health. JAMA. 2018;320(10):973-974.Published online August 16, 2018. doi:10.1001/jama.2018.10782 .
Hingle M, Patrick H, Sacher PM. The intersection of behavioral science and digital health: the case for academic–industry partnerships. Health Educ Behav. 2018;46(1):5-9. doi:10.1177/1090198118788600 .
Matheson GO, Pacione C, Shultz RK, Klügl M. Leveraging human-centered design in chronic disease prevention. Am J Prev Med. 2015;48(4):472-479. doi:10.1016/j.amepre.2014.10.014 .
April Oh, Ph.D., M.P.H., is a former Senior Advisor for Implementation Science and Health Equity in the Implementation Science (IS) Team in the Office of the Director in the Division of Cancer Control and Population Sciences (DCCPS) at the National Cancer Institute (NCI).
Dispatches from the Implementation Science Team, is an episodic collection of short form updates, authored by members and friends of the IS team representing a sample of the work being done and topics that our staff are considering for future projects. Topics address some of the advances in implementation science, ongoing issues that affect the conduct of research studies, reflections on fellowships and meetings, as well as new directions for activity from our research and practice communities.