Enhancing Health Research Results Dissemination for American Indian and Alaska Native Communities through Indigenous Community-Centered Design

Abstract

American Indian and Alaska Native (AI/AN) communities not only face significant health disparities but are often underrepresented in health research dissemination. Existing communication tools may fail to effectively reach these communities in culturally relevant and accessible ways, limiting their ability to benefit from critical health research. We co-designed and evaluated a prototype for health research results dissemination for AI/AN communities. We created and evaluated the prototype drawing from previous co-design workshops with AI/AN people. 38 participants completed an evaluation providing feedback for further iteration and highlighting key features such as search functionality, ease of use, visual and interactive elements, and content accessibility. Participants emphasized the importance of community connection, educational resources, and personalized experiences. We feature an alternative design approach we call Indigenous Community-Centered Design to create more accessible and engaging health research communication tools for AI/AN communities, fostering stronger connections and more accurate research representation.

Introduction

Developing effective health research dissemination tools for American Indian and Alaska Native (AI/AN) communities is fundamental for enhancing community health and well-being. AI/AN communities often face significant health disparities compared to the general United States population, including higher rates of chronic diseases, mental health issues, and substance abuse disorders¹. Effective health research dissemination can help bridge these gaps by ensuring that significant health information reaches these communities in culturally and contextually appropriate and accessible manners. A key challenge is the historical context of mistrust towards research institutions. This mistrust stems from past unethical research practices and limitations on culturally and contextually sensitive approaches for research within AI/AN communities². Consequently, developing dissemination tools that are collaborative and culturally tailored is essential to build trust and ensure the relevance and uptake of health information. Community collaborative research efforts, such as those involving participatory research models, have shown promise in improving the quality and relevance of health research for AI/AN communities³. These models emphasize the importance of involving community members at all stages of the research process, from design to dissemination, thereby ensuring that the research better addresses the specific needs and contexts of the communities^4,5. Furthermore, effective dissemination tools can support AI/AN communities by providing them with knowledge and resources to make informed health decisions. This empowerment is needed to promote health equity and improve overall community well-being.

In a previous study, we found that community norms around context, partnership, transparency, and dialogue were valuable considerations for developing interactive research dissemination systems for collaboration with AI/AN communities⁶. Awareness of context includes researchers’ understanding of local culture, including how to approach participants and show respect in culturally appropriate ways. This understanding may be achieved through partnerships focusing on power dynamics and regularly spending time with different stakeholder groups, many of whom may not be the design’s intended end-user. Transparency is tied directly to clear communication which promotes more active dialogue providing a variety of ways to communicate that would not otherwise be possible (i.e., mixed multi-media)⁶. Based on this knowledge, we created and used a new approach, Indigenous Community-Centered Design. We piloted this approach through community participatory design workshops with AI/AN community members to co-design a prototype for health research dissemination.

In this paper, we describe this new approach and the evaluation of our health research dissemination prototype that uses this unique design approach.

Background

Indigenous Community-Centered Design Approach

AI/AN people have been conducting research long before Western empirical research methods were established. For example, before colonization and Russian acculturation, Unangax (Aleut) people in Alaska’s Aleutian Islands had an elaborate calendar system that factored in the natural environment and when the natural environment and animals were at certain points such as, when birds are laying eggs or when seals are skinny from the winter. These systems identified the best times to go hunting and gathering for food⁷. It took exceptional observation and documentation aptitude to develop these systems of knowing. These methods considered the world around them and the connection between the social, physical, and spiritual worlds.

Yet, research is not always beneficial to AI/AN communities and these communities have experienced a history of unethical health research conduct. This disreputable research has imposed stereotypes on Indigenous people and has historically benefitted individual researchers or specific research institutions instead of helping the communities where the research was conducted⁸. These discrepancies have led to an increase in standards for AI/AN community collaboration and Tribal research sovereignty and solidarity in AI/AN health research. Yet, limitations still indicate the need for new methods to attain more contextually focused strategies. We integrated a response to this unethical history into our study design and have developed a new approach that we term Indigenous Community-Centered Design. Our approach incorporates community-engaged research and an Indigenous research methodology of relationality, with empirical user-centered design methods including participatory design, value-sensitive design, and speculative design.

Incorporating Relationality & Community Respect from Indigenous Research Methodologies

Indigenous research methodologies prioritize the relationships and interconnectedness between people and their physical, social, and spiritual environments⁸. This approach contrasts with positivist social science research methods which aim to predict and control behavior⁹. By incorporating relationality into our design process, we are acknowledging that relationships, social or otherwise, shape how we engage with AI/AN research participants and how we understand the data they share with us. In community-engaged research, AI/AN community members are often engaged throughout the research process including conceptualizing research topics, developing research questions, collecting, analyzing, and interpreting data, and disseminating study results^{2, 10-12}. As part of honoring relationality and community-engaged standards, we have followed established guidelines for conducting research with AI/AN communities by including essential AI/AN representation on our research team. Two of the authors (Dirks (Unangax) and BearBow (Southern Cheyenne)) are AI/AN researchers. As an outcome of AI/AN communities’ rights for Tribal research sovereignty, community engagement in research is now overwhelmingly standard for conducting research with and for AI/AN communities ^{11, 13, 14}. Moreover, multi-directional communication with communities is important to foster trust and to help ensure information shared and collected remains pertinent and meaningful to impacted communities^{2, 15-17}. For AI/AN communities, the information must be pertinent to the local context, encompassing local values, knowledge, and expertise^18-20.

We also follow standards of respecting Tribal sovereignty towards research14 and have received the proper Tribal health research review and approval to conduct this study with AI/AN communities. Additionally, we take an asset-based approach to our research, wherein we recognize historical trauma and injustices while, at the same time, community wellbeing, Indigenous knowledge and culture, and community resiliency as protective factors for community wellness14. One way we have enacted this approach was to conduct our prototype user evaluations during the University of Washington (UW) First Nations Annual powwow, a cultural event that honors Tribal community members who participate in this cultural activity. Our research highlights community knowledge and strengths, viewing them as paramount to developing more useful and appropriate health research dissemination tools for AI/AN communities.

Adapting Participatory Design Methods

User-centered design approaches, such as participatory design are potentially beneficial when exploring AI/AN community research dissemination values. Participatory design seeks to democratize information technology use and innovation ^{21, 22}. Core tenets include giving stakeholders meaningful influence in design and providing mutual learning opportunities between researchers and stakeholders ²³. Ideally, effective design gives stakeholders the ability to share their critical feedback on design solutions, create insight into ideas and prototypes, and understand design phases and concepts²⁴.

Forming mutual trust is essential for maintaining participatory relationships. Without it, participants may not feel comfortable fully disclosing information for fear of retribution²⁵. Trust building can occur through iterative reflection on community interpretations of technology, which may help uncover local frameworks to reference technology interaction that may be more sensible to community members than academic frameworks²⁶. As part of our process, we were very open to community insight which led to making adaptations to our design activities to better meet needs and support trust building while providing an opportunity for participants to practice design activities before even moving forward with our intended design. Moreover, community participants should be able to openly express opinions about existing and proposed designs²⁴ as they may be less likely to share opinions if they distrust or misunderstand the design process or feel like they will be in trouble if they openly share. Pre-design activities intended to introduce design frameworks and stages can help develop an understanding of the participatory design process which may encourage trust^{27, 28}. As part of our design process, we developed procedures to introduce the design process to participants prior to focusing on our intended design. This helped develop a sense of comfort with the design process and gave participants an opportunity to suggest changes to the process so that they were more open to sharing their insights.

Research that honors Indigenous knowledge while acknowledging researchers’ learned biases towards what constitutes valid data is imperative for the conduct of ethical research and design with Indigenous communities. Our research encourages collaboration during the research activities which, ideally, promotes respect and validity for all knowledge systems (e.g., Western and Indigenous). As each community has its unique characteristics, eliciting feedback from AI/AN communities to provide direct response on how and in what ways they want to receive research results is imperative to make decisions on how technology should be used to disseminate research results to their communities.

Prototype Development

We followed this Indigenous community-centered design approach to develop our prototype for disseminating health research results. The purpose of our co-design workshops was to design a tool that health researchers can use to share community-facing results of research conducted in AI/AN communities. Our prototype was grounded in data collected with AI/AN people in Anchorage, Alaska. Anchorage is an urban center, and as such, it includes diverse AI/AN cultural representation. Because of this setting, workshop participants co-designed a tool that is representative of this diversity. Note that each community has its own specific values, priorities, and expectations, and our workshop participants highlighted what is focal to them. Other AI/AN communities may hold different priorities, which makes it important to establish partnerships with specific communities to verify their unique needs.

We used thematic analysis²⁹ to identify our workshop participants’ goals for a health research dissemination tool. Participants identified three main goals for the prototype: learning, communicating, and finding. They emphasized the importance of learning about research results while acknowledging the history of unethical research in AI/AN communities. They also wanted access to relevant health education resources to support their wellbeing. For communication, participants suggested integrating social features to facilitate discussions among stakeholders and with researchers. They also wanted to be able to easily find and track ongoing research in their communities and access resources to address research problems proactively. Thus, the prototype content should include research education, research background, topical health resources, status of study, and study results, with clear, straightforward language and cultural and contextual sensitivity. Workshop participants also shared that visual design elements should reflect diverse AI/AN cultural backgrounds and activities to ensure representation and relevance.

Methods

We conducted a mixed-method evaluation of our low-fidelity prototype. Methods for our process and procedures for data collection and data analysis are provided in this section and include information about our data collection materials, study procedures, analysis, and ethical considerations.

Materials: Data collection materials used in this study included: (1) laminated handouts of the low-fidelity prototype (Figure 1) that we co-designed with AI/AN participants and (2) a user evaluation survey. The prototype consisted of wireframes that illustrated the basic layout, design, and functionality of a website for disseminating health research in AI/AN communities. We designed the evaluation survey to gather qualitative and quantitative feedback from participants. The purpose of this initial evaluation was to get feedback on the content and functionality of the prototype rather than visual design elements which will be included in a more interactive version to be developed in the future.

Figure 1.

AI/AN Research Prototype Wireframes

Procedures: A randomized sampling strategy³⁰ was used to recruit participants to complete the usability evaluation survey during the University of Washington First Nations Annual Powwow—an annual Tribal event open to the public. Participants were recruited from a table outside of the powwow activities along with other vendors and organizations promoting their businesses. Inclusion criteria required participants to be 18 years or older and interested in both reviewing our prototype for health research results dissemination for AI/AN communities and providing survey feedback. We provided participants with an overview of the study’s purpose and procedures, and verbal consent was obtained from all participants before they began the prototype evaluation. Participants were voluntarily entered into a random drawing for a chance to win a prize (e.g. gift card, beaded earrings). They were then given access to the prototype and instructed to navigate through the various sections and features, exploring the prototype as they might with a fully functional website. After interacting with the prototype, participants completed the evaluation survey, which included a mix of closed-ended and open-ended questions designed to capture their impressions, preferences, and suggestions for improvement. Key areas of focus included search and accessibility features, content and information presentation, interactive and personalized features, and overall design and usability. Responses from the evaluation survey were collected and recorded for analysis, with both qualitative and quantitative data gathered to provide a comprehensive understanding of participant feedback.

Data analysis: Quantitative data from the closed-ended questions were analyzed using descriptive statistics to identify trends and patterns in participant responses. Qualitative data from the open-ended questions were analyzed using thematic analysis²⁹ to identify common themes and insights related to the prototype’s design and content. We used R for quantitative analysis and Dedoose for qualitative analysis.

Ethical Considerations: This study was approved by the University of Washington Institutional Review Board and the Alaska Native Tribal Health Consortium’s Alaska Area Institutional Review Board. It was also approved by a Tribal health research review board.

Participants

The study included 38 participants with diverse demographics. The majority self-identified as American Indian or Alaska Native (68%, n=24), followed by White (15%, n=6), African American or Black (11%, n=4), and Asian (8%, n=3), while 18% self-identified as Hispanic (n=6). The gender distribution was predominantly woman (76%, n=29), with men (13%, n=5), transgender (10%, n=3), and gender non-conforming (1%, n=1) participants also represented. Participants ranged in age from 21 to 55 years, with an average age of 36 (SD=11.7). Most participants had at least some college education (95%, n=32).

Results

Participants were asked to share feedback on the prototype concept, including understanding of the purpose of the prototype concept (Table 1), finding information (Table 1) and likelihood of use (Table 2).

Table 1.

Understanding prototype purpose and finding information

Table 2.

Likelihood of Use

Overall, most participants found the prototype concept to be effective in conveying the purpose of each prototype section (M=3.86, SD=1.03, n=37). They also found it easy to find information within the prototype (M=4.12, SD=0.91, n=34).

We also asked participants to share feedback on the likelihood of the prototype being useful to themselves and other specific groups (Table 2). Overall, the responses indicate that participants found the prototype concept to be useful across different groups, including AI/AN Youth (M= 4.35, SD=0.98 n=34), AI/AN Elders (M=4.41, SD=0.74, n=34), and health researchers (M=4.45, SD=0.94, n=33). The likelihood of participants using the prototype once it is finished was also high (M=4.48, SD=0.65, n=35), reflecting strong interest and positive reception.

Summaries of participant qualitative feedback are outlined below by use and functionality, visual attributes, interactive attributes, personalization, and contextual information (see also table 3 for highlights).

Table 3.

Highlights of Qualitative Feedback by Theme

Use and Functionality

When asked about the use and functionality of the prototype, participants highlighted a range of features they valued. They liked the ability to discover ongoing and completed research studies in AI/AN communities, to understand how research study results help solve problems for AI/AN communities, to have the ability to send direct messages to researchers, and to post comments about the research through a comment forum. They appreciated the notion of a clear, well-organized, and straightforward layout, mentioning the systematic structure and ease of navigation. Most found it easy to understand, with clear sections, objectives, and consistent language. Participants valued the transparency in presenting research status, reports, and researcher bios, which helped them feel more informed and confident about the information available. Participants also noted that the potential for a website tool like this stood out from others they’ve engaged with and could help users find necessary health research resources more effectively. Accessibility features, such as high contrast colors and easy-to-read text, were valued, especially for the possible use by AI/AN Elders, and hover-over pop-ups for definitions and instructions were also noted as potentially useful.

Visual Attributes

Although our prototype evaluation was intended to be less on the prototype’s visual attributes and more on its content functionality, and information organization, many participants responded to its visual appeal. Many valued the simple layout, which featured easy-to-understand graphics and high contrast for better accessibility. The simple, clean, and user-friendly design made a strong impression, with some participants specifically highlighting the front page, use of Indigenous images, and color schemes. However, some participants described the visuals as “dull” and “basic,” and suggested including more graphics, infographics, and vibrant colors, particularly to engage younger users. They also suggested adding more creative polish, making the website less “square and gray”, and including regional or Tribal maps to aid in navigation to information on specific communities. They emphasized the need for more Indigenous images, graphics, and art/design elements in negative space, suggesting enhancements with more interactive graphics. To appeal to a broader audience, some recommended using larger text and diverse fonts. Specific requests included ensuring that the “Home” dropdown menu uses varied synonyms instead of repetitive headers for increased clarity which is contrary to established user experience standards.

Interactive Attributes

Participants found the ability to check research status and view results in different media formats (e.g. video, text) memorable. They noted including videos on each page to break down dense research information was positive. Researcher bios and photos made the site feel more personal and relatable. Pages dedicated to community health resources and background information about research and ethical protections were also important features. However, some participants indicated a need for additional interactive features to enhance understanding and usability. Some participants suggested adding more robust search features to allow users to search by researcher’s name, Tribe, geographic location, and health research topic, highlighting these features as having positive impacts on search and accessibility. Adding a site map and making the navigation more user-friendly were recommended, as well as a dedicated page about the organization managing the research and its members. They also expressed interest in engaging with more multimedia content, such as listening to podcasts about research study results and accessing educational tools like research-related certification courses and self-assisted learning materials. A few participants emphasized the importance of integrating social media features, such as hashtags and social media posts, to enhance engagement and connectivity to information across social media platforms.

Personalization

Participants suggested personalized features, such as forums for comments and discussions, and noted the potential for personalizing their experience through more curated content or favorites. They understood and appreciated the prototype’s purpose of sharing health research results with AI/AN communities and valued the potential to connect with researchers and other community members. Elements like an interactive map to select different AI/AN groups and options for users to choose colors and graphics were suggested, along with making the website multilingual to improve accessibility. Participants also recommended personalizing user pages post-signup including features that allow users to see curated content based on their preferences such as a feature to “favorite” specific studies, researchers, communities, or health topics for curated updates.

Contextual Information

Some participants also wanted more information about research participants and the overall research in more simplified terms. Some participants also requested simplified examples of research topics and more information about how data is gathered and used.

Some also felt the prototype structure was good and only needed minor tweaks, expressing satisfaction and eagerness to see the next version. Despite these suggestions, several participants mentioned there was nothing they particularly disliked about the prototype concept.

These suggestions reflect a desire for a visually appealing, interactive, and user-friendly tool that offers robust search capabilities, personalized content, and clear, accessible information. These insights underscore participants’ desires for a visual tool that effectively communicates health research results and fosters community engagement as well as education.

Implications

Our Indigenous Community-Centered Design approach not only enhances our prototype’s visual appeal and functionality but also honors Indigenous community knowledge and methodologies. It fosters trust, engagement, and collaboration, ensuring that the platform is both more effective and more culturally and contextually appropriate for AI/AN communities. The feedback gathered from participants on our prototype evaluation provides valuable insights for the development of a more effective and user-friendly research results dissemination platform for AI/AN community audience (Figure 2). The emphasis on visual appeal, accessibility, and interactive features highlights the importance of designing a tool that is not only informative but also engaging and easy to navigate. On a surface level, incorporating more graphics, vibrant colors, and Indigenous images could enhance the visual appeal and make the platform more attractive to a broader audience, including younger users.

Figure 2.

Design Implications (Credit: Designed by Hyeyoung Ryu, PhD)

On a more technical level, the need for robust search functionality and personalized content underscores the importance of providing users with tools to easily find and engage with relevant information. Features such as the ability to search by researcher’s name, Tribe, geographic location, and topic, as well as the option to favorite specific studies and receive curated updates, can significantly improve user experience and satisfaction. The feedback also indicates a strong desire for social media integration and interactive elements, which can increase accessibility and foster greater engagement and connectivity among users. Integrating social media features, such as hashtags and posts, and adding interactive elements like maps and multilingual options can enhance functionality and appeal. Participants value being able to connect with one another and have an ability to respond and communicate about research being conducted in AI/AN communities in a convenient way.

The ethical importance of content transparency and the inclusion of researcher bios and photos suggest that users value a personal and relatable connection to the research being presented. Offering clear, accessible information about research status, reports, and the researchers involved can help build more trust and confidence in the platform. Moreover, providing a platform for community members to easily communicate with both researchers and other interested users supports increased transparency and collaborative processes that are less commonly used in standard research dissemination methods.

Conclusion

These insights highlight the need for a comprehensive, community-centered, and user-centered approach to the design and development of health research dissemination tools for AI/AN communities. By addressing the identified improvement areas and incorporating suggested features, developers can create effective tools that not only communicate health research results but also foster community engagement and education, leading to a more equitable and supportive environment focused on community strengths and relationships. Additionally, this approach ensures that the tools are more culturally resonant and respectful of Indigenous knowledge systems, promoting trust and collaboration between researchers and AI/AN communities. By integrating community feedback and prioritizing relationality, we can develop platforms that are not only informative but also affirming of community perspectives and needs, ultimately contributing to the overall well-being and resilience of AI/AN communities.