Advancing Community–Based Research with Urban American Indian Populations: Multidisciplinary Perspectives

Abstract

The U.S. has witnessed significant growth among urban AI populations in recent decades, and concerns have been raised that these populations face equal or greater degrees of disadvantage than their reservation counterparts. Surprisingly little urban AI research or community work has been documented in the literature, and even less has been written about the influences of urban settings on community-based work with these populations. Given the deep commitments of community psychology to empowering disadvantaged groups and understanding the impact of contextual factors on the lives of individuals and groups, community psychologists are well suited to fill these gaps in the literature. Toward informing such efforts, this work offers multidisciplinary insights from distinct idiographic accounts of community-based behavioral health research with urban AI populations. Accounts are offered by three researchers and one urban AI community organization staff member, and particular attention is given to issues of community heterogeneity, geography, membership, and collaboration. Each first-person account provides “lessons learned” from the urban context in which the research occurred. Together, these accounts suggest several important areas of consideration in research with urban AIs, some of which also seem relevant to reservation-based work. Finally, the potential role of research as a tool of empowerment for urban AI populations is emphasized, suggesting future research attend to the intersections of identity, sense of community, and empowerment in urban AI populations.

Empowerment and alleviation of suffering in disadvantaged communities have long been central tenets of community psychology (Iscoe, 1974; Revenson & Seidman, 2002). In contrast to their “treatment-oriented” counterparts in clinical psychology, efforts characteristic of community psychologists attend closely to the contexts of suffering, diversity within communities, and active collaborations between researchers and communities in attempting to achieve systemic (rather than individual) change (Goodstein & Sandler, 1978). As such, detailed attention to these three domains in community-based work, particularly in relation to disadvantaged communities, would be particularly informative for the field and community partners. In this article we make a case for the importance of collaborative research as a tool of empowerment in working with urban American Indian (AI) communities and explore how important aspects of heterogeneity, geography, membership, and collaboration can impact research collaborations. We present four illustrative vignettes, three from the perspectives of behavioral health researchers and one from the perspective of an urban AI community member.

AI communities have long maintained the attention of community psychologists and a host of other applied research disciplines. Attention to AI communities has, in large part, grown due to the significant physical and mental health disparities that continue to exist in many AI populations despite the 1976 Indian Health Care Improvement Act's mandate to “ensure the highest possible health status to Indians” (Pub. L. No. 94-437, §3a; for an overview of these disparities see U.S. Commission on Civil Rights, 2004). Attention has also been garnered to focus at the interplay between behavioral health problems and sociopolitical issues such as entrenched poverty, cultural marginalization, and political oppression (e.g., Whitbeck, McMorris, Hoty, Stuben, & LaFromboise, 2002). One important response documented in the community psychology literature has been to work with AI communities collaboratively in developing locally grounded, strategic interventions to leverage systemic change. These interventions have targeted behavioral health problems directly (e.g., Goodkind et al., 2012) as well as deficits in reservation systems of care (e.g., Miller, Blau, Christopher, & Jordan, 2012).

However, the vast majority of work with AI populations has focused on reservation communities, even though urban AIs have swelled in recent decades to account for over 70% of the AI population (U.S. Census Bureau, 2010). Recent growth of urban AI populations was prompted by the federal government's “termination” era programs of the 1950s, which were designed to abolish the special status of Indian land and encourage reservation-dwelling Natives to move to preselected urban areas (Snipp, 1992). Although urban living often allowed for improvements in occupational and educational resources, it also introduced additional struggles for AIs, such as limited access to health care and social support. In terms of health care, the vast majority of the Indian Health Service (IHS) budget serves reservation communities, with only 1.06% reserved for 34 government-subsidized urban Indian health organizations (UIHOs; Castor et al., 2006). With only 34 financially-strapped UIHOs serving as the primary source of health care for urban AIs, access to these services is a serious concern. Additional barriers exist for many urban AIs reliant on limited forms of public transportation or who are not enrolled in a federally recognized tribe (Jackson, 2002; Lobo, 2001). In terms of social support, urban AIs often have diminished or less accessible resources compared to reservation AIs who have access to extended family. As a result, AIs may experience increased daily stressors (IHS, 2008; LaFromboise and Dizon, 2003) and feelings of alienation, disempowerment, and hopelessness (Jackson, 2002; Lobo, 2001; Weibel-Orlando, 1999).

Given growing concern around urban AI population wellness and the near absence of empirical work to document and address community needs, community psychologists may have important roles to play. However, a significant barrier is the absence of readily available information to inform engagement in community-based work with urban AIs. Guidelines have been written to inform systems of collaboration with AI reservation populations (e.g., Fisher & Ball, 2003), but it remains unclear how the urban context of urban AI populations might bear unique influence on the research process. As a result, researchers are left with the less than desirable “learn as we go” approach, which sets the stage for mistakes and misunderstandings that can be challenging for researchers and community partners.

In this article we aim to help fill this gap by offering a compilation of idiographic accounts of community-based behavioral health research with urban AI populations. Three accounts are offered by behavioral health researchers and one from a UIHO staff member with extensive experience collaborating in research partnerships. Each account is the personal statement of the author listed next to its title and serves as a case report from a distinct project or set of projects. Through a format of first-person narration, perspectives from multiple disciplinary backgrounds are offered alongside that of a community representative to present a broader picture of the role of urban contexts in various collaborative works with urban AIs. This presentation should be particularly salient for community psychologists given their ecologicalmindedness and commitments to context-rich understandings of community life and intervention (Shinn & Toohey, 2003).

The accounts below are offered in order of presentation by a substance abuse and mental health services researcher (Dennis Wendt), a clinical associate professor of nursing who is also a certified nurse-midwife (Melissa Saftner), a senior Ojibwe social work researcher (Sandra Momper), and an urban AI community member with staff experience at several urban Indian centers (John Marcus). Each author offers her or his own set of “lessons learned” drawn from their respective research collaborations, each with a Midwestern UIHO. Accounts focus on distinct facets of the author's research experience, and themes from each are woven together in a discussion that highlights important considerations for future research with urban AIs. Considerations are derived from research experiences in urban contexts, and many stand out as distinct from work with rural AI populations while others seem relevant to reservation-based work. Lastly, the potential role of research as a tool of empowerment for urban AI populations is emphasized, and suggestions are made for future research at the intersections of identity, sense of community, and empowerment for urban AIs.

Heterogeneity in Urban AI Populations, Dennis Wendt

A significant challenge in conducting behavioral health research with urban AIs is contending with great heterogeneity among community members. Although reservations certainly are inclusive of varying degrees of diversity, urban research requires attention to an incredible diversity of tribal, reservation, residential, and ethnoracial factors (Lobo, 2001; Weibel-Orlando, 1999). Without an appreciation of this heterogeneity, researchers might be prone to view AI participants in terms of a generic ethnic gloss. Many diversity issues are similar to other populations (e.g., gender, religion, and sexual orientation), but others (e.g., tribal affiliation, residential history, multiracial identity, and relational network) are relatively unique to urban AI contexts and may deeply affect individual identity and sense of community. For this case, I discuss four complexities associated with AI heterogeneity in the context of 17 interviews with Native community members (9 women and 8 men, ranging in age from 18-69) at an UIHO (for the original study, see Wendt and Gone, 2012). These interviews addressed what it means to be American Indian in the city and specifically in the context of an UIHO.

First, the urban AI community with which I worked was multi-tribal and consisted of individuals of varying degrees of tribal affiliation or connection. Most respondents were affiliated or connected with regional tribal groups (5 Haudenosaunee, 3 Ojibwe, and 3 Odawa) but many hailed from more geographically distant tribes (e.g., 3 Cherokee, 2 from Plains tribes, and 1 from a Southwest tribe). Although the UIHO made many efforts toward inter-tribal harmony, a few respondents mentioned conflicts or hard feelings in terms of differing tribal backgrounds, especially for tribes with hostile relations historically. An additional complication was the role that official tribal status played. Some individuals had considerable familial and experiential connections to a tribe but were nonetheless ineligible for tribal membership due to not meeting tribal requirements or lacking documentation of their credentials. Conversely, others had official tribal membership but minimal relational or geographic connection to the tribe. A further complexity was the relationship of individuals from tribes in the geographic region—who sometimes felt greater warrant for the traditions of their ancestors to be preferred—with those from more distant tribes.

Second, the urban community with which I worked was diverse in terms of residential history. A few respondents were raised on or near reservations, most had lived their entire lives in the same metropolitan area, and a few had highly transient backgrounds. It is worth noting that all 17 participants, though very diverse otherwise, had lived the majority of their lives in urban settings. Some were able to visit reservation and ancestral homelands regularly, whereas others visited seldom or not at all, or were unaware of their geographic roots. Given their urban residence, all respondents (to varying degrees) were somewhat acculturated to Western beliefs, practices, and institutions. This did not mean, however, that respondents were necessarily less connected to traditional beliefs, practices, and relationships.

Third, many urban AIs with which I worked had mixed race ancestry and self-identified as multiracial (typically with White, Black, or Latino ancestry) and/or were in mixed-race partnerships. Respondents generally reported an atmosphere of racial tolerance at the UIHO, but several respondents also expressed occasionally feeling like an outsider because of their mixed ancestry or racial appearance. This multiracial environment, combined with tribal and residential heterogeneity, was occasionally reported to be associated with suspicion towards certain community members based on their physical appearance. One respondent, for example, disclosed frustration about being confused by some as White based on her appearance, in spite of her well-known Native ancestry. This multiracial climate was complicated further by the presence of non-Native family members, staff, and researchers, alongside some worries of the UIHO being overly influenced by community members with more distant connections to Native ancestry or traditional ways, who have more recently self-identified as Native (see Jackson, 2002, for more on this issue).

Finally, an important but easily overlooked aspect of urban AI heterogeneity in my research was the individual's nodes of relationships with other urban Natives. Several respondents reported the existence of contentious factions among members with differing loyalties to urban Indian centers and their associated relational networks. This is a common problem in urban communities; because urban Indian centers frequently serve as hubs of Native community life, the existence of multiple organizations in the same metropolitan area can be associated with fragmentation or ill feelings among a community that is already relatively marginalized (Lobo, 2001).

Community Geography, Melissa Saftner

My work with an urban AI community involved a qualitative study in which twenty women between the ages of 15 to 19 participated in individual interviews or talking circles about their beliefs and attitudes towards sexual risk behavior (for the original study see Saftner et al., in press). Talking circles are considered a traditional format of group communication for many AI populations in which each member of the circle is afforded the opportunity to speak and be heard on the subject at hand and related topics. This communicative structure has been modified for use in qualitative research to permit audio recording and is widely accepted as a “culturally appropriate” supplement or alternative to standard focus group methods and interventions in social and health science research with rural and urban AIs (for more on talking circles see Picou, 2000; Strickland, 1999; Struthers, Hodge, Geishirt-Cantrell, & De Cora, 2003).

Through involvement in this project I found the geographic location of urban AI community members in relation to key landmarks and each other to bare significant impact on the research process. On one hand, the relative proximity of urban AIs to research institutions (e.g., universities) has certain benefits. Reduced travel time allows researchers to invest more time in building relationships with the community, volunteering services, or fulfilling extra-research obligations (e.g., faculty responsibilities, parenting). This also makes for less expensive research, which makes community-based research more feasible for a wider range of researchers and helps to mitigate concerns expressed by community psychologists regarding the influence of external funding agencies over the research process (e.g., Rappaport, 2005).

On the other hand, however, the geographic dispersion of community members emerged as a formidable challenge. Unlike other urban-dwelling ethnoracial groups in the U.S., urban AIs rarely live in clustered neighborhoods (e.g., ethnic enclaves); rather they are “fundamentally a widely scattered and frequently shifting network of relationships” (Lobo, 2001, pp. 74-75). One important consequence of this dispersion is the need to understand the network of relationships that constitutes the urban AI community and decide upon a specific location to host your project. Absent tribally-managed research review boards or clear organizational leadership at the community level to serve as a de-facto point of entry, some researchers have suggested navigating these dispersed communities by basing work out of an urban Indian center (e.g., Lobo, 2001; Jackson, 2002). Typically, urban Indian centers bring together community members from across vast urban landscapes by providing a range of services tailored to community needs (e.g., employment services, health services, social events, and cultural education). In the context of health research, UIHOs can fill this role by representing community interests throughout the research process and by organizing a project advisory council (or review board) to serve as guide to the community's various relational networks. In addition to fulfilling these roles, the UIHO with which I partnered offered indispensable organizational input and support, which was helpful in overcoming community member concerns about possible exploitation by researchers. These understandable concerns are common among many indigenous populations (Smith, 1999), but with the backing of the UIHO administration and advisory council, concerns were minimal and easily navigated.

A second challenge to emerge in response to geographic dispersion was the need for creativity and resourcefulness in demonstrating commitment and building trust. Standard practices employed in ethnographically-informed research with reservation communities frequently include prolonged residence on the reservation and familiarization with that tribe's history and culture; however, absent a geographic center or a singular tribal makeup to become well versed in, developing trust in work with an urban AI community may require additional creativity. Although the support of an urban Indian center like an UIHO can go a long way toward establishing trust, researchers must first gain the confidence of the center's administration and staff. Means of meriting the support of an urban Indian center will likely hinge on where a researcher's particular skills match up with the organization's mission and values. For example, an urban Indian center that relies heavily on grant funding to support its services may value a research relationship if the researcher volunteers to help secure grant funding. Alternatively, an UIHO offering health and prevention services that intentionally stand in contrast to the highly medicalized services available at nearby medical centers may be turned off by researchers unable to operate outside Western biomedical discourse and medical framings of community problems.

In my experience, volunteering services at community events (e.g., selling raffle tickets) and spending time with community members at the UIHO was essential, not only in developing trust and demonstrating commitment, but also in obtaining quality data. In the context of participant recruitment and data collection, caregivers regularly referred to the community event at which we had met in introducing me to a friend with teenagers that could participate in my study. Being a familiar face garnered enthusiasm from participants and their caregivers, which translated into more sharing in talking circles and a greater determination to problem-solve barriers to participation (e.g., irregular work schedules, unreliable transportation). This familiarity also afforded a local “groundedness” to the questions asked, data collected, analyses run, and interpretations made, which all contributed to more valid findings. For example, in preliminary talking circles it became clear that the vast majority of adolescent participants were very trusting of their health service providers, which allowed me to avoid confusing participants and potentially skewing results by inaccurately framing discussions of access to health services as related to commonly assumed, but in this case incorrect, assumptions of distrust.

Flexible Membership, Sandra Momper

For researchers, like me, who are AI, working with urban AI communities presents unique opportunities and challenges tied to membership flexibility. Absent clear geographical boundaries, singular tribal affiliations, and longstanding relational networks that often clearly demarcate “in-group” membership for AI reservation communities, AI researchers are often afforded the opportunity of community membership through work with urban AI communities. However, in my work, the flexibility of urban AI community membership also challenged me to shift between community and academic contexts and respond to challenges in fostering community ownership of research projects.

Developing a sense of community through regular contact with Native people in Native spaces is particularly valuable to many AI university faculty members due to working and living in settings steeped in values and practices of settler-colonial society. Although AI researchers often establish research collaborations with home communities, reservations, and tribes—in part, to maintain rootedness in their particular cultural community in ways that being a clear “outsider” in work with other reservations would prohibit—membership in urban AI communities is much more flexible. For example, I began building relationships with this UIHO to augment and sustain the sense of connectedness to Native people I otherwise only receive from the few annual trips I make to the Ojibwe reservation of my early childhood. Community needs have since led me to decide to take on additional roles as a grant writer and evaluator for community programs; however, the urban context of this community has afforded me flexibility to balance these roles with being relationally connected as first and foremost a community member. This sense of connectedness reinvigorates my sense of personal well-being and my initiative to aid AI populations with my skills as a social work researcher.

This flexibility and fluidity of community membership, however, presented me with two significant challenges that have been markedly diminished in parallel work with reservation populations. First, in comparison to ethnographically-informed work on reservations where cultural emersion is facilitated by geographical and temporal distance from institutions of research, the absence of a geographic area to physically inhabit in work with urban AIs can result in interactions that resemble brief, refreshing islands of time within a sea of the dominant society. Reflecting similar experiences of urban AIs leaving an urban Indian center to participate in a society that regularly confronts them with racism and indifference, time spent working with urban AIs can develop in tension with time spent fulfilling university faculty responsibilities (e.g., emails, teaching). Although time spent in the urban Indian centers offers a refreshing sense of local Native culture(s), visitors literally sign in and out of these Native spaces. This style of temporary “in and out” interactions forced repeated shifts back and forth between the academic and the Native—two distinct and culturally-rooted social scripts. The temporary nature interactions can risk less in-depth and less intense engagement with community issues. As a result, work with urban AIs may require ingenious means of ensuring the depth of engagement typically facilitated by extended residence and solitary dedication to reservation-based work.

A second complexity tied to flexible community membership in urban AI communities has centered on barriers to community ownership of research projects. Whereas one might imagine that greater distance from reservation policies of forced reliance on government rations might lead to a comparatively greater sense of agency and community efficacy among urban AI communities, all of my experiences to date suggest the opposite. While reservation settings have by and large shifted from being experienced as places of forced relocation to safe refuges from dispossession by the federal government and dominant society, urban AI communities often struggle to coalesce and organize absent claims of “sovereign nationhood” and stable community membership. As a result, urban AI communities face additional barriers to assuming control over research with their members not present in most reservation settings. Initially, I approached this aspect of the status quo with confidence that through standard practices of “capacity building” I could leverage confidence in community members’ abilities to take charge and assert themselves in our research relationships (see Jumper-Thurman, Vernon, & Plested, 2007). However, slow progress in capacity building over more than eight years of engagement has suggested that the urban context harbors formidable structural barriers to developing a communal sense of identity, agency, and power to assert needs and manage behavioral health programming (see Chino & DeBruyn, 2006). Structural barriers likely include the paucity of UIHOs in major metropolitan areas, pervasive poverty, and inadequate transportation; however, future research is needed to develop a more comprehensive understanding of barriers to urban AI community empowerment. In the meantime, it is important to continue to push for community ownership of research endeavors in urban AI communities, as well as anticipate that such efforts may demand additional time, energy, and financial resources on the part of the researcher.

Comments on Research Collaboration, John Marcus

[Disclaimer: John Marcus is currently an AI program assistant specializing in culture-focused suicide prevention at an UIHO. His views may not be unique to just urban settings, but are important views from an “insider” and well respected community member. These views are his own and should not be interpreted to reflect on his UIHO employer or its policies.]

My experience has been that our urban AI community is open to research participation if the research is done in a way that is respectful of our culture. More specifically, Native and non-Native researchers alike should display a certain level of cultural competence and humility, clearly communicate and remain faithful to the agreed upon research negotiation, and respect the community's cultural traditions throughout the process.

In general, there does not seem to be any established reputation surrounding social science researchers as either trustworthy or untrustworthy. When research has come up it was related to government-funded institutions and the experiences shared has led to a mistrust of such institutions. Due to these experiences, what is important to the community, irrespective of the researcher's status as Native or non-Native, is establishing trust which can be assisted through demonstrating a level of cultural competence when interacting with community members. It is important that the researcher become familiar with tribal customs, behaviors, and the treaties of the region they are doing research within because this will help them understand, recognize, and respect tribal sovereignty. This is what I consider to be embracing a post-colonial perspective in which tribal citizens are viewed as members of independent, sovereign nations engaged in the process of exercising birthrights, instead of institutionalized propaganda such as AIs being conquered people, dependent on the U.S. government.

Cultural competence is something that can be built by attending community events and learning from community elders, but in addition to this understanding of cultural customs and behaviors, researchers should establish a more meaningful relationship with the community than simply coming in to collect data and then leaving. I recognize that many researchers might be concerned about losing claims of objectivity by attending events and engaging with community members, but this is what we would like to see. A sufficient level of involvement might be attending four events per year so that researchers make themselves available to interact with. This community contact is important both leading up to and after the actual research project, and by doing so, researchers will gain a better understanding of community beliefs and practices.

These culture-based norms should be respected throughout the research process. This means clearly communicating the terms of participation in a project, presenting the findings to the community before publication for feedback, and following through with the original agreement of participation. Clear communication about the terms of involvement is crucial for establishing mutual agreement between community and researcher so that both sides are content with the arrangements. In these terms of involvement, emphasis should be placed on the potential impacts participation might have on both community members and the community as a whole. Research should be a process that helps to bring our small community together, not apart.

An important part of agreeing to participate should also require that researchers inform the community of findings before publishing results. This could be done by giving at least six weeks’ notice before presenting findings before community members and tribal elders in an easily accessible location. In this presentation it is important to recognize and respect the oral traditions of our people, so I would suggest that PowerPoint slides be kept to a minimum, with the majority of information being conveyed orally. It is also important that researchers be open to the interpretations of results made by community elders after the presentation. In doing so, this step would allow for valuable community feedback that could potentially prevent misunderstandings by offering alternative or local explanations of findings before publication.

If able to negotiate these important issues, researchers should feel confident in engaging our urban Native community with proposals for consideration because they will likely be well received. We, as a people, would be willing to share our culture with others and participate in research projects that help to ensure research literature accurately reflects who we are, and if this in turn, above all, could be shown to be helpful in the rebuilding of our Nations.

Discussion

Experiences offered by these three researchers and one urban AI community organization staff member make a compelling case for conceptualizing research with urban AI populations as an overlapping but, in many important ways, distinct endeavor from reservation work. They also offer a plethora of insights that might encourage, inform, and improve collaborative research endeavors with urban AI populations. Emphasizing heterogeneity, the first case touched upon the importance of recognizing and responding to multitribal constituencies, varying residential histories, multiracial members, and fragmented relational networks. Discussing community geography, the second case emphasized the value of close proximity to research institutions, the importance of partnering with an urban Indian center to overcome community dispersion across vast urban landscapes, and the need for creativity in demonstrating commitment to improving conditions in the community. Focusing on membership, the author of the third case shared how the more flexible membership of urban communities allowed her in-group membership in a refreshing Native space but also left her with challenges of shifting between cultures of the community and the academy, as well as addressing barriers to community ownership of their collaborative work. All of these challenges, complexities, and opportunities stood out to these researchers as important “lessons learned” from their research experiences with urban AIs. Finally, the author of the fourth vignette emphasized a general openness among urban AIs to research participation, provided that researchers develop “meaningful relationships” with the community, adhere to local communicative norms, demonstrate “cultural competence,” and respect the sovereign status of tribal peoples. These comments, alongside those of our other authors, resonate closely with increasingly popular notions of “cultural safety” as a framework for research with indigenous populations (for more on cultural safety see Anderson et al., 2003).

These accounts offer rich contextual information about research with urban AIs that fits well with accounts from work with geographically disparate urban AI populations in the Northeast (e.g., Iwasaki & Byrd, 2010), West Coast (e.g., Weibel-Orlando, 1999), and Midwest (Jackson, 2002). It is also worth noting that many of the themes discussed have been recently observed by several anthropologists working with urban AI populations (e.g., Jackson, 2002; Lobo, 2001, Weibel-Orlando, 1999). However, each narrative stands as a distinct case report. Thus, it would be a mistake to interpret any of the accounts provided as “representative” of a particular group (e.g., urban AIs), and although future research with urban AIs will likely find relevant much of the information contained in these narratives, recommendations are not meant to be transported and directly applied to other contexts. Rather, these narratives offer descriptive accounts of community-based research with Midwestern UIHOs so that future researchers may carefully consider if and how the information presented is relevant to the particular urban AI context in which they plan to work, a process that requires input from community members.

Future Directions for Community Psychologists

The insights shared by these three researchers and one community member collectively highlight the need for better understanding the intersections between community, identity, and empowerment within the urban setting in which urban AIs reside. Here we highlight the need for future work on the relationship between sense of community, identity, and empowerment.

Connecting sense of community to empowerment

Sense of community is a construct with a long history in community psychology that has been discussed as a potential tool of empowerment (e.g., Bachrach & Zautra, 1985). However, given the geographic dispersion and fluidity of membership characteristic of urban AI communities, implicit assumptions of geographic proximity in current measures of “community” make their use with urban AIs problematic. It seems that developing a better understanding of the qualities that constitute community for urban AIs would be an important first step in understanding the relations between sense of community and empowerment. Wendt and Gone (2012) offer a helpful example of this kind of locally-rooted research in describing the role of an UIHO in fostering connection to people, place, and culture for one urban AI community. As we learn more about influences on urban AIs’ sense of community, tailored measures could be developed and incorporated into the evaluation of empowerment efforts seeking to bolster community cohesion.

Connecting cultural identity to empowerment

Cultural identity has been tied to wellness and empowerment in the literature on AI populations (e.g., Walters, Simoni, & Evans-Campbell, 2002; Whitbeck et al., 2002), and, in the case of urban AIs, several studies have highlighted local understandings of causal links between identity issues and community problems (e.g., House et al., 2006; Iwasaki & Byrd, 2010). Given local support for a connection between cultural identity and empowerment among members of these communities, community psychologists interested in working with urban AI populations would do well to further our understanding of the unique contributions of urban settings to cultural identity, incorporate these nuanced understandings of identity into their intervention work, and develop creative ways of assessing the linkages between this cultural identity and empowerment.

Limitations

At least two important limitations should be considered. First, accounts were drawn from research tied to UIHOs. Although well-suited for hosting health-focused research endeavors, research partnerships with alternative community organizations (e.g., non-health focused urban Indian centers) may shape research experiences in important ways. For example, different urban Indian centers will vary in interest and ability to support research and actively participate in research partnerships. Furthermore, urban AIs that do not frequent UIHOs might differ in their ideas about behavioral health issues and research. Second, although all three university-based authors are familiar with community psychology, none maintains a degree in the field. Thus, the disciplinary backgrounds represented by the academic authors could be considered a limitation of this work; however, we would emphasize that, as a decidedly interdisciplinary field, community psychology is best defined by a core set of values (Rappaport, 2005), values that are well represented in the corpus of works in which all four authors have been engaged.

Conclusion

The U.S. has witnessed significant growth among urban AI populations in recent decades, and concerns have been raised that these populations face equal or greater degrees of disadvantage than their reservation counterparts. To date, little urban AI research or community work has been documented in the literature. Moreover, there is little to no information about the influence of the urban settings in which these communities reside on issues of community-based work. Highlighted in the first person accounts of research with urban AI populations, three researchers and one urban AI community member shared insights about accounting for heterogeneity, navigating community geography, managing flexible group membership, and maintaining respectful research collaborations. Discussion of these narratives pointed to important overlap with descriptive research in diverse urban AI settings and emphasized the importance of caution and careful consideration of how the contexts of future research are similar to and different from descriptions offered in these accounts. Moreover, in an effort to support future research collaborations, promising future directions were highlighted at intersections of identity, sense of community, and empowerment in urban AI populations.