The Threefold Path to Equity: Approaches for Health and Aging Researchers

Abstract

The authors present a model for pursuing equity in research on health and aging, in terms of: (a) community-driven research governance, with reference to examples inside and outside of the United States, (b) a focus on policy change, where policy is defined broadly in terms of all legislative and regulatory change, and (c) equity-focused research practices, at the level of measurement, analysis, and study design. The model is visualized as a “threefold path” that researchers may walk, to achieve changes within our field, and changes in how we interface with other fields, and communities.

Following the murders of George Floyd and Breonna Taylor, the pages of academic journals have been filled with new pieces that seek to address systemic racism (Adkins-Jackson et al., 2022; Alson et al., 2021; Dean & Thorpe, 2022; Hing et al., 2022). Alongside this push are discussions of other kinds of inequity, including ageism (Barrett & Michael, 2022; Ramirez et al., 2022), ableism and fatphobia (Stoll & Egner, 2021), heteronormativity (Jones, 2019), and transphobia (Stone et al., 2020). This work has provided guidance to academic research as it already exists, rather than how we bring about systemic change within and beyond our disciplines (Bohren et al., 2022; Chantarat et al., 2021; Dean & Thorpe, 2022; Hing et al., 2022). Systemic inequities are “systemic” because they are constituted by the interrelations between institutions, as well as within them (Bonilla-Silva, 1997). An attack on systemic inequities must therefore strike at systems that create inequitable power structures (Go, 2017). Furthermore, it must propose changes that have the potential to affect interfacing institutions, and benefit communities that have consistently been denied equity. If we want to make a difference, we must consider moves that affect the squares next to us on the institutional checkerboard. To that end, we volunteer a threefold path that researchers can embark on, to begin the work that systemic change requires. The contribution of this paper is to demonstrate that these three paths—policy, research, and just governance—are intertwined and necessarily so. Therefore, if we want to ensure that our work remains scientifically powerful and supports justice, it is not enough to that we see researchers advancing down one path; instead, we must see progress down all three.

Why Do We Need Paths to Equity in Health and Aging Research?

We need paths to equity because inequities exist in the world. Since the mid-20th century, social scientists have documented the ways in which older adults become neglected by society as a whole, once they discontinue their role as an economically productive agent (Cumming & Henry, 1961; Hochschild, 1975). Today, we understand that ageism manifests in a multitude of other dimensions, including through abuse, loneliness, and poor medical care (Brooke & Jackson, 2020; Fraser et al., 2020; Ramirez et al., 2022; Vervaecke & Meisner, 2021). Under coronavirus disease 2019, we have also seen ageism contribute to mortality, as the lives of older adults were treated as less valuable than younger adults (Global Report on Ageism, 2017). Older adults also face severe economic disadvantages in terms of high rates of poverty (Carr, 2010). When intersected with other forms of inequity, such as structural racism, sexism, homophobia, and ablism, it is unsurprising that we sit atop a tower of research documenting inequities among older adults (Harari & Lee, 2021; Ramirez et al., 2022; Robert & Ruel, 2006), and it is correspondingly right for us to work to eliminate them (P. Braveman, 2014; P. A. Braveman et al., 2011).

However, alongside the inequities that exist in the community, we should not be blind to the inequities coded into our own workplaces. There are often demographic differences between researchers and the people they study, especially in terms of racial composition, or economic background, and the positionality of researchers may influence the presentation or interpretations of findings. The work that we do in diverse communities has mostly been “extractive”: paying people to participate in studies (Cheff, 2017), while giving little back to those communities, instead concentrating income and capital in already-wealthy research institutions (Kouritzin & Nakagawa, 2018). The progress of science, and knowledge for its own sake is valuable, but the amount of research that we produce has exploded (Bornmann et al., 2021), and communities are well within their rights to ask “Why did we do this?”

Our work does not typically orient itself around this question, but rather to the networks of discipline-bound professionals in our careers (Watts, 2017). Indeed, our jobs keep us too busy, and the incentives we encounter are too great, to resist this drift toward insularity. Thus, as we advance in our career, and earn more, we reproduce the gaps that we set out to study. We are all to some degree aware of this; the question instead is what can we do? What kind of agenda can we have, what kinds of plans can we make, and what benchmarks can we measure ourselves against? We can do better than this, and in this piece, we lay out a way forward.

The Governance Path

First, it is important to recognize that the discourses surrounding inequity, and the categories we use to describe inequities, are shot through with power. They were created in the context of well-resourced institutions that diffused these discourses throughout society (Connell, 2018; Go, 2017). To use the example of race, the sociologist Julian Go gives a powerful example at the Congress of Arts and Science in St. Louis during 1904, where a room of White researchers laid out the conditions for the formation of American social science, while just down the street, the World’s Fair had turned Zulu, Kwakiutl, Arabs, Filipinos, and Indians into exhibits of how “savages” conducted their daily activities (Go, 2020). What would it have looked like, instead, to have different conditions for the production of authoritative knowledge—or as Gayatri Chakravorty Spivak asked more than 30 years ago about “subaltern” studies in India, what would happen if the people being studied spoke for themselves, about themselves (Spivak, 1988)?

Accordingly, the apex of this diagram points toward imagining new democratic power structures for the production and distribution of knowledge. These models are more developed in some areas of research than others—most notably in HIV research (Guta et al., 2014), research with Indigenous populations (Macaulay et al., 1998; Schnarch, 2004), and in Black communities (Bailey et al., 2021). In this literature there are many different, well-tested models of community involvement. For public consultations, common in the United Kingdom, there is a well-developed Public and Patient Involvement infrastructure, including for dementia research (Jinks et al., 2013; Miah et al., 2019). For community advisory boards that inform research questions and design, and improve community buy-in, there are numerous examples in the not-for-profit and academic sectors—especially active in Latin America (Fals-Borda, 1987; Mitchell et al., 2020). There are also models for full legal co-ownership of the research data by research institutions and communities (e.g., the framework of Ownership, Control, Access, and Possession in Canada; Schnarch, 2004).

The level of involvement in the project will ideally be tailored to the capacities and desires of the community, and not necessarily follow a “more is better” principle when it comes to community involvement. Communities may not feel the need to be heavily involved, or be overburdened in a new, demanding role beyond their already-existing responsibilities in community (Doyle & Timonen, 2010; Janes, 2016). Regardless, for researchers on aging who are looking for examples, there are abundant models that involve older adults across a range of health conditions (Miah et al., 2019; Turcotte et al., 2019), and social positions such as race, sexual identity, or socioeconomic conditions (Bendien et al., 2022; Blair & Minkler, 2009; Dong et al., 2011; Doyle & Timonen, 2010; Van Wagenen et al., 2013).

A challenge with many of the above examples is that they tend to come and go—leaving researchers to build trust over and over again, while leaving little that lasts in the communities they study (Jinks et al., 2013; Turner et al., 2020). It is small wonder that trust between community and researchers can be eroded under these conditions. A field of researchers may instead be interested in setting up independent cross-project organizations to represent community interests, such as community data trusts (Elevate Health, 2022), backbone organizations (Kania & Kramer, 2011), or community-based organizations that serve to integrate high-profile multisectoral partners and disparate community-based organizations (a “local integrator,” see: Centre for Connected Communities, 2022). This last part is key, because there is always the danger that a project’s “community” arm will be composed exclusively of elite representatives from other high-profile organizations, and contain little to no lay community representation or control (Wolff, 2016). Community boards may even be demographically similar to the population being studied, but represent elites from that population, with divergent interests and perspectives (Táíwò, 2021). It may be more productive to create bridges between those in power, and those without it, so that community does not have to remain a mere spectator or uncredited consultant—but rather have power over the process, or to initiate research projects using the leverage that organizations like community data trusts provide (Elevate Health, 2022). An institution-building approach may also serve to accelerate community-engaged research, because it rightly takes time for researchers to build trust with community, and if there is already a local actor with legitimacy among lay community members, it keeps open lines of communication between communities and researchers.

As a corollary, there is also the danger of “false friends,” who appear to be community advocates and representatives, but have very poor relationships with community. For example, when entering into a research project on services for Indigenous Elders, a researcher might be tempted to partner with local long-term care homes with an Indigenous focus—unaware of scandals about poor quality of care that never made the press, but are the subject of frequent conversation in community. This is all to remind the reader: trust and bonds with community must come first, and organizational partners second, in determining true community representation in decision making. Small-scale qualitative research projects, carefully constructed alongside people living in community, may identify organically arising opinion leaders, or people who connect otherwise-disconnected cliques, as a useful first step toward building these relationships (Valente, 2012).

The Policy Path

The rightmost “foot” of the triad in Figure 1 is “policy,” which is a deliberately broad term for changes in law, regulation, or practice. These could be changes in law at the national, regional, or municipal level—but it could also be as microlevel as a change in reporting practices and policies at a major health care provider. Here, the most basic step one can take is to responsibly report results, to avoid re-stigmatizing disadvantaged groups, and consciously aim for impact in what one publishes. Community governance can facilitate this, especially if they have control over the messaging, and there are formal procedures about how to handle disagreements over interpretation and dissemination (Macaulay et al., 1998). The next important step is participation in planning tables and committees to ensure one’s perspective is heard and acted upon and cultivating networks between researchers and policymakers of all kinds.

Figure 1.

The threefold path to equity.

This node in the threefold path avoids complacency in the research team—it is not enough to simply gesture toward the policy relevance of one’s work, but one must make it relevant. This is an area where researchers’ connections to established actors may be a boon. If a researcher’s home institution has connections to high-profile networks of advocates, service providers, clinicians, nonprofits, or private sector partners, they can begin the process of influencing policy by presenting their findings to them. With repeat appearances, and language appropriate to the audience, these presentations can open a dialogue where the researchers become trusted voices, and sought out for their opinions. In these presentations, researchers should dignify and credit their community partners, inviting them to speak in their own words about the importance of research findings. This can be one of the most effective ways of amplifying voices that have typically been unheard in halls of power—by actually inviting them into those halls, rather than speaking for them.

In this process, it may be helpful to very careful to define what stage of the policy cycle one is intervening in. Are you interested in setting an agenda by raising awareness of a new problem? Critically examining how we could be solving the problem better, for instance, by evaluating a current approach? Or generating and identifying solutions—recommending what should be done, rather than criticizing what was or was not done already? These cautions apply equally across many different kinds of policy analysis, not just econometric-style approaches (Abadie & Cattaneo, 2018). Here, as above, researchers who are not used to undertaking this kind of work should be humble and expect to learn this craft slowly from people who already have expertise and experience with policy-making circles. Professional organizations (see Supplementary Material for example organizations) can also serve as brokers to policy tables, for researchers who lack connections to policymakers.

Perhaps most crucially, it is important for researchers to be able to measure their success. There are several ways to go about this, from choosing a set of key quantitative indicators that will be tracked over time (ideally with community partners), to an environmental scan of new policies, regulations, popular press publications, or legal briefs that refer to the authors’ work. Relevant time scales will ideally be identified, for short-, medium-, and long-term outcomes, and potentially even before undertaking their project, the research team could develop a theory of change for their work, so they understand conceptually how their work is supposed to make a difference (Savaya & Waysman, 2005). Reflections on lessons learned and unexpected outcomes should be recorded and publicized, especially challenges with implementation (National Center for Injury Prevention and Control, 2013). It may be possible to measure change, and in some cases a complete econometric analysis with comparison groups and cost–benefit analyses may be suitable—but as with any other task, the approach ideally flows from the question, and the data, that researchers can produce or acquire.

The Research Path and Its Stages

The third, leftmost node in the threefold path is research practices, and this contains the most detailed discussion for researchers seeking to apply the conceptual model above. The items in this node (analytic techniques, theoretical frameworks, questionnaire design and measurement, data collection) are not concurrently occurring, but can be thought of as things that can be done in the short term, intermediate term, and long term. These are disaggregated in Figure 2.

Figure 2.

Stages of the research path.

The short-term strategies in Figure 2 are intended for projects that have existing and long-standing practices, where change might be slow, and involve negotiations with many actors external and internal to the project. Starting immediately, a researcher within such a project can seek out new analytic techniques that help to disentangle associations with identity and discrimination, including contextual effects, or latent variables. This could include high-visibility frameworks such as intersectionality or critical race theory, but also approaches from the QuantCrit literature (Suzuki et al., 2021), decolonization theories (Go, 2017), critical geography (Planey et al., 2019), and Indigenous ways of knowing (Simonds & Christopher, 2013). These are perspectives that have been carefully elaborated by teams of scholars for decades, and a researcher will therefore find much to draw upon. Finding new collaborators who are already well-versed in these approaches would be a valuable first step.

The intermediate strategies are intended for projects that may have some of their infrastructure already built (e.g., a grant, a team, a client, a research center, etc.), but where there is room for some structural changes in the project. Here, questionnaire design strategies could be valuable in ensuring that questions around discrimination and identity are not sidelined, or tokenized through a few questions, without much time for testing or development. Drawing upon racialization and racial formation theories, it is important to note that identity categories, and their daily reinscription in American social life, are not a simple process (Hochman, 2019; Omi & Winant, 2014). As Wendy Roth has recently noted about the “race” category system, “race” involves how people categorize you, how you categorize yourself, how you think others (including institutional actors) will categorize you, your “objective” phenotype, and your ancestry (Roth, 2016). Furthermore, for some groups in the United States, especially Hispanic individuals, racial identities may be in flux over the life course, or even situation to situation, depending on interlocutors, or large political events such as elections of an anti-immigrant politicians (Brubaker, 2004; Mora, 2014). This contains a lesson for investigating other forms of inequity; when considering any identity, not just race, considerations around the emergence and disappearance of new identity categories over an older adult’s life course may produce fruitful lines of inquiry.

Finally, if a researcher or research team has a (relatively) blank canvas to draw upon, more long-term strategies that shape an entire research agenda can be employed. For large national samples, ensuring that researchers have sufficient oversamples for assessing inequities—including intersectional inequities—will be essential for generalizing to the wider population. However, the stories one tells with one’s data are not more true, or more fair, simply because the data come from a national probability sample. These kinds of studies are only possible in high-status research institutions, whose staff may be out of touch with any social reality beyond their own, and shared research governance with communities may be institutionally challenging—although given the influence these surveys have on policy, it is still a desirable goal. Instead, more community-focused and area-specific studies may be easier to carry out, both to create power-sharing governance structures, and to be clearer about what stories one is telling, by restricting one’s storytelling to a time and a place with its specific history.

For this last point, it is worth drawing a distinction between inequities and differences, in terms of how it may affect research design. A project need not describe differences by group to describe inequities felt by one group, because sometimes a form of disadvantage happens for some groups that have no analog for other populations. For example, a project examining trauma that arose from residential schooling for Indigenous families would obviously be about an inequity the community suffered. But this research project would not need to study a White “reference group” to be informative—only that it centers the experiences of the Indigenous families (see Rotondi et al., 2017).

Conclusion

The overriding message of this piece is as follows: If we are to make a change in the world, we must think about how our work interfaces with other fields—or fails to. Policy is a lever for material change in the world, and cultural change, and it seems beneficial to our field, and the wider world, for our research to be at planning tables. Similarly, in the “governance” arm of the threefold path, funders may choose to incorporate community governance into scoring rubrics for any research that gathers data from communities, ensuring that community voices are present as more than just data. Finally, and most central to our practice, our own research methods and approaches need to reflect this commitment to equity. This is a familiar refrain, but it must go beyond measurement and new statistical techniques—the commitment needs to be evident in the framework behind research design. These are considerable standards to meet, but the challenges we face are considerably grave. No less than wholehearted sustained commitment is appropriate.

Funding

This work was supported by the National Institute on Aging (grant/award number: R37AG030481; R01AG033903; R01AG043538; R01AG048511; R37AG030481).

Conflict of Interest

None.

Data Availability

This article does not report data and therefore the preregistration and data availability requirements are not applicable.