The Need for “Big Bioethics” Research

Author

Joel E. Pacyna and Richard R. Sharp

Publish date

Tag(s): Legacy post
Topic(s): Professional Ethics

This editorial appears in the Jan 2022 issue of the American Journal of Bioethics.

Joel E. Pacyna and Richard R. Sharp

Empirical bioethics research has become an established field of study, with its own unique goals, vocabulary, and methods (Camporesi and Cavaliere 2021; Lee and McCarty 2016; Sugarman 2010), and with many universities and academic health centers hosting bioethics programs that support a variety of educational and translational research activities. Appropriately, the success of these programs has prompted closer scrutiny of their impact and relevance to the aims of medicine. In this issue of the journal, for example, Fabi and Goldberg challenge bioethicists to consider whether sources of funding for bioethics scholarship are helping to mitigate health inequities or contributing to those very inequities by redirecting the field toward other ethical concerns (Fabi and Goldberg 2022).

We agree with Fabi and Goldberg that the long-term impact of bioethics scholarship is highly dependent on its practitioners’ capacity to recognize systemic biases within the field and make adjustments to the aims of their research. Building upon this insight, we want to suggest that if bioethics scholarship is to remain relevant, it must also adapt its methods to keep pace with new developments in patient care and clinical research. Over the past several decades the scale of translational research has expanded considerably, both with respect to the number of studies conducted and the total numbers of people enrolled in those studies. Healthcare institutions are increasingly supporting large studies evaluating access to healthcare services, costs of medical care, strategies for increasing cost-effectiveness, and characterizing contributions to health disparities. Additionally, data sharing arrangements and applications of machine learning in healthcare promise to use “big data” in the service of improving health outcomes (Davenport and Kalakota 2019). These initiatives are fueled by both federal funding and institutional investments in implementation science, artificial intelligence, and translational research (Annapureddy et al. 2020; Chambers, Feero, and Khoury 2016).

If empirical bioethics research is to keep pace with these shifts in biomedical research, it will need to employ methods that leverage this scale. It is unclear, however, whether bioethicists are ready to respond to these opportunities and embrace the methods of “big bioethics.”

“Big bioethics” can be defined as empirical bioethics research—often surveys or retrospective reviews of patient outcomes—that collect and analyze data from very large numbers of people. While setting a minimum sample size for a “big bioethics” project would be arbitrary, we consider studies involving several thousand individuals to be “big” within the context of traditional bioethics research. Such studies typically have the statistical power to examine subtle differences in psychosocial and behavioral outcomes between subgroups, including subgroups that have been historically under-represented in bioethics research. For example, a study involving thousands of patients who are offered a new clinical intervention may be able to identify factors that predict higher levels of decisional ambivalence or misconceptions about the potential benefits and risks of the treatment. In contrast to studies that engage smaller numbers of patients, “big bioethics” research may be able to identify atypical patient experiences and less common ethical perspectives on healthcare, perspectives that might otherwise go undetected. Additionally, “big bioethics” may be able to illuminate new areas of bioethical inquiry that merit further exploration using more traditional bioethics methods. For example, a bioethics study that assesses completion of advance directives across diverse populations could identify population-specific factors that become the focus of subsequent qualitative studies examining end-of-life care.

Although “big bioethics” will be attractive to many, the pressing question is whether bioethics programs have the capacity to support this work. The answer to this question is both a straightforward “yes” and a more complex “no.” Within bioethics, there is a long-standing commitment to mixed-methods research, often combining qualitative and quantitative methods to examine complex ethical topics. Scholars in bioethics often learn multiple research methodologies, which they apply in the context of multi-disciplinary teams studying bioethical issues. Adding a new set of methods to this professional toolbox is unlikely to be concerning to bioethics researchers.

However, there are a number of more subtle challenges raised by “big bioethics” research. As has been argued elsewhere (Scully 2019), empirical bioethics is a discrete discipline within the sciences that seeks to give patients—especially those at the margins of medicine—greater voice. As a discrete discipline, its aims and assumptions tend to attract scholars whose methodological preparation aligns with the types of research methods that have been used by bioethicists to empower those who may be silenced in healthcare. For example, bioethicists with advanced training in medical anthropology or ethnography will likely find a natural alignment between the traditional aims of bioethics research (e.g. understanding marginalized perspectives on healthcare) and the epistemic orientation provided by qualitative bioethics research. Correspondingly, epidemiologists, biostatisticians, and cognitive psychologists might not be as quick to recognize potential connections between the aims of bioethics research and their areas of methodological expertise. Although bioethics researchers often partner with specialists in quantitative research, those experts are rarely members of bioethics programs. To the extent that bioethics programs support faculty and trainees whose research affinities and methodological skillsets align with the historical foci of the field—often scholars with expertise in qualitative research—many bioethics programs are not well positioned to conduct “big bioethics” research.

There are other reasons why bioethicists may be hesitant to embrace “big bioethics.” Since one of the primary goals of bioethics is to give disenfranchized persons greater voice, bioethics studies that employ qualitative methods may be seen as an vital corrective to the sometimes de-personalizing reductionism of “thin” survey research. Furthermore, bioethicists may view the prioritization of qualitative methods as essential to the future viability of bioethics, even if that priority is associated with a loss of near-term visibility and impact. For example, qualitative research findings can be difficult to publish in higher visibility medical journals, in part due to a lack of familiarity with those research methods among policy makers and clinicians. Within this environment, qualitative researchers may feel that they should continue to advocate for qualitative approaches within bioethics and resist “selling out” in favor of thin descriptions of patient experiences, which already enjoy a privileged status at many academic journals.

The challenge issued by Fabi and Goldberg is an excellent example of self-reflective accountability in bioethics. In addition to taking up their call to reassess the field’s topical priorities and financial structures that shape those priorities, bioethicists should also reflect on the methods we employ and consider the extent to which those methods provide unique insights into the needs and experiences of patients at the margins of medicine. If bioethics research is to continue to demonstrate value, it must be responsive to the evolving focus and scale of contemporary biomedical research. While it is unclear to what extent “big bioethics” research may reshape the questions asked by bioethicists, it is increasingly evident that the field of bioethics would benefit greatly from increased methodological diversity among its practitioners, including the addition of research specialists who can work with very large datasets that are commensurate in scale with the types of research initiatives that are becoming commonplace in clinical and translational research.

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