Temporal Misalignment and Unequal Agency: What Terminal Cancer Patients Teach Us about Time and Inequality

Schedule Conflict

One can only be in one place at a time. In the short term, capital-activating actions must be fit into the one and only schedule. Conflicting demands for slots on cancer patients’ schedules from cancer symptoms, everyday life, and unpredictable delays throughout the healthcare system could significantly disrupt the continuity of care and constrain patients’ agency. Individuals who work swing shifts, for example, frequently have difficulty complying with tight control over eating, exercising, and insulin injection schedules (Bury 1982; Lutfey and Freese 2005; Paust et al. 2023). Caregivers, too, have to shoulder the burden of unpredictable schedules and consistent interruption (Altomonte 2016). Even in organizational settings designed to maximize control over one’s time, such as neonatal intensive care units, parents who cannot accommodate the inflexible organizational schedules miss opportunities to be socialized into competent caregivers (Heimer and Staffen 1998) or to activate their cultural health capital in interactions with healthcare providers (Gengler 2020). The ability to prioritize or reschedule has become a prerequisite for contemporary actors to live at the intersection of multiple fields but “stay in every game” (Atkinson 2019). Terminal cancer patients have to invest their capital in negotiating schedule conflict between chemotherapies, surgeries, doctor visits, side effects, acute symptoms, and medical bills, as well as their work life and family life, before regaining a sense of agency to make decisions about their treatment.

Trajectory Mismatch

One also cannot put the cart before the horse. In the medium term, capital-activating actions must be situated in meaningful sequences of events (Mische 2009, 2014; Tavory and Eliasoph 2013). Post-acute care providers, for example, frequently try to align patients’ trajectories of recovery with those of insurance coverage to avoid potential financial burdens on both the organizations and the patients as a result of mismatch (Altomonte 2022). Compared to schedule conflicts, individuals often have more room to maneuver between multiple, coexisting, or sequential trajectories, rather than synchronizing or collapsing them all into one. Egg freezing, for example, helps women disentangle the trajectory of finding romantic partners from the trajectory of childrearing and reclaim a sense of agency over their life courses (Brown and Patrick 2018). In cancer care, insurance coverage, regulatory approval, and clinical trials are critical institutional resources that too often follow their own trajectories and lag behind individual trajectories of disease progression. An enormous research apparatus seems to offer unlimited options (Timmermans and Berg 2003), but for individuals, science makes uneven and unpredictable progress, and on a different timescale than how fast their bodies deteriorate, disrupting the treatment trajectories they have planned.

Anticipation Uncertainty

It is also hard to act when there is no future to act upon. In the long term, patients must hold onto a sense of certainty and a future worth investing in, to anchor their capital-activating actions in the present (Beckert 2013, 2016; Emirbayer and Mische 1998; Frye 2012; Mische 2009; Sendroiu, Álvarez-Benjumea, and Winter 2025; Tavory and Eliasoph 2013). Although anticipations tend to be more malleable and flexible than trajectories, patients whose ability to anticipate the future is severely constrained, or whose timeline for “what constituted the future was compressed” (Abramson 2015:79; Heimer and Staffen 1998; Livne 2021), could see the future as “something over which they have no control” (Atkinson 2013:654) and be reluctant to take responsibility and plan for long-term outcomes (Heimer and Staffen 1998:86). The ability to anticipate a future in which their children would be well, even one that is “packaged and sold in the modern healthcare system,” provides crucial motivations and scaffolding for parents of critically ill children to activate their cultural health capital (Gengler 2020:181). Prognosis, “a form of anticipation about disease, treatment, and the patient’s future life span” (Kaufman 2015:197), also sets the stage for not only the decisions patients have to make about their treatment, but also how physicians have to communicate in ways that are “responsive to the needs of the patient for hope” (Kaufman 2015:214). Terminal cancer brings significant uncertainty and anxiety, and patients often have to first rebuild their ability to anticipate a future that is compatible with what the institution can promise before any decisions can be made.

Schedule Conflict

For participants already at the clinics, it was often through their ability to accommodate treatment schedules, not the affordability of treatment options, that inequality became most evident. Few patients could afford the hefty price tags of cancer treatment out-of-pocket, so they also had to navigate bureaucratic schedules imposed by their insurance coverage as they converged with the schedules of the disease, treatment, and the demands of everyday life.

Treatment of advanced-staged, metastatic cancer typically involves regular monitoring, continuous medication, and in some cases draining and periodized procedures such as radiotherapy, immunotherapy, and chemotherapy. Many chemotherapeutic drugs, for example, are administered in repeating cycles of two to six weeks, with follow-up blood tests, CT scans, and appointments with oncologists to check for their effectiveness and unpredictable side effects. However, except for periods of hospitalization, where the hospital time takes over, other short-term priorities almost always demand spots on individuals’ schedules. Treatment preferences varied, but agency to pursue different options was unequal: participants’ ability to resolve conflicts between personal schedules and treatment plans shaped whether they could activate resources when opportunities arose.

Full-time, benefit-protected jobs gave many participants access to cutting-edge treatments at elite cancer clinics, but these patients often had to juggle work and family responsibilities in precarious ways—preserving their main sources of economic and social capital while facing treatment schedules that demanded rigid compliance. Bobby Vaughn [7073], ³ a 51-year-old house painter being treated at one of the top melanoma clinics thanks to his unionized job, constantly felt he did not have any choice in his treatment plan. Bobby had to work 32 hours per week to maintain full-time status, as required by his employment-based insurance. When asked why he passed on the opportunity to go to another cancer clinic his oncologist recommended as more promising for him medically, Bobby explained it was not even an option given how much conflict the commute would create with his family’s already loaded schedule:

I mean, six hours, [versus] two hours. The only option was [this clinic]. . . . We have two sons, my wife works, I work. It just—for right now we’re just going to take our chances with [this clinic]. The [other clinic] is just going to throw our family in disarray.

Participants who were not more financially resourced, but were given better opportunities to negotiate treatment schedules, had a better chance of taking advantage of treatment options that became available and fit their goals of care. The following exchange between June Joseph [10008], a 48-year-old forklift driver diagnosed with pancreatic cancer, and her care team in the exam room illustrates how even a decision to continue chemotherapy is never just medical or economic, but temporal:

Both June and her oncologist agreed it would be in her best interest to keep the infusion port implanted and start a new cycle of chemotherapy right away, but as June ran out of sick leave, the challenge became how to fit the new treatment cycle and subsequent side effects into her work schedule, rather than the other way around. In June’s case, the nurse, who had developed not only a close relationship with her but also an understanding of her temporal dilemma, was able to count the days she would have to miss, carefully calculate how many days she could delay chemotherapy, and help her negotiate schedule conflict with both the clinic and her employer, before she could act on what seemed like a straightforward decision. For most participants, schedule conflict was rarely a one-time thing they could maneuver out of, but a constant struggle to “play with the cycle,” which could accumulate into significant deviance from the intended treatment plan.

Conflict that arose from the inflexibility of treatment and work schedules was further intensified by systematic yet unpredictable temporal misalignment throughout the healthcare system. When bureaucratic delays at the hospital or insurance company struck participants with an already overloaded schedule, even a few days’ wait could extend into significant constraints on participants’ agency to act. During an appointment we observed with Aaliyah Jackson, a Black single mother taking care of her teenage son who had renal cancer, the oncologist asked if her son had started the new medication on time:

One framing might cast this predicament as a chronic lack of cultural health capital, but such a view risks discounting Aaliyah’s success in securing treatment for her son at a top cancer clinic, and obscures the temporal underpinnings of the problem. Hospital visits provided protected time for Aaliyah to consider treatment options, but the timing of the call from the insurance company—between an upcoming surgery and an already full schedule as work, life, and her son’s cancer converged in her everyday life—left her little room to respond to a new problem.

State-sponsored welfare programs not only incur wait times for eligibility verification and transition between jurisdictions, but they also impose categorical restrictions on patients’ everyday schedules. Nicolas Fields [4021], a 47-year-old musician on disability-based Medicaid, decided to move to another state so that his best friend, a nurse in pediatric oncology, could become his caretaker. He found out, however, that he had to reestablish his eligibility for Medicaid in the new state before he could continue his treatment. In the meantime, his disability-based eligibility for Medicaid effectively prevented him from working. As a result, to activate his social capital for better-quality care at home, he had to endure not only a lapse in treatment but also “many idle hours on my hands . . . hours of like trying to figure out what to do with myself,” a period he described as extremely stressful and mentally devastating.

Even for participants who could afford private insurance and had more control over their work schedules, living with rigid treatment regimens still brought significant constraints on their agency, as scheduling became increasingly resource-draining to reconcile with other aspects of life. Scheduling issues were especially challenging for individuals in high-paying professions like technology and finance, who relied on working long and flexible hours to maintain not only a high level of economic and social capital (Goldin 2021; Yu and Kuo 2022), but also an identity beyond being a cancer patient and a sense of agency not defined by the disease.

Peter Curtis [4040], a 71-year-old banker, at first liked to brag about how he enjoyed traveling between Hawaii and Colorado to get involved with deals and investments, cruising on his sailboat from time to time, while making himself available for any treatment opportunities anywhere for his pancreatic cancer:

In fact, I’ve been flying back and forth from Hawaii coming over here to take [chemotherapy], then I fly back on Thursday, then I take this Friday and fly back Saturdays. . . . Yeah, I just decided I wasn’t going to let it interrupt the way I lead my life, other than I have to do this flying.

Even with all the resources and flexibility Peter had to prioritize quality of life, reconciling an increasingly demanding treatment schedule with quality of life outside the cancer clinic only became more and more difficult over time. Three months later, when we interviewed Peter again, he admitted: “finally I just thought this is too much traveling back and forth.” However hard Peter tried to prioritize quality of life, he eventually had to stay longer and longer at the clinic for radiation and checkups. As another participant Chris Mitchell [7036] explained, sooner or later, terminal cancer patients became “bound” to the hospital. In this way, schedule conflict exacerbated existing disadvantages for patients who were dependent on institutions that imposed their own rigid temporalities, and it created significant constraints on agency for actors who had flexible schedules and resources to spare.

Trajectory Mismatch

Even when participants were ready, and sometimes desperate, to activate their capital, treatment options might not align with the trajectories they had projected and hoped their investment would set in motion. We observed three intertwined forms of trajectory mismatch: (1) treatment options that participants saw as their last hope could take years to receive regulatory approval and become commercially available; (2) treatment options that were available as clinical trials could be gatekept by physician-researchers to prioritize collecting high-quality data and complying with study protocols; and (3) treatment options could require participants to maintain their capital beyond what the temporality of their terminally ill body would allow.

The extent to which participants could remedy this mismatch—between individual trajectories of disease progression and the institutional trajectories governing treatment availability—shaped their agency to activate capital and pursue the care they valued. Capital could be reliably activated only insofar as treatment options were available on the market or through clinical trials. Yet, science makes uneven progress across different types of cancer, and on a different timescale from individual trajectories of disease. Participants constantly juggled between the urgency to switch treatment as their current plans failed, and the stalling of progress when they needed it most. Although a terminal disease was, by definition, incurable, many participants were motivated to make up for such mismatch between institutional and individual trajectories by aggressively planning and searching for opportunities to bypass the institutional timeline and find next-in-line treatment that fit into the trajectories they had projected.

Celia Chang [7069], an Asian American software engineer who retired in her early 50s after being diagnosed with an aggressive type of breast cancer, decided that instead of waiting blindly for her next scan to tell her if the treatment worked or not, she should become an avid researcher and hope to get ahead of institutional trajectories. Celia and her partner, a biologist working in the biotech industry, read peer-reviewed journals and conference papers, and they crowd-sourced information on online forums. “This is my plan,” as Celia explained:

I’m going to just get the information as much as I can, learn more, because I have another six weeks before I know whether this [is] working or not. If it doesn’t work, we have to switch. Maybe at that point I have to make—we can make some decision whether go for the trial or go do other, see what’s other options [there are].

Even for participants with ample and flexible cultural capital, being an active but amateur consumer of cutting-edge research and searching for “magic bullet” options for survival was a daunting effort. Phase 1 trials entail high risk of toxicity and low response rates (Chihara et al. 2022). Any next-in-line options participants did find had to remain accessible within the right time window for them to realize their planned treatment trajectories. Even when researchers made progress on their disease, regulatory approval and market rollout still ran their own course. A paper that showed promising results in killing cancer cells could take years to translate into an FDA-approved, commercially available drug—a wait few participants could afford.

Pat Agarwal [4022], an affluent, college-educated, professional middle-class immigrant, hoped that by activating his transnational networks, he could access alternative institutional trajectories outside of the United States:

We sat down and my sister was here from India, and she has quite an influence in India. She knows a lot of people and they are pretty well off and they know people. And like there is a big institute in Mumbai and lots of people from U.S. and Western countries, they go over there for surgeries when they cannot do it right here.

One year later, after mobilizing extended family for an extensive search, Pat still had not found a viable treatment option that could get him out of waiting, and he eventually became too ill to travel. The family pushed for more aggressive treatment at local clinics, hoping that new options would become available, but none did by the time Pat entered hospice.

Clinical trials, which participants desperately looked for, follow a very different trajectory that rarely matches that of individual disease progression. Despite being widely advertised and understood as treatment opportunities for terminal cancer patients, clinical trials are designed to produce evidence about potential treatment tomorrow, not net benefits for every participant (Fisher 2008; Kaufman 2015; Keating and Cambrosio 2012; Nurgat et al. 2005). Participants were locked in a race against the disease and counted on their physicians to secure spots in trials, but physician-researchers had to screen out patients who were not best candidates for securing funding and results. As a physician explained in a meeting we observed, having to consider too many patients for limited spots in a clinical trial could jeopardize the timeline of the entire research. Eligibility criteria had to be set carefully to screen out more patients and avoid delays: “We need some kind of screening mechanism because a lot of people come to us for the study but it would behoove us to get that test done because so many patients are not eligible.”

For participants, the stakes were even higher: life itself. Failing to meet the screening criteria for one trial could mean missing the recruitment window for another; rushing to enroll in one trial could disqualify a person from better trials that were coming up. One participant paid $18,000 out-of-pocket for additional diagnostic tests to establish eligibility for enrollment in a clinical trial, only to eventually be determined ineligible. In the end, no amount of capital could guarantee finding one’s way into clinical trials and out of institutional trajectories.

Not all forms of capital were as effective in managing trajectory mismatch as cancer patients expected from navigating other parts of the healthcare institution. Depending on who set the plans and timelines of clinical trials in the organizational context, participants might find their localized knowledge and networks more transposable than economic and cultural capital when it came to jumping institutional waiting lines. The experience of Meghan O’Brien [7029], who had widely metastatic omentum cancer, illustrates how getting access to the trajectory-setting backstage of local healthcare organizations could be more effective:

I actually went to Dr. Knowles for a second opinion [be]cause I’ve worked [in the same hospital system] for 30 years. . . . Dr. Knowles happened to have a clinical trial that he was opening that would give me the same chemo as they would’ve given me over here, which he agreed would be the second line to try.

Meghan’s cultural health capital as a nurse-turned-patient did put her in an advantaged position in clinical interactions. However, it was the combination with local, personal ties she had developed working for the hospital, an often less transposable form of social capital that Small (2009) terms “organizational embeddedness,” that allowed her to connect with a former colleague overseeing local institutional trajectories and eventually fast-track access to clinical trials when she needed to switch treatment.

The struggle to manage this fundamental mismatch between the trajectories of treatment and research might also be compounded by a third form of mismatch—between the trajectory of disease progression and the need to maintain economic capital beyond what people’s bodies would allow. Because eligibility for insurance coverage remained tied to full-time employment, many participants had to navigate the conflict between their trajectories as patients facing disease progression and deteriorating health, and trajectories as employees having to sustain full-time status. Participants who were initially able to work often lost full-time employment sooner than the institution had assumed, making underprepared transitions to unemployment, disability, or retirement insurance, disrupting treatment trajectories they had planned for but few could afford out-of-pocket. Some participants described spending as much time researching new coverage and overcoming new bureaucratic obstacles as they did researching actual treatment options.

The timing of these transitions as a result of trajectory mismatch led to diverging strategies even when resources seemed comparable to start, as demonstrated by a comparison between Bobby Vaughn [7073] and Julia Kim [7037]. Like Bobby the housepainter, Julia enjoyed secure employment and good health benefits working for a multinational retailer. But unlike Bobby, who was able to maintain full-time employment, Julia lost her ability to work soon after her cancer progressed, and she had to invest economic, social, and cultural capital in navigating an unwanted transition to disability and bureaucratic hurdles that came with the new status:

My treatment is being paid [now] because I was able to go on retirement. . . . I was afraid I was going to go into a transition [from full-time to disability] where I have to pay COBRA, which is like five or six hundred dollars a month. And then my cousin says, “You know, why don’t you try and see if you can get early retirement?” . . . I just turned 55. I read on it and I called and sure enough, I could. But then I found out after four or five months . . . [when] I got all my bills and there’s a difference. . . . A lot of the copay. If I have procedures done, you know, intervention radiology, I’m still liable for 25 percent of it. And by the end of May, it was like $2,000 that I had to shell out.

Many participants had a reliable source of insurance coverage, but for Julia, insurance became a constraint on her agency to make treatment plans. Unexpected disease progression toppled not only her ability to work, but also her existing treatment plan predicated on stable, matching insurance coverage. Julia had to divert time and resources to re-create treatment plans that would match the new coverage. In other words, much capital was invested, not to strategize for the best available care, but simply to catch up with institutional trajectories to make treatment possible.

Anticipation Uncertainty

Taking action in the short and medium terms requires individuals to have calculable, or at least conceivable, futures. Yet, as the disease threw participants into extraordinary anxiety about both the length and quality of their time left, the institution offered limited certainty. On the one hand, the extent to which the future was anticipatable to participants depended on the uneven institutional trajectories and unpredictable future of cancer research. On the other hand, even for participants with types of cancer for which more treatment options were available, or significant progress was being made, the institution’s promise of a cure in the near future did not automatically translate into an anticipatable future, as “individualized prognoses about the timing of death [were] difficult if not impossible to pin down” (Kaufman 2015:196). As a result, when participants still had resources to invest toward the later stages of disease, they often invested in anchoring their present decisions in futures imagined but not necessarily realized by the institution.

A number of participants, especially those with economic and cultural capital, who sought the remote prospect of remission for an incurable cancer indicated they were not necessarily looking for immediate medical benefits, but to regain a sense of certainty about the future and thereby agency in the present. Alan Day [7528], a 66-year-old business owner, despite not finding a feasible option or having a concrete plan, continued to aggressively search for clinical trials and discuss with his oncologist every remotely relevant study he found online: “[T]he idea of doing trials, in the sense of the long-term benefit is appealing so it’s worth a little extra effort just in that sense. Plus, maybe it’ll help me. Who knows?” By searching for information that had no immediate benefit, resourced participants like Alan invested their cultural and social capital in a sense of connection to future breakthroughs in medicine, which in turn anchored and motivated their continued investment in present treatment.

Participants who had limited resources to spare often could not afford to manage uncertainty about the future. Many relied on their oncologists, who were incentivized by the institution to recruit and retain patients, for a tangible, imagined future in which clinical trials were framed as waiting for a new drug that could put their cancer into remission. An exchange we observed between an oncologist and a patient with prostate cancer not responding to the current treatment provides an illustration. Asked about the lack of remaining treatment options moving forward, the oncologist appeared to sense frustration in the patient’s question and reassured him that continuing treatment could open more options soon:

We have another option with a medication that doesn’t even have a name yet. . . . It’s in the process for FDA approval now. By the time you have done 10 cycles, you’ll likely be able to [switch to] this in 20xx. . . . From the beginning of time until 20xx, there were only a handful of treatments available. After 20xx, there were a lot more tools to help us not just buy time but put the disease into remission.

In reality, most drugs fail at this stage of development (Sun et al. 2022). Yet, by repackaging an experimental treatment of ambiguous medical value and indeterminate timeline into a concrete relationship to a remote yet seemingly certain breakthrough in science, the oncologist successfully shifted the anchor of the participant’s decision: away from the grim trajectory of disease progression and the risk of over-treatment, toward continued treatment and engagement in clinical trials as providing a sense of agency.

Even in cases where participants have made peace with their own futures, anticipation uncertainty can take alternative forms that extend beyond the patient’s own life course. Researchers estimate that 5 to 10 percent of all cancers are hereditary (Garber and Offit 2005; Jahn et al. 2022). As a result, a cancer diagnosis can trigger concerns about the cancer “running in the family” or a more general elevated risk for the next generation. Lorena Benjamin [7064], a young mother diagnosed with a rare, highly metastatic type of melanoma, described anxiety over her two daughters’ future as her motivation to search aggressively for clinical trials:

So if it raises my daughters’ risk of getting a melanoma and if there [was] melanoma and if there was actually like a gene linkage between melanoma and breast cancer, I mean, I’m not thinking about it [for] me but I’m thinking about it for the fact that I’ve got a 21-year-old and a 16-year-old. I would want to know what are the best options for my girls. And that’s probably, I would say, the number one reason for me picking a clinical trial.

For Lorena, the hereditary risk of her cancer presents a unique dilemma: her participation in clinical trials, while helping develop targeted therapies that had significantly improved survival rates in melanoma, did not necessarily offer immediate benefit for herself. However, by anchoring her decisions in the anticipated cancer risk in her daughters’ future, Lorena gained a sense of agency despite her limited resources and dire prognosis. In other words, for capital-activating decisions to feel meaningful and worthwhile even under profound uncertainty about one’s own future, participants learned various ways, not necessarily altruistic, to build a relationship with a more anticipatable future.

Relationships between Temporal Dilemmas and Resource Disparities

Now that we have shown how schedule conflict, trajectory mismatch, and anticipation uncertainty played important roles in the lives of individuals managing a terminal disease, we can connect these ethnographic findings to unequal resources among our participants. Were the patterns of temporal misalignment we observed reducible to the unequal distribution of resources, or is temporal misalignment something more than another dimension where fundamental causes play out?

Our analysis was suggestive of some associations between individual efforts to manage different forms of temporal misalignment and disparities in economic, cultural, and social capital, but multiple correspondence analysis (MCA) helps us situate our findings about time more precisely in the distribution of resources among all our participants. If patterns of temporal misalignment could be adequately explained by resource disparities, we would expect temporal misalignment to explain an insignificant amount of variation where resource disparities are present in the MCA space.

The MCA results show a more nuanced picture where resource disparities and temporal misalignment appear to be distinct dimensions of variation among our participants. Figure 1 visualizes the associations between participants (in number IDs), demographic and socioeconomic variables, and the presence and absence of temporal misalignment in our data. Along the horizontal axis (Dim 1), participants are most distinguishable by indicators of their economic (household income), cultural (level of education), and social (marital status and family size) capital, and the presence of anticipation uncertainty. Along the vertical axis and weakly associated with most variance in economic and cultural capital (Dim 2), participants are most distinguished by employment status, family size, and the presence of schedule conflict and trajectory mismatch. In other words, while the presence of anticipation uncertainty is more strongly associated with markers of resource disparities, schedule conflict and trajectory mismatch appear to contribute significantly to a distinct dimension of inequality, not only independently of Dim 1 where resource disparities are most significant but also weakly associated with most other demographic variables. We also considered whether temporal misalignment might be associated with age and cancer types, but we found that only the youngest age group (28 to 49) was marginally associated with the first three dimensions. Part A of the online supplement presents these results in more detail.

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Figure 1.

Reduced Multiple Correspondence Analysis Biplot of Associations between Individuals, Selected Demographic Variables, and the Presence of Temporal Misalignment in Their Accounts (n = 79).

A hierarchical clustering of the MCA space further validates how we grouped our participants in qualitative analysis. First, on the top left of Figure 1 are upper-middle-class participants high on economic, cultural, and social capital, like Peter [4040] and Pat [4022]. These participants occupied the top income bracket, enjoyed the most support from family members and social networks, continued to work full-time with substantial financial and temporal flexibility, and were less likely to experience schedule conflict or anticipation uncertainty. However, they often invested considerably in outrunning institutional trajectories and searching for nonstandard treatment options. On the bottom left are the majority of middle-class white and Asian patients who, like Chris [7036] and Celia [7069], had the economic and cultural capital to stay on top of the latest research and treatment options and remain positive about their future. Yet, working as professionals and living with smaller families, they did not have as much flexibility with their schedules. To reconcile schedule conflict, they often had to reduce to working part-time as their disease progressed.

On the right of Figure 1 are working- and lower-middle-class participants low on economic and cultural capital, who were also most likely to be Black women, without college education, and in the lowest income brackets. These participants struggled the most to anticipate what their future would look like with cancer. Positioned on the bottom right, participants who worked full-time jobs in manufacturing and service were more likely to struggle in the short term to balance work and family responsibilities, and they were more likely to encounter bureaucratic delays in trying to maintain their insurance coverage. Positioned on the top right, participants who worked in precarious jobs, did not go to college, and often had to stop working altogether soon after the diagnosis, were more likely to confront trajectory mismatch that disrupted their agency to manage treatment options and welfare benefits, and that they, unlike the more resource-rich patients, could not buy their way out of.

While reflecting accurately the slightly uneven but still diverse distribution of participant characteristics among those we observed in these clinics, the patterns are both consistent with our qualitative findings and provide added support that temporal misalignment is a distinct mechanism that extends resource-centric theories and connects the diverse temporal experiences of terminal cancer patients we met. Specifically, while disparities in economic and cultural capital along the horizontal axis may be significant factors in shaping anticipation uncertainty, participants’ efforts to manage schedule conflict and trajectory mismatch between the disease, one’s personal life, and the healthcare institution are independent drivers of inequality that cannot be reduced to unequal resources.

Implications for Research on Inequality

Our account has implications for understanding inequality, not just in the arena of serious and chronic illness, but in relation to agency, resources, and institutions more broadly. Our findings highlight the central role of time, not only as a resource unequally distributed in existing inequalities, but also as a family of mechanisms that connect individual agency to institutional contexts in shaping when and how resources can be used. On the one hand, institutions create a dynamic form of inequality by maintaining institutional order through imposing temporalities at the cost of individual agency. On the other hand, individuals experience these inequalities acutely in their efforts to manage their temporal relationship with institutional contexts and reclaim a sense of agency in navigating institutional resources and opportunities. Explanations of inequality that do not account for temporal entanglement between resources, agency, and institutional context may over-simplify the relational, dynamic, and temporally mediated nature of inequality, especially in such complex and time-sensitive cases as healthcare.

Cancer funnels individuals into an institutional context that foregrounds temporal dilemmas in a way that mirrors many other milieus of temporal instability. Immigration, for example, can impose decades of waiting in visa queues, court backlogs, and even detention centers for an arbitrary adjudication on one’s legal status and possible futures (Cwerner 2001; Fee 2022; Griffiths 2014; Parreñas 2021). Eviction, too, can perpetuate trajectory mismatch between stagnant wages and welfare payouts, rising housing costs, and a rigid payment schedule that poor tenants in low-income neighborhoods have few ways to reconcile (Desmond 2012). The disruption that COVID-19 created also had a temporal aspect: working mothers disproportionately shouldered the responsibility to resolve conflicts between work-from-home and school-at-home schedules (Augustine and Prickett 2022; Collins et al. 2021), small businesses disproportionately struggled with mismatch between business cycles and lockdown cycles (Bartik et al. 2020), and our expectations for a return to normalcy in the near future constantly clashed with the fear of prolonged restrictions.

In a stronger sense, temporal misalignment contributes to inequality even without the magnifying effect of biographical disruption. Consider education. The distinction Lareau (2003) observed between the “natural growth” of working-class children and the “concerted cultivation” of middle-class children hinges not only on disparities in economic and cultural capital, but also on different temporal dilemmas that parents have to manage. For white middle-class parents, prescheduled activities create a highly predictable schedule that matches their own, but their perfect plans may still be toppled by last-minute school closure due to bad weather. On the other hand, working-class, and especially racial minority, parents who have to routinely triage immediate, unexpected demands for their time (often from surveilling institutions) to get the family through the day, simply cannot afford to micro-manage their children’s free time. Or consider queer time. Queer people bear the additional burden of articulating and managing temporal misalignment as many institutions of modern capitalism are predicated on its subjects assuming a stake in a reproductive future (Edelman 2004).

In these ways, the temporal approach to inequality we advance in this article has potential to bring together a diverse range of cases to help us better understand intersectional inequality. As methodological advances allow sociologists to leverage the increasing availability of large-scale time-use and time-stamped behavioral data (Cornwell et al. 2019; Golder and Macy 2014), as well as computational approaches for measuring temporal expressions in text data (Stuhler, Tavory, and Wagner-Pacifici 2026), future research will benefit from more explicitly theorizing these dynamic, fine-grained, and intersectional temporal mechanisms of inequality.

Implications for Understanding Time Sociologically

Our study also shows the value in integrating work on inequality while continuing to articulate time as a sociological concept. Building on a fast-growing literature on temporality and agency (Atkinson 2019; Emirbayer and Mische 1998; Hitlin and Elder 2007; Tavory and Eliasoph 2013), our analysis reaffirms the utility of both theorizing time explicitly and measuring time with nuance. Following scholars such as Brown and Patrick (2018), we call for more studies that use the relational nature of time to link the concept of agency to the lived experience of inequality. We also further extend the scope of a temporal approach by offering a cross-section of how temporal misalignment not only affects individuals from diverse social backgrounds but also crosscuts institutional domains such as healthcare, workplaces, and the welfare state.

Building on foundational work by Emirbayer and Mische (1998), Tavory and Eliasoph (2013), and Atkinson (2019), we show how elements of Bourdieu’s theory serve as a fruitful starting point for moving beyond situations to institutions. Explaining how participants in our study managed the everyday and existential challenges they faced requires understanding how cancer patients’ temporal dilemmas not only delimit possible outcomes but also exacerbate resource disparities and influence their decisions to activate some form of capital. While this article draws selectively on Bourdieu’s concept of capital as used in medical sociology, a robust model of understanding temporality in institutional contexts is central to his widely used theory of fields and habitus and should interest scholars across subfields. Future research might continue to explore the underappreciated relevance of the sociology of time to our discipline’s longstanding interests in connecting levels of analysis between individuals and institutions, biography and history, as well as culture and structure.

Implications for Cultural Sociology

A longstanding debate in cultural sociology concerns how to reconcile institutional orders and individual agency as conflicting sources of action (Emirbayer and Mische 1998; Sewell 1992; Swidler 1986). On the one hand, institutions appear to impose obdurate and internally coherent logics of intertwined practices and meanings (DiMaggio and Powell 1983; Meyer and Rowan 1977). On the other hand, we rarely subscribe to institutional logics in their entirety (Hallett 2010), but draw on cultural and organizational resources to resist, negotiate, inhabit, and reengineer institutions (Hallett 2010; Swidler 1986, 2001; Zietsma and Lawrence 2010). Empirical applications of these models, while incorporating agency into sociological explanations, have been criticized for reducing decision-making to the mechanistic response of cultural dopes enacting existing scripts, or the overgeneralized agency of abstract agents pursuing the same objectives. In reality, the ways individuals experience, confront, and embed their agency in institutional contexts are diverse, dynamic, and multidimensional.

In our case, we zoom in on how time gives the healthcare institution a tangible and actionable form in patients’ decision-making experiences. The healthcare institution appears to terminal cancer patients as neither dogmas nor scripts, but practical challenges grounded in ruptured temporal relationships to which they devise diverse and specific responses. These responses do not rely on the prophetic visions or tautological purposes of the institution, but are motivated by a pragmatic disposition to make sense of one’s temporal experience while maximizing one’s room for future action against any temporal constraints. The power of institutions, in turn, may also manifest in their use of time as a means of control and discipline over individual action. Our focus on time not only offers a useful vantage point that connects agency to inequality, but it also lays groundwork toward a theory of action that will benefit from more large-scale, time-use, and time-stamped data.

Implications for Medical Sociology and Health Policy

Our findings show how time is an essential ingredient of both inequality and policies that address inequality in the arenas of health and medicine. Access to resources and treatments remains a necessary condition of more effective and equitable healthcare, yet it is far from sufficient. To be sure, very few people can afford to pay for chemotherapy out-of-pocket, and diagnoses for complex conditions, ranging from cancer to Alzheimer’s disease, are rarely straightforward. On top of this reality, time is rarely in the favor of those who face progressing challenges at the intersection of health and society. Our healthcare system’s intricate and marketized temporalities of scheduling, billing, insurance coverage, and clinical trials often introduce more misalignment than individuals can manage, and prevent people from converting resources into effective action. The Patient Protection and Affordable Care Act, for example, while effectively narrowing inequality in insurance coverage (Gutierrez 2018), does not automatically translate into health equity without individual efforts to fit oneself into misaligned temporalities between healthcare organizations and the welfare state (Altomonte 2022).

Likewise, the tensions between under- and over-regulation, often adjudicated politically rather than through evidence-based policymaking, only expand temporal constraints on patient-physician collaborations that have proven effective in combating many diseases (Epstein 1995; Eyal 2013; Marcus 2023). A deeper sociological understanding of how people manage temporal misalignment embedded in their relationships with healthcare institutions and over the course of a disease can provide a more accurate picture of the effectiveness of resource provision and facilitate the incorporation of time into the making of policy interventions.