Using longitudinal qualitative research to understand the experiences of minoritized people

Abstract

This paper demonstrates how Longitudinal Qualitative Research (LQR) is an innovative method to understand the lived experiences of members of minoritized groups when temporality is a structuring element of their experiences. Most qualitative research in psychology is cross-sectional, which limits our understanding of individuals whose experiences are context-dependent and linked to the temporal norms of specific social environments. LQR is unique for allowing researchers to compare change and stability over time and reveal how social challenges and barriers impact perspective shifts and long-term decision-making. To demonstrate the usefulness of LQR as an inclusive methodology, we discuss an ongoing study of career decision-making among a diverse cohort of biomedical scientists. We have used annual interviews to follow biomedical science trainees from the beginning of their PhD into the initial stages of their careers. We present case studies of minoritized scientists to illustrate the methods for long-term engagement used to elicit sensitive and critical information during their training. We show how LQR is a viable methodology for a variety of research questions and can be accomplished using large or small sample sizes and limited resources. Our primary goal is to show how LQR is useful to understand the experiences of minoritized individuals in contexts that have historically excluded them.

1. Introduction¹

Psychology aims to broadly understand the human condition. Yet, the field has a well-documented history of using research to promote racial pseudoscience and uphold ideologies of white supremacy (American Psychological Association, 2021; Pilgram, 2008). Throughout much of psychology’s history there has been near exclusive adherence to positivist, post-positivist, and deductive designs based in the prioritization of quantitative methods (Clegg, 2016; Eronen & Romeijn, 2020). Most graduate psychology programs do not teach qualitative methods based on the perception that it is not rigorous scientific inquiry (Rubin et al., 2017). Yet, qualitative research has been instrumental in foregrounding the lived experiences of minoritized groups, including Black, Indigenous, People of Color (BIPOC) and sexual and gender minorities (SGM). Qualitative designs can center the voices of people from minoritized groups; conducting qualitative research over time allows for critical insights on perspective shifts and the impacts of sustained interaction between individuals and environments.

In recent years, psychologists have called for the incorporation of anti-racist methods and practices to center the experiences of minoritized groups (Buchanan et al., 2021; Case et al., 2014). Case et al. (2014) assert that qualitative research is a unique potential tool for social liberation and for highlighting contexts historically overlooked in the experiences of minoritized peoples. Qualitative research is rich with techniques and methodological perspectives. While there has been a recent uptick in the use of qualitative methods within psychological research (Carrera Fernández et al., 2014), much of it only scratches the surface of its methodological potential. Qualitative psychological research is mostly cross-sectional in design (Farr & Nizza, 2019; Keles et al., 2020). Cross-sectional research can provide useful information about social processes, but only as brief snapshots in time which limit opportunities to observe change.

In this paper, we draw on a multi-year study with a diverse cohort of biomedical scientists to show how longitudinal qualitative research (LQR) can center the experiences of members of minoritized groups. LQR enables researchers to engage with subjects over time and capture depths of experience in areas where temporality is important, including education, social mobility, and the life course (Wood et al., 2020). LQR is effective for understanding complex experiences in disparate and rapidly changing social domains across all populations and especially minoritized groups. As such, it provides an antidote to knowledge gaps resulting from the misrepresentation and erasure of minoritized peoples.

1.1. What is LQR?

LQR is “qualitative inquiry that is conducted through or in relation to time” (Neale, 2011, pg. 4). Not only is change over time built into LQR’s design, but data analysis relies on time as a frame of reference. Saldaña (2003) states plainly that “time is data.” LQR attends to how time “interacts and interplays” with the collection and analysis of data (Saldaña, 2003, pg. 7). Its nature allows researchers to capture change over time along individual and structural dimensions and to analyze factors influencing shifts in actions and perspectives (Saldaña, 2003).

The concept of time as data is applicable in most social domains, as each embeds its own concept of time. Saldaña (2003) provides an example of how analysis of time and change in his education ethnographies shifted his own research goals. For one study, Saldaña followed a white, novice schoolteacher in an urban school with three interviews over two months. After hearing her reflections about working with Latinx youth from low-socioeconomic backgrounds, he extended the study and followed her as she continued teaching and completed a thesis based on her experiences. In LQR unexpected observations may lead to revised questions; the potential to reveal nuance in experiences is a major strength of the methodology.

Among the most sustained efforts in LQR is the Timescapes Network, which includes multiple projects to understand the experience of personal and familial relationships, is another example of LQR methodology. The Timescapes researchers emphasize that temporal data can reveal how people construct identities in social realms over time. Specifically, Henwood and Finn’s (2010) study of masculinities and fathering over eight years revealed a process of “making sense in the present of what was meaningful for participants in the past.” In analysis they employed Saldana’s attention to continuities and changes over time (Henwood & Sharini, 2022). They suggest these LQR approaches open possibilities to study the complexity of how people align, realign, and/or distance themselves when they revisit an aspirational vision over time (Henwood & Sharini, 2023).

Another aspect of qualitative research essential to LQR is the co-construction of knowledge. This concept is especially relevant in psychology, where experimental, deductive methods fail to account for researchers’ biases and place undue emphasis on hypothesis-testing over participants’ voices (Luca, 2013). The co-construction of knowledge involves a collaborative process where researchers and participants learn from each other and gain understanding of one another’s perspectives and motivations (Charmaz, 2006). Interviews are not just information-gathering tools, but subjective encounters for generating meaning and knowledge. This is essential for research with minoritized populations, whose subjectivities are often overlooked or misrepresented. An approach incorporating the co-construction of knowledge makes space for relationships where participants feel safe to reflect, share, and find meaning in their experiences.

2. Methodological Benefits and Techniques of LQR

In LQR, interviewers use various techniques to maximize their ability to capture change over time and generate in-depth knowledge. A semi-structured interview technique ensures essential questions are asked consistently across a population and allows for probing on topics brought up in the present but linked to prior conversations. Semi-structured interviewing focuses on collecting comparable data from every interviewee by using a guide. However, interviewers can deviate from the guide to follow unexpected topics raised by the interviewee.

In LQR, the development of trust- and knowledge-building does not need to be rushed; a safe and trusting interview context is co-created over time. LQR interviews may become a context where research around change at various levels, from individual to structural, can be plumbed (Hermanowicz, 2013). While an interviewee’s choice to disclose may be driven by many factors, creating a trusting space is foundational. Literature on counterspaces identifies trust-building and sharing as essential to transformative change (Solorzano et al., 2000). For many subjects, the interview is a time for introspection or anticipation of how their data may affect change (Clark, 2010). As with a counterspace, the interview can be a site of social interaction for trust-building and transformation.

Probing by following up with additional questions is essential in semi-structured interviewing and especially beneficial to knowledge-building. In cross-sectional research, the interviewer has a single interview to probe for more detail. In LQR, an interviewer may recognize a missed opportunity and follow-up later in the same or a subsequent interview, even if the passage of time affects responses or the participant’s memory of the event. A probe might not be fruitful at the time of disclosure but may become important as information unfolds. For example, a scientist who must change dissertation topics after being “scooped” may not want to speak about their next steps right away. In a subsequent interview, they can describe their experience with the benefit of elapsed time. Revisiting experiences is key to generating cumulative knowledge and assessing stability and change.

2.1. LQR in Science Education

Our research uses LQR to explore and make visible the experiences of minoritized people in science education and training. A diverse scientific workforce is critical for addressing health disparities, which continue to mount in the United States and across the world (Nielsen et al., 2017; Yang at al., 2022). In recent decades, social-behavioral researchers have increased attention to profound disparities in access, support, and persistence in science training based on race, ethnicity, and gender. Research on the trajectories of scientists with minoritized identities is urgently needed and requires sustained engagement beyond cross-sectional analysis. Contextualizing the trajectories of minoritized scientists using time as a variable is critical to reveal the complexity involved as trainees envision and align with career and other interests; strive for satisfying personal lives; and contend with changing opportunities and barriers in scientific careers. Results of our study will inform interventions to address challenges of inclusion.

2.2. Challenges to Diversity and Inclusion in Biomedicine

For more than 30 years, the US biomedical community has tried to address stagnant levels of racial/ethnic and gender diversity. Inclusion of Black/African American, Latinx, American Indian and Alaska Native, and Native Hawaiian and Pacific Islander scientists within the research workforce has not improved in recent decades. Problems with retention and advancement among historically well-represented women (i.e., white and Asian women) also persist.

Women comprise more than half of biomedical doctoral degrees but hold fewer than 40% of full-time faculty positions, with minimal expansion into academic leadership. The problem is more glaring for Black/African American, Latinx, Pacific Islander, and Indigenous scientists of all gender experiences. Scientists from these groups make up about 9% of life science doctoral recipients employed in faculty positions in four-year colleges and universities (National Science Foundation, 2019). The numbers are stark for Black/African American scientists. In 2017 Li and Koedel found that in biology departments across 40 prominent, public research universities, Black/African American scientists held only 0.7% of tenure-track positions. Research also shows Black/African American scientists receive less NIH funding, proportionally, than their white counterparts in large part to underfunded health disparities research (Hoppe et al., 2019)

Efforts to understand barriers to inclusion and advancement in biomedicine are substantive but limited. Much of the research is based on surveys and cross-sectional qualitative research. Through annual interviews, we have collected data that is critical for understanding how racism, sexism, and other forms of differential treatment operate in the biomedical sciences and hinder the advancement and contributions of minoritized scientists.

PhD training in biomedicine is a long and individualized undertaking. Over time, trainees make critical decisions about graduate institutions, labs and mentors, research projects, and careers. Many minoritized scientists find these decisions challenging because social support and mentorship vary widely across and within institutions, especially where minoritized students do not see peers and faculty who share their identities. The insights to systematically understand minoritized scientists’ experiences during training are elusive, but retaining their talent relies on this knowledge.

3. The National Longitudinal Study of Young Life Scientists

The National Longitudinal Study of Young Life Scientists (NLSYLS) began in 2008 with funding from the National Institutes of Health (NIH). Our goal is to understand career decision-making among a diverse cohort of biomedical scientists. A primary focus is on interest and intentions in academic research careers, where minoritized scientists are least represented.

Between 2008 and 2011, we enrolled 265 beginning PhD students in biomedicine from 75 colleges and universities across the continental US and Puerto Rico. Approximately one quarter were enrolled as undergraduate juniors and seniors or as participants in a postbaccalaureate research Interviews collect biographical and real-time information about trainees, including their identification with science and disciplines; scientific and personal experiences; career decision-making; and perceptions of how social identities and personal priorities affect experiences. At each interview, researchers ask participants to describe where they see themselves in five to ten years professionally and personally, and to share perceptions, both positive and challenging, about career field of interest. These question streams make time explicit by prompting participants and researchers to reflect on expectancy and anticipation and explore change and continuity over time (Henwood & Shirani, 2023). Because the research is longitudinal, interviewers’ work becomes more intensive over time as prior transcripts and cumulative data are reviewed in advance of each year’s interview cycle. Interviews last one hour on average and are recorded, transcribed, and checked for accuracy program. We continue to interview 94 who are pursuing or planning to pursue academic research careers. Participants have exited the study through voluntary discontinuation; attrition from graduate school; and differentiation into careers outside of research science.

We recruited participants from universities after establishing agreements with programs, including undergraduate research opportunity programs, Postbaccalaureate Research Education Programs sponsored by NIH, and biomedical PhD programs. Once agreements were reviewed by institutional review boards, program leaders emailed the study recruitment announcements. Our study is approved by the Northwestern University Institutional Review Board as study number STU00017678.

Interviewers went to each campus for initial in-person interviews close to the start of the fall term for rising college juniors or the start of a postbaccalaureate or PhD program. The next year the same interviewers returned for a second in-person interview. Subsequent interviews have been conducted by phone. Of five original interviewers, two left the project in 2011 and 2012, when Christine took over their interviews.

We developed a universal codebook designed to organize interview data into buckets corresponding to themes from the interview guides. We developed sub-coding architectures tailored to projects focused on subsets of the population and for developing case reports of individuals (Remich et al., 2016; Wood et al., 2016; Wood et al., 2020). NVivo Qualitative Data Analysis Software is used for coding.

4. Researcher Positionality

The authors are professional researchers with postgraduate degrees who share an interest in improving diversity and inclusion in biomedicine and in science education more broadly. Our research team is interdisciplinary, with expertise in psychology; institutional efforts for diversity, equity, and inclusion; biomedicine; sociology; public health; education; and anthropology. We are socially diverse in terms of race/ethnicity, gender and sexual identities, parental education, and methodological training. Our reflections on positionality show how our identities and experiences inform our research.

Christine has been with the research team and longitudinal study for ten years. She writes, “I am white and a member of the LGBTQ+ community. I am a first-generation college graduate from a working-class family; my adoptive parents received no education beyond high school. After attending a private historically women’s college on scholarships, I earned a PhD in sociology and pursued a career in medical social sciences to study diversity and inclusion in biomedicine. Despite my intersectional identities, I have learned a great deal about the entrenched inequalities impacting participants in our studies.”

Rick is the principal investigator (PI). He writes, “I am a white male who grew up during the Civil Rights and Vietnam War eras, which shaped my beliefs in social justice and equity. I bring an insider’s view of biomedical research through a career-long immersion in laboratory research and research training, particularly focused on diversity, equity, and inclusion. In mid-career, through collaborations and self-learning, I re-created my research focus to use tools and knowledge of the social sciences to bring deeper attention to the barriers faced by minoritized scientists.”

Ida brings expertise in clinical-community psychology and public health. She writes, “I am a white passing, bi-racial woman, raised in a majority Latinx community, mostly by a single mother who did not attend a four-year college, although I have older siblings with graduate degrees. My research is anchored within the framework of structural violence, the idea that institutions and social organizations systemically harm certain groups of people, not necessarily through direct acts of violence, but by using social and political structures to negatively impact the morbidity and mortality of those from non-dominant groups (e.g., BIPOC and SGM).”

Remi joined our team as a data manager responsible for ensuring the quality of transcripts and was soon appointed as a research associate. Her experiences with anthropological fieldwork add value to our analyses. She writes, “I am a white, transgender woman and a part of queer communities. I am especially attuned to subtext about an individual’s narrative when refracted through the lenses of gender and sexuality. I grew up in a low-socioeconomic status family, which sensitized me to topics around income, generational poverty, and the barriers individuals face in academia. I read literature and learn from communities’ engagement to sensitize myself to the experiences of biomedical scientists who have been racially and/or ethnically minoritized.”

Robin has been with our team since the beginning of our longitudinal studies. In her role as a research associate, she has conducted interviews for more than a decade. She describes her experiences, “Over time as an education professional, I became aware of my position and privileges as a white, straight, middle-class woman with college-educated parents within a system that marginalizes historically underrepresented students. I joined the team as a novice researcher, but with a desire to examine how students navigate educational structures that alienate some and welcome others. My experience as an academic advisor for first-generation college goers at a community college was formative in my understanding of educational contexts, privilege, and awareness of how I present myself to students.”

Anne, a qualitative researcher with data management expertise, has maintained our large volume of interview data for more than seven years. She writes, “I have conducted fieldwork with educators struggling to access resources that promote equitable learning opportunities and I strive to see minoritized people’s experiences within that milieu. As a white cisgender person, I recognize that well-intentioned inquiry and shared challenges are not enough to make those experiences fully visible to me.”

Team members have dedicated their professional lives to understanding and combating systemic inequalities which profoundly impact our participants’ (and our own) experiences. Our dedication to diversity and inclusion has increased in recent years, with the worsening structural, physical, and symbolic violence inflicted on BIPOC and other minoritized communities. Over years of research, we have witnessed how changing contexts within science, higher education, and society have impacted study participants, ourselves, and our communities.

5. Case Studies to Highlight the Value of LQR

Here we discuss three case studies from our research, all are minoritized individuals who completed their PhDs and at least two years of postdoctoral training. Their career outcomes vary, and all have provided a depth of information about their trajectories and perspectives on research science. They have shared information about how their identities – social, professional, and personal – have been impacted by educational and social environments. We include these case studies to show how LQR was critical to understanding the trajectories of each and factors impacting change and stability in their career intentions and commitments in science.

5.1. Nathan: Following an Interviewee’s Lead

Nathan is a self-identified Black, gay man from a low-income family who completed his undergraduate degree at a private, predominantly white institution (PWI). He identified a strong interest in science in high school and participated in research at his undergraduate institution and at two summer experiences. He applied and was accepted to several PhD programs during his year in a postbaccalaureate research program. He elected to attend graduate school at a top-tier, private research university based on his perception that the faculty were non-egotistical, and science focused.

At an early training stage, Nathan expressed a “lifelong goal” to pursue a research question of particular concern to SGMs. He was also clear in his goal to become a tenure track faculty member. He said in his first interview,

What’s most attractive about [an academic position i. After his postdoc, he pursued a career outside of academia. The development of his realizations also displays the ways in which scientific training can obscure the degree to which there is support across training, professionalization, and career attainment. Oftentimes, this reality is only revealed slowly and over time. s] the level of control that you have over what you do. I can ask my own questions if I can get good funding for them. I can do my own science.

Nathan decided to join a lab not closely aligned with his specific scientific questions and more based on the expectation that he would find a supportive PI. He believed this PI and small lab would provide close attention and allow freedom to choose projects. In his third interview, he said,

That [topic] wasn’t something I thought I would get into. What got me was [my mentor] was working with [cells] and I’ve been working with [the same cells]. I find them fascinating. When I met with [my PI], she was full of energy, [and] focused on research. She was light-hearted and understanding and approachable. I liked that.

Nathan’s goal was to go back to his initial research interest. In his third year of doctoral training, he expected to switch to this area for his postdoc.

By the end of Nathan’s PhD, he moved away from his initial interests because he believed the field was saturated. In his fifth interview, he said,

I’d say [I’m] headstrong in terms of trying to get back into that. But I don’t even think I want to get back into [it]. There are so many people working on it. I want to go into something [where] I can have a greater impact, something emerging.

Nathan decided to pursue “emerging” diseases because he believed there was more opportunity to make his mark as a scientist.

Nathan was successful in many respects. He passed his courses and comprehensive exams with ease; defended his dissertation within four years; and authored multiple publications. Throughout graduate school, Nathan maintained a belief that science operated as a meritocracy, where he would be judged on the quality of his science and not on factors like race or social class. He resisted associations with support groups for minoritized students and had few opportunities to attend conferences. He said in his fourth interview,

I found that in these [high caliber] institutions, they just want the best and it doesn’t matter what you look like. It doesn’t matter what you sound like. It just matters about what’s coming from your brain, and I value that.

Nathan’s limited network connections and mentors did not offer resources or guidance to support his career development. As a result, he lacked critical information to best position himself for an academic career. Nathan received multiple postdoctoral offers, but he chose to stay in his dissertation lab and explained that his doctoral mentor and an administrator told him he could eventually obtain a faculty position there. Nathan also stayed in his graduate lab because he felt his PI needed him to continue pushing the research forward. At the start of his postdoc, he said,

I wanted to stay for the interest of getting another paper and being a more attractive candidate for a postdoc that I eventually would get in my long-term field of interest. It is also in her interest to keep me on, because [the PI] doesn’t have anybody else and I was already good at what I was doing.

There is an expectation in biomedicine that graduates leave their doctoral lab and work in a new setting for postdoctoral training. Two years into his postdoc, Nathan was increasingly aware of the professional consequences of remaining in his doctoral lab. He had no plans to pursue a different postdoc and regretted not receiving more accurate advice about choosing a postdoc. In his tenth interview, he said,

A part of me [regrets my postdoc choice]. A part of me wishes there was somebody saying ‘Nathan, if you want to stay in academia, you will be judged from a completely different stance if you go to another institution or at least a different lab.’

Nathan’s narrative of science as a meritocracy shifted as he became aware how his ideas, publications, awards, and grants were not positioning him for faculty jobs. He expressed complex feelings about the conflict between meritocratic principles and the undue expectations of minoritized scientists. He said during his postdoc,

I think about how many Black people really do become professors in the biomedical sciences and just how seriously it is taken. There are so many initiatives to get minorities into science. As you go upwards, I feel there’s less support…You want me to stay, you want me to succeed, but do you really want me to become a professor? Are you really going to respect the questions I ask? Are you really going to respect the pursuit of knowledge that I deem worthy?

In this remarkable statement, Nathan reflected on the complexity of meritocratic principles and how his perspective shifted over time to recognizing the importance of support, advocacy, and navigating a system with tacit rules and norms. His comments reflect his realization that training programs for minoritized scientists are useful, but less available at later stages of training, and thus inhibit the progression of minoritized PhDs into faculty careers. Nathan found the lack of support and respect for minoritized scientists disheartening

LQR allowed us to follow Nathan’s views on the concept of meritocracy in science, which was not part of our interview guide. Following the theme over time revealed how Nathan’s attachment to academic science eroded as poor support, inadequate mentorship, and lack of career development inhibited his prospects. His decisions for graduate school, PhD lab, and postdoctoral training were driven by a limited mentoring network and advising that ran counter to biomedical training norms and distanced him from his original research interests. Late in his trajectory, he reflected on race and the treatment of Black scientists as a major flaw in biomedical training. Nathan rarely discussed his gay identity or its intersection with Black identity, nor did he describe adversity in science based on his sexual identity. Nathan’s relationship with his PI and avoidance of support tailored to Black scientists were essential to understanding the outcome of his story.

5.2. Candace: Probing for Change over Time

Candace is a self-identified Black woman and first-generation college graduate who found her passion for biomedical research through a program at her undergraduate institution. This program included coursework, labs, and a journal club, but not exposure to developing and running a research project. To fill this gap, she planned her own summer research experience. In her first interview, she spoke about her research interest.

With research, it’s kind of like a puzzle and you just unlock the secret. Even though it’s tedious and takes forever, I like being there and trying to unlock all those different secrets and seeing how we can manipulate something… [it’s about] seeing how you can manipulate bacteria to treat people in the future.

Candace applied to graduate school to gain experience with research. During her recruitment interviews, faculty interviewers gave her positive feedback for her ability to think through research projects, ask relevant questions, and suggest new directions. She reported,

I told the interviewer that I didn’t have much research experience. So, he put me on the spot and asked me questions; he asked me to [design] a research project and wanted to see where I would go with it. I [told him] my ideas. And he’s like, ‘That’s a great way to think of it. You did better than 95% of the people who come in here.’

During her first year in graduate school, rotating in four labs confirmed that research was the right professional path and that she should continue towards a PhD.

While lab rotations confirmed how scientific research was her calling, she felt isolated because she was one of only a few Black students in her program. Isolation impacted Candace’s sense of belonging and contributed to what she identified as “imposter syndrome.” She discussed these experiences with friends she made through the Black Graduate Student Association.

During PhD training, Candace actively explored career options. While she initially considered becoming an academic research scientist, she shifted away from this goal after experiencing the work culture of academic science. Specifically, she observed how much time faculty spend on grant writing as opposed to bench research. In her fifth interview, she said,

The overarching thing that made [an academic research career] less appealing for me is that funding is going to be completely dependent on grants. When I was going in, I didn’t have [much of an idea] of what academia entailed. I think it’s been great that I’ve learned all of this.

The ongoing collaboration between Candace and her interviewer allowed us to see gradual shifts in her career intentions. Early interviews coupled with later stage interviews revealed a narrative about perspective shifts and the reformulation of goals.

As Candace became less interested in becoming an academic PI, she continued to explore career options. She learned about science communication and writing after completing an Individual Development Plan, a career development tool for biomedical students. Initially, Candace explored science communication and actively pursued information and exposure to this field by attending a professional conference. There she observed for the first time how perspectives as a Black woman were needed. She reported in her seventh interview,

[The conference] had forums where they showcased some of the minority women [in science writing]. It was nice to see how my voice was needed in the field… [The conference] helped me think about how I will convey certain topics to people [and keep] my experience with ethnicity and gender in mind. I’m interested in [African American scientists]. It came to me [after hearing racist remarks from politicians about Black academics that] …it would be nice to show that seeing a successful Black person in science is not an exception to the rule.

Realizing her voice is needed in science writing opened space in annual interviews to explore her views on what perspectives are valued in academia.

Candace’s perspectives on research science continued to evolve and became even more nuanced at the end of her PhD. Her interviewer veered from the question guide to probe on themes of meritocracy in science after hearing about this from other respondents. In response to a direct question about her views on meritocracy in science, Candace replied,

[Meritocracy is] something [many people value] …[But] it seems like an excuse. I think [we all] gravitate towards people we feel comfortable with or have things in common with. Considering how [academia is] a male-dominated field, and you have males in charge of hiring…Who are you more likely to invite for a drink to have guy-talk [with]? A guy. I think that infiltrates all professions.

Candace’s reflections on meritocracy are salient in comparison with others in our study. While Nathan gradually shifted away from the perception that academic science is a pure meritocracy, Candace was straightforward in expressing her view that meritocracy is an ideology steeped in bias. She pushed forward with a career she felt was a better fit for her than research science, while Nathan’s realization came too late for him to successfully pursue an academic career. Nathan and Candace were interviewed by the same team member, and the comparison between the two participants reflects our interviewer’s attention to the concept of meritocracy in science as an emerging theme.

The collaborative work between Candace and her interviewer unraveled a story that deepened over time. Our interviewer tracked Candace’s professional development activities and followed up on those in subsequent interviews. Candace’s case study is especially important in comparative context, as her story reveals a particular experience of how perspective shifts can lead to positive and active decisions as opposed to the frustration and disappointment Nathan expressed. The ability to compare change and consistency across individuals is a major benefit of LQR.

5.3. Courtney: Understanding Consistency, Change, and New Information

Courtney is a self-identified Latinx woman who enrolled in our study while completing a research program for recent college graduates. She first realized her interest in biochemistry during college while participating in a summer research experience at an academic medical center. Courtney found immense value in the research experience because her mentor “believed in my talent” and supported her development. Back at her small, undergraduate PWI after the summer, she felt more confident and noticed the institution at her summer program was more diverse than her college.

Courtney returned to the same institution for a postbaccalaureate research program to prepare for PhD training as she did not feel ready for graduate school immediately after college. In her first interview, she relayed a mix of confidence and doubt about enrolling in a PhD program.

At the beginning of [my senior year of college] I didn’t feel confident. [Now] I’m ready to go. I’ve always doubted [whether] I could be a great researcher because I don’t know the facts and the details step-by-step.

Courtney applied to graduate school during the postbaccalaureate program and earned admission to six schools. Based on support and familiarity she experienced during her research experiences, she selected the same institution and lab where she completed both research programs.

Courtney’s first two years of graduate school were challenging. She struggled with the results of her experiments and learned her mentor, whom she had worked with for a long time and found supportive, might be leaving his position. She passed her qualifying exams “conditionally” and was told she needed to improve her writing and knowledge base.

The most pivotal event of Courtney’s graduate career was changing labs in her third year. Her original mentor closed his lab due to lack of funding. She found a new lab with an appealing project. Her new mentor discouraged collaborative work, gave minimal feedback, and was adamant that she would dedicate her time only to her dissertation. Her mentor’s instructions contradicted departmental guidelines that encouraged collaborations to finish the PhD in a timely manner.

The lab transition was hard on Courtney. She questioned her skillset when she struggled with her project. She assumed the new project would be straightforward but found the work of the previous graduate student to be flawed and the mice that took time to generate were not usable. She faced social climate issues in her lab which she attributed to gender bias. She reported her PI used “sarcastic” and “offensive” language, which she said disturbed her and other women in the lab.

Courtney eventually recovered her mice and finished her research, but she took a year longer to graduate than expected. Her sense of “feeling behind” decreased her confidence. She disclosed for the first time, late in her PhD, that she had experienced stress and anxiety throughout graduate school and had sought treatment. This disclosure was significant, as she had not discussed her mental health previously.

After her PhD, Courtney remained in her dissertation lab for a short postdoctoral phase. In a post-PhD interview, she disclosed she had developed a chronic health problem, which limited the time she could spend in lab. She described her role in the lab as evolving into a “lab manager.” Her relationship with her PI improved, but she found his mentorship to be insufficient.

He respects my input as a scientist. He is very understanding of the way I do things. We’ve developed a great way of talking where I can be honest, and he won’t take offense and we can make changes. As a mentor, I would say he’s still lacking, but on other levels we’ve become very comfortable with one another.

A couple of years after graduating, Courtney found and accepted a postdoctoral fellowship in a different lab at the same institution. Part of her decision to stay at the institution was personal; she had a partner who was a critical part of her support system. Her partner was also a person of color with experience in science; Courtney could confide in him about her experiences. During the postdoc, she disclosed she had entered “trauma therapy” to understand “things that hold me back from being the scientist I want to be.” Mental and physical health became a recurring theme, but only later in her training.

Courtney’s career intentions changed across interviews. She began graduate school with a goal of becoming a “professor” and in subsequent years listed clinical research, nursing, government, genetic counseling, and college teaching as interests. Often, Courtney reflected on her lack of belief that she could produce her own projects or develop a research program, noting, “I’m more comfortable going along with other people’s ideas.” Her lack of confidence and career uncertainty may have been mitigated with better mentorship, but her realizations about her work style and role preference were important.

Despite Courtney’s scientific and personal struggles, her overall outlook during her postdoc was optimistic. In a post-PhD interview she said,

I’m optimistic that if I survived the PhD, I [can] survive anything. It was a rough go. I am very unclear of [my] path right now, but I know that if I stay healthy and keep with the same work ethic that I’ve always had, things should work out for me.

Courtney’s story is impossible to understand without comparing change and consistency over time, an analytic lens specific to LQR. She was consistent in not attributing her PI’s mistreatment to racial/ethnic discrimination, and only occasionally to gender and personality differences. She was also consistent in seeking the emotional support of her romantic partner. She was even consistent with changing her mind – her career intentions and identification with science wavered each year. It was her discussion of mental health challenges in later interviews that were most revealing, leading Courtney (and us) to recontextualize her experiences with this added information. The continuity of the interview process and long-term collaboration between Courtney and her interviewer were essential to unraveling her story and allowing for late-stage disclosure.

These case studies demonstrate how annual interviews over many years allowed us to analyze change and stability among minoritized scientists navigating a complex and unequal field. They have also revealed insights into the varied experiences of participants holding multiple, minoritized identities of race/ethnicity, socioeconomic background, mental and physical health status, and sexual identity. Returning to Saldaña’s concept of time as data (2003), we structured our research around the training cycle of biomedical scientists but learned things about our participants that were occurring on separate timelines.

6. Discussion

Time is a structuring element within most social domains. LQR has a unique ability to show how individuals’ experiences unfold relative to temporal norms specific to a social field. Following scientists over a generation revealed how individual experiences took shape in the context of timelines and milestones in PhD training and national and institutional efforts to foster diversity and inclusion in science. Annual interviews yielded great insight into our participants’ trajectories. Among our minoritized participants, especially, we have learned how institutional climate, mentorship, and information availability facilitated and inhibited progress toward scientific and career goals. The experiences impacting critical decisions and career success depend on what occurs in local contexts, where the impacts of racism, sexism, and other prejudices are felt viscerally by individuals.

Using LQR helped to unfold complex and deeply personal information in ways never anticipated. For example, Courtney’s disclosure of mental health struggles was revelatory; she had not mentioned having anxiety in prior interviews, despite her negative experiences in graduate school. Candace redefined her longstanding career goals after seeing how her voice as a Black woman would be valued in science writing. Across our population, other participants have relayed distress based on racial stereotyping, sexism, and poor mentorship, with varied impacts on their career choices. In other instances, we have been heartened to learn about positive mentoring and career support; a key aim of our research is to understand the factors promoting persistence and career development. We credit LQR with our ability to understand complex processes and decision-making in scientific training.

LQR relies on robust interview data to ensure comparability across timepoints, within and across cases. For members of groups historically denied access to higher education, a long-term view is critical for understanding how social structures, identities, and relationships shape experiences and persistence. Allowing for trust-building and disclosure over time counteracts the “epistemic violence” that has impacted minoritized populations, where lived experiences are seldom considered in what counts as valid knowledge about mobility and change (Teo, 2010). Our hope is to spark interest in LQR among psychology researchers concerned with inclusivity in research and interventions. The power of LQR is in analyzing dynamic processes that occur over time. Time is an especially critical component for promoting more inclusive institutions and facilitating equity, as these processes are slow and uncertain.

6.1. Resources and Feasibility

LQR is a longer-term endeavor than most psychological research although it is not limited to the length and scale of our research. Resources in the form of funding, person-power, and dedicated research time may pose challenges for sustaining LQR projects. Funding lapses and personnel changes impact the continuity of the research and may affect how data are interpreted and how much time researchers dedicate to a project.

We are fortunate to have had NIH and university support to conduct our research for many years. We recognize that most researchers do not have that level of financial and organizational support, nor do most research questions require it. We have developed strategies for training new members, managing data, and maintaining a shared purpose; these strategies have been critical to continue our research. Here, we discuss efforts to maintain consistency in interviews and data analysis. We will also discuss how to scale LQR for sample size, cost, time limitations, and research team composition.

Researchers working on the same project for more than a decade will experience interruptions and challenges to continuity, including staff turnover and the need to manage ever-increasing volumes of textual data. Turnover among interviewers and research staff can have varied impacts on continuity. Turnover may impact participants’ relationships and attachment to the study. Our participants do not continue to participate in our study just because we offer a small incentive each year; they do so because they remain engaged. To promote continuity and retain participants, new interviewers assure participants they have read all their interviews and consulted with the previous interviewer. Similarly, turnover can affect data analysis and collective memory within a team. To preserve continuity and sensitize new team members to our analytic process, we maintain a detailed codebook that provides a common language and touchstone. New research team members undergo extensive training by learning the codebook, co-coding transcripts with other team members, and establishing intercoder reliability.

Depending on a study’s scope and time requirements, LQR can generate volumes of data that need to be systematized for record keeping, participant confidentiality, accessibility, and retrieval. Investing in staff who specialize in data management is helpful for implementing consistent workflows. To manipulate a complex data set, software tools such as NVivo, SPSS, and Microsoft Access are often necessary. Inexpensive qualitative analysis software packages such as Dedoose have become increasingly popular. Dedoose is secure and accessible on the web, which removes the need to maintain software on a server or shared drive and allows for easy collaboration with virtual partners. Researchers also use tools like Microsoft Excel to organize and even analyze text data.

In LQR, more is not necessarily better. A strategy for resource-limited groups is to use small samples and emphasize internal validity over representativeness and reproducibility. Researchers in smaller and less resourced contexts can conduct LQR by tailoring studies to existing problems and introducing new settings or contexts. For example, researchers studying the long-term health outcomes of people with major depression may draw on questions posed by existing research but conduct the study in a different city or within a different demographic. Smaller-scale designs, in terms of subject population and study length, are often more appropriate than sprawling samples and allow for higher internal validity. A study about how first-generation college students navigate life at a university may not need to extend beyond four or five years and could still reveal deep insights about the study participants.

Undergraduate and graduate research assistants can provide valuable and high-quality contributions to longitudinal research teams at teaching intensive institutions. Both undergraduate and graduate students can learn many, if not all, of the skills paid research staff perform at larger institutions. These skills include managing data, co-developing interview protocols, conducting interviews, and analyzing data. These types of hands-on training experiences can even bolster the missions of teaching-intensive colleges and universities.

Finally, collaborations with researchers in other departments or universities are helpful for working with larger sample sizes, obtaining funding, ensuring personnel support, and tapping into specific kinds of expertise. Cross-national teamwork for health disparities research has become increasingly popular, as has the adoption of qualitative methods in this area (Milford et al., 2017). Researchers involved in cross-team collaborations have similarly argued for the use of standardized codebooks compatible across local contexts. Although comparative research presents a unique need for cross-team collaboration, the insights about developing a balance between general codebooks and local subcodes are useful.

7. Conclusions

Our goals for this paper were to demonstrate the usefulness, processes, and feasibility of LQR designs for studying social contexts where temporality is a structuring element and inclusivity is a problem. We have found LQR to be indispensable for understanding the training experiences of early-career biomedical scientists. LQR allows researchers a unique ability to compare the experiences of individuals over time against the backdrop of time-dependent norms in a social field. For research studies involving minoritized participants, experiences with inclusivity and barriers to access in certain social settings are often time dependent. Among populations historically excluded from social institutions like higher education and professional fields, there are no guidebooks for how to navigate exclusionary environments. Experiences and perspectives are likely to shift based on encounters in local settings with varied practices and attitudes towards inclusion.

Table 1.

NLSYLS Population

	Entered PhD program	Completed PhD degree	Did not complete PhD degree	Unknown: lost to follow-up
All	265	204	41	20
Gender
Female	175	129	29	17
Male	90	75	12	3
Representativeness
Underrepresented in biomedical research (UR)*	86	57	21	8
Well-represented in biomedical research (WR)*	179	147	20	12
Ethnicity
Latinx**	42	27	12	3
Race
American Indian or Alaska Native	5	2	2	1
Asian or Asian American	26	21	3	2
Black or African American	40	29	8	3
Latinx, selected white	21	15	4	2
Latinx, selected no race	11	8	2	1
Native Hawaiian or Other Pacific Islander	0	0	0	0
White	149	124	15	10
More than one race - well represented***	5	3	2	0
More than one race - underrepresented****	8	2	5	1
Family immigration
First generation	35	26	6	3
Second generation	54	35	15	4
Most Advanced Degree Obtained by Parent or Guardian
High school graduate or GED or less than high school	72	50	13	9
Bachelor’s degree	59	43	11	5
Graduate or professional degree	134	111	17	6

^*UR is an NIH designation applied to the following racial and ethnic groups: Blacks or African Americans, Hispanics or Latinos, American Indians or Alaska Natives, Native Hawaiians, and other Pacific Islanders.

^**NIH uses the term “Hispanic or Latino”

^***no race or ethnicity identified fits NIH’s UR categorization

^****at least one race or ethnicity identified fits NIH’s UR categorization

1. Abbreviations:

LQR

Longitudinal Qualitative Research

NIH

National Institutes of Health

PI

Principal Investigator

PWI

predominantly white institution