Matthew Bahnson
Tabe Ako Abane- 1Department of Psychology, University of Cincinnati, Cincinnati, OH, United States
- 2School of Engineering Education, Purdue University, West Layfette, IN, United States
Introduction: Several factors shape doctoral students’ decisions to leave their programs before completion. Among these, the quality of the advising plays a critical role. Yet, there remains limited understanding of how advisor relationships influence consequential decisions, such as early departure and lab change considerations in doctoral engineering students. This paper investigates the influence of advisor relationships on early departures and lab change considerations in doctoral engineering students.
Methods: Engineering doctoral students from 26 top-ranked universities in the United States and 17 doctoral engineering disciplines responded to an online survey on departure considerations, advisor relationships, and lab change actions. In our sample (n = 269), fewer women (n = 108) participated compared to men (n = 121), with gender non-conforming individuals comprising a smaller proportion (n = 12), and 28 participants not self-identifying a gender. Linear regression was used to measure the association between advisor relationships and departure considerations, both with and without a master’s degree. Mediation tests were performed to assess the mediating effect of student’s ability to assess their progress to degree (progress assessment) on this relationship.
Results: Our results indicate that advisor relationships explained 12% of the variance in departure without a degree (R2 = 0.12, F (1, 267) = 36.85, p < 0.001) and with a master’s degree (R2 = 0.12, F (1, 267) = 35.66, p < 0.001). Progress assessment was statistically associated as a partial mediator of this relationship, with significant indirect effects (β = −0.05, p < 0.05) for departure with or without a master.
Discussion: Low advisor relationship was associated with self-reported engagement in preparatory steps for early departure and research lab change considerations among doctoral engineering students. Conversely, negative advisor relationships are associated with increased self-reported engagement in steps leading to lab changes or departure considerations.
1 Introduction
Doctoral students leaving before completing their engineering doctorate has continued as an urgent topic in engineering education. Student decisions to depart without a doctorate may not reflect academic performance or skill acquisition. Rather, early departure may signal deeper concerns about doctoral engineering student attrition. National statistics indicate that approximately 40% of doctoral students do not complete their programs within 10 years (Council of Graduate Schools, 2008; Academies, 2018; Sowell et al., 2025). More recently, nearly 70% of engineering doctoral students have within the past month, seriously considered leaving without completing their degree (Bahnson and Berdanier, 2023), underscoring the ongoing challenges surrounding early departure from engineering doctoral programs.
Although multiple factors interact to shape departure considerations, few are as influential, or as fragile, as the advisor relationship given the possibilities of misunderstandings, unequal power, and reliance on funding (Barnes et al., 2010; Barnes et al., 2012; Barnes and Austin, 2009; Berdanier et al., n.d.; Brawner et al., n.d.). As primary mentors in a doctoral student’s journey, advisors provide essential guidance to help students navigate their discipline, internalize professional norms, develop as independent researchers, manage complex academic requirements, and receive both emotional and professional support (Lovitts, 2001; Murphy et al., 2007; Zhao et al., 2007). Doctoral funding tied to research projects supported by the advisor’s grants complicates the academic relationship with a financial dependency (Berdanier et al., n.d.). The financial connection positions faculty to serve simultaneously as supervisors, academic advisors, and mentors.
Given this outsized role, one might expect an extensive research base devoted to advising in engineering; yet the scholarship remains surprisingly thin. Although the literature is growing, only a modest number of studies have probed the advisor–advisee dynamic in depth. For instance, Burt et al. (2021) argued for stronger advising, concluding that when faculty incorporate greater elements of care into their advising, it leads to more meaningful advising experiences and stronger advisor–advisee relationships. Zhao et al. (2007) explored factors affecting students’ satisfaction with the advising relationship, drawing data from doctoral students in the United States across 27 universities and 11 disciplines, and found that disciplinary differences in both choice criteria and advisor behavior are more robust predictors of satisfaction than individual characteristics. For example, in chemical education, communication to resolve conflict between advisee and advisor can be influenced by personality perceptions, existing relationship norms, and the power imbalance between student and advisor (Qu and Harshman, 2022). Further, graduate handbooks may not provide the best guidance to advisor or advisee on reaching the desired outcomes of doctoral study (Donkor and Harshman, 2023). Berdanier et al. (n.d.) connected declining satisfaction with one’s advisor to thoughts of leaving a doctoral program. These studies underscore the importance of advisor relationships in shaping doctoral experiences. Yet, understanding remains limited regarding how tensions within advisor–advisee relationships contribute to consequential decisions, such as departure and lab change considerations.
The analyses reported here extend existing knowledge on advisor relationships by examining their influence on doctoral engineering students’ early departure and research lab change considerations. Specifically, we explore how advisor relationships relate to departure considerations, whether students’ perceptions of academic progress mediate this relationship, and how advisor relationships may also be linked to lab change consideration actions.
2 Background and theoretical framework
A larger body of research has examined advisor relationships beyond engineering, departure considerations, lab changes, and degree progress in doctoral education. Each line of work has generated important contributions that form the foundation of what we now understand about doctoral student experiences, research group and peers, advisor relationship, and funding and cost structures which strongly influence students’ degree progress and retention. However, even when these constructs appear within the same study, the literature has largely examined them as separate or loosely connected areas. This approach has advanced our knowledge of each construct on its own, but it also means we know less about how these factors interact to influence students’ decisions to persist, switch labs, or leave their programs. Our study bridges that gap. We synthesize literature on advisor relationships, lab change, and departure considerations to develop a conceptual framework that captures how these constructs jointly shape students’ experiences. We then draw on empirical data related to advisor relationships, departure considerations, and lab change to further illuminate how advisor relationships influence early departure and lab-switch considerations in engineering doctoral programs.
2.1 Theoretical framework
To investigate how advisor relationships influence early departure and research lab change considerations among doctoral engineering students, our study implements the Graduate Attrition Decisions (GrAD) model (Berdanier et al., 2020). Although originally developed to explain attrition, the GrAD model is well suited to investigating laboratory switching due to the similarity in departure from a program and departure from a lab influences. Further, both types of departure decisions should be seen as a continuum of decision-making rather than a binary or one-time decision. The GrAD model provides a structured approach to understand how various factors influencing graduate students’ decisions are interrelated, enriching the discourse surrounding the retention of engineering students. Berdanier’s formulation of the GrAD model was derived from an extensive qualitative analysis of graduate student feedback collected from social media platforms. The GrAD model identifies six interrelated themes (Figure 1), four of which have been explored in engineering and higher education scholarship concerning graduate attrition: advisor relationships, support networks, and cost (Berdanier et al., 2020). Among these, advisor relationships served as a central axis around which many of the other themes revolved. Advisors shape doctoral students’ experiences on multiple fronts (Zhao et al., 2007; Berdanier et al., 2020; Schlosser et al., 2003). Through the socialization they facilitate, advisors can strengthen or erode students’ academic and social support networks (Hocker et al., 2019; Weidman et al., 2001). Similarly, advisor dynamics can shape a student’s experience of cost, not just in financial terms, but also in emotional, research, and professional development aspects, as well as opportunity costs (Brawner et al., n.d.). The GrAD model explains how the advisor relationship intersects with and amplifies other naturally occurring factors, shaping graduate students’ experiences of stress, persistence, and decision-making within the broader doctoral ecosystem. Building upon the GrAD model, we seek to understand how the advisor theme of graduate attrition contributes to departure or lab change considerations while assessing the interaction of how students feel about assessing their progress. Figure 1 illustrates the GrAD model and emphasizes the intersection of advisor relations with student progress evaluation, departure decisions, and lab change choices.
Figure 1. GrAD model primary themes and sub-themes emergent of graduate engineering attrition (Qu and Harshman, 2022) with added notation of themes of attrition, departure and lab change considerations, and progress assessment.
2.2 Advisor relationships
Advisors serve as the central architects of doctoral success, with their multifaceted roles spanning three primary domains of influence. First, advisors support academic success by laying the foundation for degree progress and completion (Bair and Haworth, 2005) and guide students’ development throughout the program (Burt et al., 2019). Second, advisors contribute to personal growth by providing mentorship (Saddler, 2009; Artiles et al., 2023, 2025) and support socialization, helping students shape their scholarly identities (Sweitzer, 2008). Third, advisors shape the professional trajectory through the overall graduate experience (Lee, 2008; Shanachilubwa et al., 2023), facilitate professional development (Simon et al., 2015), and influence students’ future careers (Denton et al., 2025; Choudhary and Jesiek, 2015). However, advisor roles are not just faculty obligations; they are relational cues that doctoral students use to assess the quality of their relationships with their advisors. For instance, when advisors provide (or fail to provide) research guidance or psychosocial support (Sweitzer, 2008), students use these enacted roles as the basis for evaluating the quality of the relationship. One study indicated that the difficulty of research tasks intersects with the quality of the advisor relationship (Parker et al., 2019).
Scholars define advisor relationships using descriptive labels, which are based on how students describe their experiences or how researchers interpret those stories. According to McCain et al. (2024), student narratives reveal four primary relationship dynamics. Strained relationships are defined by conflict and negative emotion, whereas evolving relationships focus on growth and overcoming challenges. On the positive end, Supportive relationships provide professional support and satisfaction, while Egalitarian relationships elevate the student to a colleague, prioritizing collaboration and peer status. Distinct from student narratives, researchers rely on broad categorical labels to classify advisor relationships. They characterize problematic relationships as poor, negative, or weak, while describing supportive relationships as positive or supportive.
In some cases, these labels represent a distinction without a substantive difference. For example, Mackie and Bates (2019) argue that “poor” advisor relationships negatively influence mental health, while Barnes et al. (2010) reached a similar conclusion using the term “negative” advisor relationships. Moving beyond broad descriptors, Levecque et al. (2017) categorized advisor relationships into three distinct leadership styles: autocratic, inspiring, and laissez-faire. They found that the laissez-faire style is statistically linked to negative mental health outcomes.
In this study, we define a negative advisor relationship as one characterized by tension, conflict, or behaviors that undermine a student’s sense of support and belonging, such as dismissiveness, poor communication, or overtly critical interactions (McCain et al., 2024; Barnes et al., 2010). While similar, a poor advisor relationship, by contrast, reflects insufficiency or absence, where the advisor fails to fulfill expected roles or responsibilities, such as providing timely feedback, guidance, or resources, without necessarily displaying hostility (Mackie and Bates, 2019). While these categories are conceptually distinct in the literature, survey instruments tend to capture advisor relationship quality along a single continuous dimension. Finally, a positive advisor relationship involves constructive engagement, mutual respect, and supportive behaviors that foster student growth, well-being, and academic persistence (McCain et al., 2024; Mackie and Bates, 2019; Barnes et al., 2010; Levecque et al., 2017). These styles can be understood to reflect varying levels of autonomy, support and involvement as measured by the scale of the advisor relationship used in this study. Making these distinctions allows us to move beyond interchangeable labels and clarify the functional differences between relationships that are actively harmful, those that are inadequate, and those that are affirming and their implications for persistence and departure consideration.
2.3 Departure considerations
Departure consideration refers to the evolving process by which doctoral engineering students begin to question their continuation in the program, ranging from initial doubts and intentions to leave, to active planning and concrete steps toward withdrawal (Bahnson and Berdanier, 2023). This perspective places attrition as a gradual and ongoing process, rather than a sudden event (Bahnson and Berdanier, 2023; Lovitts, 2001; Saddler, 2009; Artiles et al., 2023). Related terms used in the literature to discuss students’ graduate departure from their programs include intention to depart, consideration to leave, departure, or attrition consideration (Weidman et al., 2001; Artiles et al., 2025; Sweitzer, 2008; Lee, 2008; Shanachilubwa et al., 2023; Simon et al., 2015). Several factors influence departure considerations, with personal and program-related challenges often serving as critical events that prompt serious considerations of leaving the doctoral program (Artiles et al., 2023; Lee, 2008; Shanachilubwa et al., 2023). Among program-related factors, poor or negative advisor relationships have been strongly linked to departure considerations, with a growing body of literature identifying them as a primary influence on the departure considerations of engineering doctoral students (Berdanier et al., n.d.; Zhao et al., 2007; Donkor and Harshman, 2023; Artiles et al., 2023; Sweitzer, 2008; Denton et al., 2025; Choudhary and Jesiek, 2015; Parker et al., 2019).
Nevertheless, students with strained advising relationships often refrain from placing full blame on their advisors. Instead, they tend to internalize these difficulties, attributing them to personal shortcomings or perceived failures to meet the inherent rigor and demands of doctoral study (Simon et al., 2015; Denton et al., 2025; Mackie and Bates, 2019). This tendency reflects a broader pattern in the literature, where students are responsible for their own persistence or attrition, even when programmatic factors play a significant role (Lovitts, 2001; Artiles et al., 2023; Barnes et al., 2010; Levecque et al., 2017). Such internalization of blame may further complicate students’ ability to accurately assess their degree progress, reinforcing uncertainty and departure considerations. However, when self-blame fails to alleviate stress, emotional exhaustion, or mental burnout (Denton et al., 2025; Golde, 2005), students reach a tipping point and begin to seriously consider leaving their programs (Simon et al., 2015; Denton et al., 2025; Mackie and Bates, 2019; Zerbe et al., 2022). However, the departure decision is rarely impulsive. The decision is often preceded by a period of deliberate reflection, during which students weigh several critical factors: the severity of breakdown in the advisor–student relationship, the availability of external support or mediation, and the degree to which their academic path aligns with long-term career goals (Bahnson and Berdanier, 2023; Shanachilubwa et al., 2023; Denton et al., 2025; Zerbe et al., 2022; Bahnson et al., 2023). While these considerations are common, the decision-making process is far from uniform. It varies widely across individuals, shaped by each student’s unique personal circumstances, academic expectations, and coping capacities (Sallai et al., 2022) and can be strongly influenced by a student’s self-assessed progress (Borrego et al., 2017; George et al., 2018; Ruud et al., 2018; Sallai et al., 2023).
2.4 Progress assessment
Progress in doctoral education rests on two pillars: completing coursework and producing original research, culminating in the dissertation (Borrego et al., 2017; George et al., 2018; Ruud et al., 2018; Sallai et al., 2023). Foundational coursework provides students with the theoretical grounding, methodological repertoire, and technical skills necessary for lab-based inquiry (Lovitts, 2005). Yet coursework alone cannot signal real progress, because doctoral study ultimately hinges on research productivity. Traditional indicators, such as GPA, rarely predict whether a student will complete the PhD (Lovitts, 2005). Rather, successful completion is more closely tied to the student’s capacity to evolve into an independent researcher (George et al., 2018; Ruud et al., 2018; Sallai et al., 2023). Advisors, therefore, play a pivotal role in this transition (Borrego et al., 2017; Bahnson et al., 2024). In this study, progress assessment is operationalized using a single self-report item capturing perceived clarity, rather than milestone completion due to the continuing research and writing time following completion of most degree milestones. They shape research direction, provide financial support, and connect students to professional networks that accelerate learning and degree completion (Borrego et al., 2017; Crede and Borrego, 2012).
In engineering programs, research is often carried out in alignment with advisors’ funded projects, offering students structured opportunities for hands-on experience and scholarly development (Borrego et al., 2017; Crede and Borrego, 2012). However, tension can emerge when advisors and students pursue divergent goals or operate with unclear expectations (Devos et al., 2016). Such misalignment can delay key milestones and lead to confusion about how progress is assessed (Sverdlik et al., 2018; Hoey, 2008). For instance, students may develop their own perceptions of progress that do not always align with those of their advisors. A healthy and constructive advisor relationship, marked by clear and collaborative communication, is particularly important to assessing research progress that is inherently context-dependent (Roy et al., 2023). When expectations are discussed openly and regularly, both students and advisors are better able to interpret milestones, assess competencies, and develop a shared understanding of academic progress (George et al., 2018; Ruud et al., 2018; Sallai et al., 2023; Bahnson et al., 2024; Zerbe et al., 2023). Positive advising relationships help bridge gaps in understanding and reduce the risks posed by mismatched research goals or ambiguous evaluation criteria (Roy et al., 2023). In such environments, students are more likely to see themselves as active collaborators, which fosters mutual trust, open dialogue, and confidence in navigating the challenges (Berdanier et al., n.d.; Ruud et al., 2018; Roy et al., 2023). However, for wide variety of reasons students still may find departure from a lab to be the best, only, or least disruptive option to persist in the doctoral endeavor.
2.5 Lab change
Attrition is not always a binary process of staying or leaving; sometimes, students switch labs as an alternative to leaving doctoral education altogether. Lab change can restore a sense of support and mitigate the risk of attrition among doctoral engineering students (Bahnson and Berdanier, 2023). In preparation for changing labs, speaking with a potential advisor is often the ‘recommended’ next step. Yet, this process requires explaining to a potential advisor the reasons for the transition, which can raise concerns about retaliation if the change is unsuccessful (Borrego et al., 2017; Crede and Borrego, 2012; McAlpine and Amundsen, 2011). Faculty members may also be reluctant to accept a student from a colleague due to the potential strain on professional relationships (Matthews, 2019). These relationships are typically well-established and may extend beyond the student’s time in the program, making faculty cautious about disrupting long-standing academic networks. Further, universities have policies on academic progress, advisor relationships, and funding that may inadvertently create hurdles for students seeking to leave or raise concerns about their experiences (Lovitts, 2001; McAlpine and Amundsen, 2011).
Therefore, doctoral students who consider switching labs often evaluate how the decision might affect their academic success, departmental relationships, the availability of a suitable new mentor, and the administrative hurdles involved including funding and cost structures (Bahnson and Berdanier, 2023; Zerbe et al., 2022). To navigate these complexities, they often take several preparatory steps. For instance, they may search for information on their own, consult with peers or social media communities (Berdanier et al., 2020), review program-specific guidelines or graduate college resources, and seek advice from program administrators (Bahnson and Berdanier, 2023; Berdanier et al., 2020). Moreover, the strategies students choose can also vary by nationality and gender. International doctoral engineering students, whose visa status is closely tied to their funding, tend to proceed more cautiously than domestic students (Gao, 2021; Ledford and Basilio, 2025). Gendered communication norms matter as well: women are more likely to use indirect channels and may feel less comfortable initiating difficult conversations with advisors or other authority figures (Wang and Houdyshell, 2021). In engineering’s male-dominated culture, this reluctance can arise from a desire to avoid confrontation or critical feedback (Holloway et al., 2020; Lovitts, 2005). While not directly tested in the analyses presented here, these dynamics can create a feedback loop in which some students feel supported and move forward with a lab change, while others hesitate because of perceived barriers or fear of retaliation.
2.6 Research questions
This research is part of a larger mixed-methods project that examines the persistence pathways of doctoral engineering students as they change research labs to continue their graduate education. The goal of this analysis is to investigate the impact of advisor relationships on student considerations of departing their program without a degree or with a master’s degree; the roll uncertainty in progress assessment in the program in departure considerations; and the association of advisor relationship with actions to change research labs. The following are the research questions for this study:
Research Question 1: How strongly does advisor relationship predict degree departure considerations?
Research Question 2: How does progress assessment statistically mediate the relationship between advisor relationship and departure considerations?
Research Question 3: How does advisor relationship predict lab change actions?
3 Materials and methods
This study reports cross-sectional survey analyses drawn from a larger mixed-method longitudinal research project aimed at better understanding engineering doctoral students’ experiences and behaviors related to changing labs. The analyses and results presented here reflect one set of exploratory analyses to contextualize departure and persistence considerations in relation to advisor relationships and progress assessment. A self-report survey administered to doctoral engineering students examines the frequency, predictors, and outcomes of lab changes and their persistence in their academic programs.
3.1 Positionality
As authors, we draw on our disparate training to investigate how advisor relationships influence doctoral engineering students’ progress assessment and departure considerations while acknowledging the importance of our personal experiences. The first author and principal investigator identifies as a White, queer man with expertise in engineering education and social psychology research. The second author identifies as a Black African graduate student with a background in engineering and education. His experience as an international graduate student, coupled with navigating lab changes, has provided him with valuable insights into the challenges faced by doctoral engineering students, particularly those who are international or from underrepresented groups. Our training from social sciences, education, engineering, and psychology provide multidisciplinary perspectives to support this research. With a balance of perspectives, we are able to look beyond individual disciplines to identify trends and themes. Our collective expertise positions us to extend the impact of our work beyond our individual disciplines. However, our lived experience has provided different views of changing labs and research advisor relationships. Indeed, power dynamics between the authors may have influenced research practice and interpretation reflecting trainee and supervisor roles under investigation in this manuscript. While not apparent in our collaboration, we are mindful of our interactions as reflecting the research topic under investigation. Simultaneously, we share common goals and a commitment to improving the educational experience of graduate engineering students.
3.2 Procedures
The 2022 edition of Engineering and Engineering Technology by the Numbers (Profiles of Engineering and Engineering Technology, 2022) from the American Society for Engineering Education (ASEE) was referenced to identify the top 50 institutions awarding engineering doctoral degrees. Invitations were sent via email to 448 engineering graduate program directors, coordinators, or department heads, requesting that they share details about the study with their doctoral students. Doctoral students voluntarily participated in the study by completing a survey hosted on the Qualtrics online platform. Participants were given the opportunity to enter a drawing for a $10 Amazon gift card, with ten recipients chosen and notified via email, representing about 4% of the participants. The authors obtained approval from the institutional review board (IRB) for all data collection procedures.
3.3 Participants
Engineering doctoral students from 26 top-ranked universities in the United States and 17 doctoral engineering disciplines responded to an online survey on departure considerations, advisor relationships, and lab change actions. In our sample (n = 269), women (n = 108) are underrepresented compared to men (n = 121) with gender non-conforming individuals comprising a smaller proportion (n = 12), and 28 participants not self-identifying a gender. Among racial and ethnic groups, White students comprised a smaller portion of the sample (n = 102), whereas Asian students are well-represented (n = 105) with some representation from of Black/African American students (n = 13), Middle Eastern or North African students (n = 19), and Hispanic, Latino/Latina/Latinx, or Spanish origin students (n = 21).
3.4 Measures
Participants answered a series of questions on departure considerations, advisor relationships, and lab change actions as part of the online survey.
Departure Considerations were measured with two items: I am considering leaving my current program without a degree; and I am considering leaving my program with a Master’s. Participants responded to each item by selecting one of the following: Strongly disagree (1), Somewhat disagree (2), Neither agree nor disagree (3), Somewhat agree (4), or Strongly disagree (5). These items were analyzed separately because they represent conceptually distinct outcomes rather than indicators of a single latent construct.
Advisor relationship was measured with nine items measuring a single factor (Bahnson et al., 2024) with a stem (My Advisor…) asking students to rate items such as values my work; is easy to approach. Participants responded to each item by selecting one of the following: Strongly disagree (1), Somewhat disagree (2), Neither agree nor disagree (3), Somewhat agree (4), or Strongly disagree (5). The mean of the nine items is used as the advisor relationship variable. The scale has strong internal reliability (Cronbach’s α = 0.95) similar to existing research (Bahnson et al., 2023). The items developed in past research represent common advisor relationship needs in engineering doctoral education (Cass et al., 2017). Although the high internal reliability may indicate some redundancy in items, it does reflect strong coherence among the indicators for advisor relationship quality.
Progress Assessment was measured with one item: I find it difficult to evaluate my degree progress. Participants responded by selecting one of the following: Strongly disagree (1), Somewhat disagree (2), Neither agree nor disagree (3), Somewhat agree (4), or Strongly disagree (5). As a single-item measure, this construct should be interpreted as indicative rather than comprehensive.
Lab Change Actions were measured with six items. Students were asked to respond Yes (1) or No (0) to the following items: Discussed changing with your current advisor; Discussed changing with a program administrator (graduate program director, department chair, or similar); Searched for program information about changing research labs; Searched for graduate college information about changing research labs; and Discussed changing with potential new advisor(s). The last item was an optional item with a write-in space: Other actions in preparation for changing research labs or universities. These items were generated based on existing qualitative research on lab change in doctoral engineering programs (Bahnson et al., 2019; Bahnson and Abane, 2025).
4 Results
Analyses were conducted with SPSS v26. Descriptive statistics, including means, standard deviations, kurtosis, skewness, and correlation were examined for normality in the study variables. Linear regression was used to determine the relationship between advisor relationship and departure considerations without and with a master’s degree. To further examine the relationship, we use mediation tests to examine the mediation effect of Progress Assessment between advisor relationship and departure considerations with bootstrapping (Figures 2a, b). The mediation analyses were conducted in SPSS PROCESS Model 4. Finally, binary logistic regression is used to assess the association between advisor relationship and engaging in investigation of lab change opportunities. Linear regression and mediation were employed consistent with prior education research treating Likert-type outcomes as approximately continuous under robust sample conditions.
Figure 2. Mediation models for advisor relationship to departure consideration without a Master’s degree (a) and with a Master’s degree (b) as mediated by self-assessed degree progress.
Table 1 presents descriptive statistics for variables related to degree progress, intentions to leave, and advisor relationships. Assessed Progress has a relatively high mean, as does Advisor Relationship, however, the skewness and kurtosis do not indicate issues proceeding with the robust analyses utilized. No correlation coefficients indicate multicollinearity. As expected, the items measuring whether or not participants had considered leaving without a degree and with a Master’s are highly correlated. Similarly, the lab change investigation activity items to measure searching for program or graduate college information about changing labs were highly correlated.
Table 1. Descriptive statistics for degree progress, intentions to leave, and advisor relationships.
4.1 Regressions
Initial analysis of the relationship between advisor relationship and departure consideration used linear regression. A significant regression was found (F (1, 267) = 36.85, p < 0.001). The R2 was 0.12 indicating that advisor relationship explained approximately 12% of the variance in departure consideration without a degree. While modest, this level of explained variance is meaningful in doctoral education research in which persistence decisions reflect multiple interacting factors. Similarly, a significant regression was found (F (1, 267) = 35.66, p < 0.001). The R2 was 0.12 indicating that advisor relationship explained approximately 12% of the variance in departure consideration with a master’s degree. Again, the modest level of explained variance represents a meaningful amount of variation given the multiple interacting factors in doctoral persistence considerations. With both linear regressions, the advisor relationship is an important predictor of departure consideration.
4.2 Mediation effects
The mediation analysis demonstrated advisor relationships strongly associated with degree progress assessment and progress assessment strongly associated with departure consideration for both departure without and with a Master’s degree. These relationships establish the importance of measuring the statistical mediation of progress assessment of the linear regression relationship between advisor relationship and departure consideration. Mediation analysis demonstrated progress assessment significantly, partially mediated the relationship between advisor relationship and departure consideration without and with a master’s degree (Table 2). The finding supported importance of a student’s ability to assess their progress in their departure considerations.
Table 2. Mediation coefficients and significance estimates for advisor relationship mediation through progress assessment to departure.
4.3 Lab change actions
Advisor relationship significantly negatively predicts student’s engagement in several common steps to changing research labs (Table 3). Doctoral engineering students who consider changing labs due to advisor relationships do not make this decision lightly; they engage in various lab change actions, as reported in Table 3. The significant negative coefficients across different actions, such as discussing lab changes with advisors, program administrators, and potential new advisors, suggest that students experiencing poor advisor relationships may hesitate to initiate conversations about lab changes with their current advisor. Moreover, the negative association between advisor relationships and discussing lab changes with program administrators highlights how negative advising experiences may discourage students from seeking institutional support. Similarly, students in strained relationships may be less likely to search for program-specific resources or graduate college information, suggesting a reluctance to engage in formal decision-making processes related to lab switching. It is also possible that institutional policies or funding constraints, independent of advisor relationships, influence students’ willingness to pursue lab changes.
Table 3. Advisor relationship on student engagement in lab change considerations.
5 Discussion
5.1 Advisor relationship
Our analysis indicates that advisor relationships are strongly associated with progress assessments and departure considerations. Mediation analysis demonstrated that progress assessment significantly and partially mediated the relationship between advisor relationships and departure considerations, both with and without a master’s degree. These results are consistent with existing scholarship, the quality of advisor relationships are strongly associated with doctoral engineering student success, satisfaction, research growth, and commitment to completing a doctoral degree (Academies, 2018; Hocker et al., 2019; Bahnson et al., 2024; Breen et al., 2024), and the characteristics defining both positive and negative advising experiences in doctoral engineering education (Barnes et al., 2010; Breen et al., 2024; Zerbe et al., 2023). Doctoral engineering students who experience negative advisor relationships may perceive their academic progress less favorably, which could increase uncertainty about degree completion. This aligns with prior research indicating that positive advisor relationships foster academic growth, self-efficacy, and retention in doctoral programs (Hocker et al., 2019).
5.2 Progress assessment
Part of the negative effect of advisor relationships was mediated through progress assessment. This mediation reflects statistical association rather than causal sequencing. Lower advisor relationship scores were associated with greater difficulty in progress assessment, which could contribute to increased departure considerations with or without a master’s degree. This may be because advisors provide research direction, financial resources, and establish support networks that are vital for effective learning and progression (Crede and Borrego, 2012). A poor advisor relationship can leave doctoral students with ambiguity, uncertainty, and a diminished sense of support and guidance. This exacerbates their difficulty in navigating the complexities of their doctoral studies and increases the difficulties in achieving critical degree milestones, and conflicts in assessing degree progress (Bahnson et al., 2024; Sverdlik et al., 2018; Hoey, 2008), which could contribute to departure considerations. Nonetheless, this difficulty can be mitigated by a positive advisor relationship. For instance, doctoral students in a supportive and positive advisor relationship often feel like collegial partners working alongside their advisors, tend to communicate more openly about difficulties, seek guidance on complex research topics, and obtain critical support essential for degree progress (Bahnson et al., 2024; Sherman et al., 2021).
5.3 Lab change actions
While some doctoral engineering students make departure considerations either with or without a master’s, others may consider changing labs as an alternative to find a more supportive environment. Reasons for doctoral students taking these actions may differ but based on findings in the literature, some factors may account for the lab change actions. For instance, doctoral students in academic environments where perceived loyalty and commitment to an advisor or research group are highly valued may worry that changing labs might harm their relationships with current advisors or negatively affect their reputation within their academic community (Zerbe et al., 2022; Crede and Borrego, 2012). Moreover, depending on the size and nature of the department, as well as how long students have been in the doctoral program, some may face increased scrutiny, disruptions to their graduation timeline, and jeopardized funding commitments (Dinsmore and Roksa, 2023). In other instances, the competitive atmosphere in academic settings, especially in engineering doctoral programs, can hinder open communication between students and advisors (Wofford and Blaney, 2021).
5.4 Theoretical implications
The importance of and significance of progress assessment demonstrates a need to include student progress assessment into the GrAD model of attrition. While course grades are included in the model, these represent a limited portion of the doctoral experience. Further, instructional courses are usually completed early in doctoral education and represent one of the first milestones achieved. An added model node of progress assessment could add meaningful connections to existing theme nodes such as Advisor, Support Network, and Goals and sub-theme nodes such as Coursework, and Certainty of Goals, and Change of Goals.
The GrAD model focuses on attrition as an outcome of the connected themes and sub-themes. However, our work demonstrates the possibility for a potential off-ramp from attrition consideration to changing research labs. Articulating changing lab investigation pathways for students through exploration of GrAD themes and sub-themes beyond the advisor could further benefit students and institutions seeking to continue in doctoral engineering programs.
6 Future work and limitations
The reliance on cross-sectional research design and a small sample size, which, while useful for identifying associations and trends, cannot establish causation due to the absence of temporal sequencing and control over confounding variables. Although mediation analyses conducted in this study may imply causal pathways, they lack the experimental controls necessary to definitively assign causation. To address this, future studies could employ longitudinal or experimental designs with larger sample populations to better understand the causal relationships between advisor dynamics, progress assessment, and departure considerations. We did not account for the influence of gender and race/ethnicity on advisor-advisee relationships, which is an important and often overlooked aspect of mentoring in doctoral education (Roy et al., 2023; McAlpine and Amundsen, 2011). This omission may mask differential advising experiences and structural inequities affecting specific demographic groups. Future research could address these gaps by exploring how gender and race/ethnicity intersect with advisor relationships, as well as doctoral students’ ability to assess their progress and navigate challenges.
Furthermore, interventions or institutional practices could mitigate the negative advisor relationships with doctoral engineering students. Such efforts might include training programs on effective mentoring strategies, fostering cultural competence, and creating structured feedback mechanisms to improve the advisor-advisee dynamic. Similarly, there is a need for research into policies and practices that enhance students’ ability to assess their progress through their doctoral programs. Implementing regular progress evaluations, establishing transparent milestones, and offering access to resources such as peer mentoring programs could empower students to navigate their academic journeys more effectively. Future investigations could assess the effectiveness of these practices in reducing stress, increasing clarity, and ultimately improving retention rates among doctoral engineering students.
Finally, while our study indicated that doctoral engineering students with negative advisor relationships face greater difficulties in assessing their progress and are more likely to make departure considerations with or without a master’s degree, it did not explain why some doctoral students persist in obtaining a master’s degree. This phenomenon could reflect a form of academic compromise, where students aim to gain some credentials for their efforts despite an untenable situation. Future research could investigate this dynamic, focusing on how students who depart with a master’s degree evaluate their options and whether their decision is shaped by personal resilience, institutional support, or advisor dynamics.
7 Conclusion
This study examines the influence of advisor relationships on early departures and lab change considerations in doctoral engineering programs. Among the many factors influencing early departure, the advisor relationship remains one of the most consequential and fragile. Results indicate a strong association between the quality of the advisor relationship, students’ ability to assess their progress, and their consideration of program departure. Mediation analysis shows that a student’s ability to assess their progress partially explains the link between advisor relationships and departure considerations, both with and without a master’s degree. Students reporting lower-quality advisor relationships were more likely to experience difficulty evaluating their progress, which in turn increased their likelihood of considering departure. Our findings reinforce a broad consensus in the doctoral education literature: the advisor-relationship is pivotal to persistence. Yet withdrawal is not the only path available to students in unsupportive situations; some seek a more conducive environment by switching laboratories rather than exiting the program altogether. While the findings from the research illustrate associations between advisor relationships, progress assessment and departure considerations, recommended institutional changes offered in this manuscript stem from implications drawn by the authors. This study highlights the importance of regularly evaluating advising and mentoring practices, transparent lab change protocols and advising environments with clearly defined milestones for assessing research and degree progress. Strengthening these institutional structures enables faculty and administrators to more effectively support doctoral students’ development while maintaining the vitality and productivity of engineering research programs.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving humans were approved by Purdue University Institutional Review Board and University of Cincinnati Institutional Review Board. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
Author contributions
MB: Resources, Formal analysis, Funding acquisition, Writing – review & editing, Project administration, Writing – original draft, Methodology, Visualization, Data curation, Supervision, Conceptualization, Investigation. TA: Writing – review & editing, Conceptualization, Investigation, Writing – original draft.
Funding
The author(s) declared that financial support was received for this work and/or its publication (Grant number: EEC2603026/EEC2404797). The National Science Foundation Division of Engineering and Education and Centers provided all funding for the research reported in the manuscript.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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The author(s) declared that Generative AI was not used in the creation of this manuscript.
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Keywords: advisor relationship, doctoral students, early departure, lab change, progress assessment
Citation: Bahnson M and Abane TA (2026) Beyond attrition: advisor relationships, progress clarity, and laboratory switching in engineering doctoral programs. Front. Educ. 11:1770054. doi: 10.3389/feduc.2026.1770054
Edited by:
Rany Sam, National University of Battambang, CambodiaReviewed by:
Jocelyn Nardo, The Ohio State University, United StatesNo Sinath, University of Battambang, Cambodia
Copyright © 2026 Bahnson and Abane. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Matthew Bahnson, YmFobnNvbXdAdWNtYWlsLnVjLmVkdQ==