The COVID-19 pandemic raised barriers for college students and challenged institutions to rethink approaches to student retention. Academic advising is critical to achieving student retention. During COVID-19, advisors faced increased work demands and adopted coping behaviors to keep workloads manageable. Coping behaviors are conceptualized as moving toward students and moving away from students. This exploratory study used multiple regression analyses to examine the relationship between advisor work conditions and the extent to which advisors used coping behaviors. Survey data from a 4-year public university indicated that the level of resources and supervisor support available to advisors were significant predictors of the extent to which advisors coped by moving away from students.

COVID-19 posed many challenges to U.S. colleges and students. Colleges became concerned with financial viability, reduced student enrollment, and student retention (Whitford, 2020). Students experienced mental health issues, financial uncertainties, aversions to online learning, and other educational and personal barriers (American Council on Education, 2020; Blankstein et al., 2020; Office for Civil Rights, 2021). Caught between competing institutional and student needs are academic advisors, professionals tasked with helping institutions achieve student retention, progression, and completion (RPC). Advisors work directly with students to advance their educational development and guide them toward degree completion (Kuh et al., 2005). Advising students toward graduation requires various approaches depending on the student's needs. This notion is supported by Lipsky's (2010) Street-Level Bureaucracy theory, which suggests public service workers with direct client contact have the potential to influence client outcomes in the way they implement policy. The aim of this study is to provide an understanding about the ways in which advisors at a 4-year public university coped during a time of unprecedented organizational change at work.

During the pandemic, college students reported an increased need for academic advising services (Blankstein et al., 2020). Higher student demand—plus new and expanded contact methods such as virtual, email, and phone appointments—likely also increased the frequency of student-advisor interactions. Additionally, the pandemic brought budget cuts, hiring freezes, furloughs, and ambiguities around rapidly changing organizational policies and procedures. This increase in demand for advising services, coupled with reduced organizational resources, challenged academic advisors with increased work demands, resource deficiencies, and high client needs. Using Street-Level Bureaucracy theory, this study examines advisors' use of coping to adapt to work stress during the pandemic.

Coping is the behavioral effort advisors employ in interactions with students to master, tolerate, or reduce external and internal daily work demands (Tummers et al., 2012, 2015). This broad definition can include many behaviors including positive thinking and problem-sharing with colleagues or others. This study focused on coping during public service delivery and concentrated on coping behaviors that occurred during advisor-student interactions. The research questions include:

R1:

What coping behaviors did academic advisors, as street-level bureaucrats, use to manage stress in interactions with their clients (students)?

R2:

To what extent did resources and supervisor support impact the type of coping academic advisors utilized?

As instruction moved online at the beginning of the pandemic, so did academic advising. Advising was among the first higher education services to embrace technology to supplement its work (White, 2020). However, academic advisors experienced formidable challenges in the process.

Pandemic uncertainties changed the nature of student needs in extraordinary ways. Studies conducted early in the pandemic found students were reporting higher levels of mental health and personal well-being needs (Wang et al., 2020). The quick shift to online learning, institutional policy changes, and increased tuition costs impacted student learning (Blankstein et al., 2020). The looming recession gave students anxiety about their job prospects and career choices, and more frequent contact with advisors became increasingly necessary.

Fears about reduced enrollment and funding from state allotments and endowments led institutions to enact hiring freezes and furloughs, as well as reduce operating costs through spending cuts for professional development (Salazar et al., 2020). This affected the institution's ability to provide the training and staffing needed for advisors to better adapt to the increased work demands.

Although not typically considered street-level bureaucrats (SLBs) in the literature, academic advisors exhibit many traits of SLBs. As defined by Lipsky (2010), SLBs are public service employees who:

Interact directly with citizens in the course of their jobs, and who have substantial discretion in the execution of their work…Typical street-level bureaucrats are teachers, police officers and other law enforcement personnel, social workers, judges, public lawyers and other court officials, health workers, and many other public employees who grant access to government programs and provide services within them. (p. 3)

The relational nature of SLB work allows some level of discretion and latitude in policy implementation. Discretion is the degree of freedom from which SLBs must choose from possible courses of behavior to implement policy (Thomann et al., 2018). In daily work with clients, they choose from a range of actions to provide appropriate services or responses to individual clients. Because of the potential impact of these decisions to help or harm clients, SLBs are guided by their professional norms and view themselves as accountable to both their organizations and their clients (Lipsky, 2010).

Academic advising is designed to connect students with appropriate resources to advance students' academic careers and address obstacles to successful degree completion. Research also supports the key role advisors play in implementing institutional policies and achieving institutional RPC goals (Harrill et al., 2015; Nutt, 2003; NACADA, 2006). Considering the vast differences between colleges, majors, and students, advisors exercise discretion in responding to each student's needs in an individualized way (Howard, 2017). This can be observed when advisors provide course recommendations to students: advisors can utilize a static, checklist-type approach to course planning or inquire about student interests and strengths.

Because advising approaches may potentially help or hinder a student's pursuit of degree completion, it is essential that advisors rely on professional memberships and norms to guide their work (NACADA, 2006). For example, the need for guidance and resources for first-generation students may differ from those of adult-learners. Based on their institution's professional norms and their professional memberships, advisors determine the depth of counseling each student receives. Institutions trust academic advisors to use best practices and careful judgment to meet individual students' needs. Researchers can study advisors as SLBs using the SLB theory because of the discretion and latitude with which advisors can approach their work and implement policy.

Implementation scholars within public administration are concerned with understanding the differences between policy as created and policy as implemented, and this research has largely ignored the work of frontline employees at public agencies (Zang, 2016). Lipsky's (2010) theory of street-level workers shifted the paradigm in the study of bureaucracy and policy implementation. Lipsky (2010) argued that policies are abstractions that only fully materialize when they are delivered to citizens. To understand the effectiveness of policy outcomes, it is important to examine the behaviors of the frontline workers responsible for delivering the policy to citizens (Tummers et al., 2012; Winter, 2012). It has been widely acknowledged in the public administration literature that SLBs experience stressful working conditions with limited resources and high workloads. To deal with this stress, they must adopt ways to cope (Gofen, 2014; Maynard-Moody & Musheno, 2003; Tummers et al., 2012, 2015; Vedung, 2015; Winter, 2012).

According to Lipsky (2010), coping behaviors SLBs used to deal with work pressure effectively become the policies they carry out.

Forms of Coping During Public Service Delivery

Since Lipsky first addressed coping, the concept has been widely acknowledged as an important response to the challenges of frontline work (Winter, 2012). However, Tummers et al. (2015) argued that SLB literature lacked a comprehensive view of coping. They found that research used different terms to define and operationalize coping. They developed a system to classify coping as a construct that can be operationalized across professions and contexts (Tummers et al., 2015). The classifications included three broad forms of coping during public service delivery: moving toward, moving away, and moving against clients. Moving toward clients refers to pragmatically adjusting to the client's needs and is a form of coping toward the client's benefit. The latter two groups are coping forms toward workers' benefit. Moving away from clients categorizes behavior in which frontline workers avoid meaningful interactions with clients, whilst moving against clients involves confrontations with clients. Past literature supports that SLBs—because of the professionalization, relational, and service-oriented nature of SLB work—are unlikely to use hostile behaviors in interactions with clients (Tummers & Rocco, 2015; Vedung, 2015). Furthermore, because of social desirability bias and the tendency for individuals to underreport moving against clients, researchers omitted this form of coping from this study. The forms of advisor coping relevant to this study are discussed below.

Moving Toward Clients (Students)

Literature supports that SLBs have high levels of professionalism, closeness with clients, and heavy reliance on professional norms to guide their work in challenging times (Vedung, 2015). Public service motivation research supports that SLBs typically choose public service careers because they want to provide meaningful services and mobilize personal resources to help clients (Bakker, 2015). Tummers and Rocco (2015) examined the role of frontline workers in the successful implementation of e-government services under the Affordable Care Act. They found that despite the high technical demands on agencies and citizens in an environment of budget austerity and political polarization, frontline workers coped with stress by moving toward clients—working overtime to help solve client problems.

This study examined coping by moving toward clients as the use of personal resources and applies to advisors who invest time and energy in helping their students, beyond that specified in their job descriptions. This includes overtime and personal days to address student needs.

Moving Away from Clients (Students)

Some scholars suggested that frontline workers cope with work stress by moving away from clients (Salamon et al., 2000; Tummers & Rocco, 2015; Tummers et al., 2015; Vedung, 2015). Tummers et al. (2015) posited that SLBs cope by moving away from clients when SLBs routinize or ration services.

Routinizing refers to a standardized or routine manner of client service. In routinizing services, SLBs attempt to deliver the same standard of service to many clients within a short time. Customization of service is compromised, which can potentially hurt clients. When advising demand is high, such as during registration, advisors adopt walk-in advising (Groth, 1990), which restricts advising appointments to a pre-set criteria of issues (e.g., future course planning). Should students have more complex concerns, advisors refer students to wait until a full advising appointment becomes available (Groth, 1990).

Rationing services refers to the actions taken to lower service availability, attractiveness, or client expectations about service delivery (Tummers et al., 2015; Vedung, 2015). During COVID-19, the number of student advising inquiries via email significantly increased. To save time and streamline processes due to the high influx of emails, advisors generated email templates to respond to commonly asked questions. While convenient and timesaving, this method does not benefit students who need personalized advising. For example, a student who is failing and wants to drop a course may benefit from a response template that outlines tutor resources or withdrawal policies. However, this response may not help a student failing class because of inaccessibility of course materials. Here, the student would benefit from personalized advice such as a referral to the Information Technology department or help discussing the matter with their course instructor. Salamon et al. (2000) suggested that nonprofit workers who work under conditions of a small workforce, amateurism, and limited budgets, often cope by moving away from clients, despite strong motivations toward serving clients' best interests.

Linking Coping Behaviors to Advising Approaches

In advising literature, two commonly contrasting and widely used approaches to advising include prescriptive and developmental advising (Harris, 2018). Prescriptive advising involves a checklist approach that restricts advising sessions to academic matters and neglects students' personal development and needs (Drake, 2011). Developmental advising is a theory-based, comprehensive approach to promote the development of the whole student. In a developmental advising appointment, advisors help students articulate academic and personal goals, develop plans to achieve those goals, and monitor student progress to meet set goals (King, 2005). Advisors who use coping behaviors that move toward students, and who rely on personal resources and energy to meet students' needs, likely use developmental advising approaches. Conversely, advisors who employ coping by moving away from students restrict time with students and tend more toward prescriptive advising.

Factors Influencing Coping Behaviors of Advisors

This study drew from the literature (Gofen, 2014; Lipsky, 2010; Maynard-Moody & Musheno, 2003; Tummers et al., 2012, 2015; Tummers & Bekkers, 2014) and identified organizational factors common to SLB work settings that can help explain variances in the extent to which academic advisors coped by moving toward and away from students.

The Problem of Resources

SLB work takes place under conditions of limited resources. Two common ways in which organizations provide inadequate resources to workers are the ratio of workers to clients and time constraints (Lipsky, 2010). The problem of resources describes the gap between the worker demands and the resources available to meet work demands such as time, staffing, training, and materials. Several studies identified resource constraints as a key factor affecting how workers approach their positions (Brodkin, 2007; Riccucci et al., 2004; Tummers et al., 2015).

Supervisor Support

This refers to advisors' ability to obtain supervisor support when needed (Burr et al., 2019). The importance of supervisor support is well documented in SLB and organizational psychology literature. Lipsky (2010) highlighted that frontline workers' behavior is shaped by supervisors, which results in fundamental changes to policy implementation and the decisions made by bureaucrats. Supportive leadership is crucial to maintain employee self-efficacy, well-being, and positive attitudes toward clients and work (Keulemans & Van de Walle, 2020; Rafferty & Griffin, 2006). The primary function of supervisors is not merely to control or monitor SLBs but also to educate, persuade, and coordinate worker decisions to ensure quality public service (Hassan et al., 2021).

SLB literature suggested that resources and supervisor support can influence SLB coping behaviors (Bakker, 2015; Maynard-Moody & Musheno, 2003; Tummers & Rocco, 2015). Because of furloughs, hiring freezes, and budgetary constraints related to COVID-19, (Salazar et al., 2020) plus increased student-advisor interactions, advisors experienced reduced resources and increased work demands. In response, advisors as SLBs tend to respond in two ways. First, guided by professional norms and public service motivations to provide meaningful service, advisors may cope by moving toward students; they will work overtime and use personal resources to help students. Second, in response to increased demands, they may cope by moving away from students, rationing time and routinizing services to create a more manageable workload. Therefore, we can hypothesize that advisors with fewer resources will utilize coping by moving toward students and moving away from students.

H1:

A negative association exists between resources available to advisors and the extent to which they cope by moving toward students.

H2:

A negative association exists between resources available to advisors and the extent to which they cope by moving away from students.

The shift in work operations during COVID-19′s stay-at-home orders limited advisors' in-person interactions with supervisors, which may have resulted in advising leadership that was underprepared for addressing the needs of staff in this new format. Under supportive leadership, advisors are likely to seek guidance on ways to approach problems of high demands and reduce the need to cope at work. Therefore, it is hypothesized that in the absence of supportive leadership, advisors can experience uncertainty and stress about work and expectations. To deal with this uncertainty and stress, advisors may cope by moving toward students (putting in extra work time to meet demands) or moving away from students (routinizing work to simplify job tasks).

H1a:

Advisors who receive supervisor support use lower levels of coping by moving toward students.

H2a:

Advisors who receive supervisor support use lower levels of coping by moving away from students.

Participants

This study sampled a population of academic advising professionals employed at a large 4-year public university with a decentralized structure of academic advising, serving a diverse student population. The study restricted participants to full-time employees (N = 71) in a professional academic advising role, where primary job duties included direct student advising. The sample did not include advising administrators or direct supervisors. All academic advisors employed at the institution during the time of the study received recruitment messages. The analysis included only completed responses (n = 30).

Materials

Participants completed an online survey that measured academic advisor working conditions during the pandemic and self-reported the coping behaviors they used in student interactions. All questions explicitly mentioned responses ought to consider the work period of March 2020–July 2021, when the institution was operating under COVID-19 restrictions. Questions were generated from past literature (Burr et al., 2019; Langford, 2009; Tummers et al., 2015) with established and validated scales to measure all variables of interest. However, with consideration to the novelty of the context, many items were reworded and adapted to better fit the context of academic advising and the pandemic. All responses were recorded on a five-point Likert scale.

Variables and Measures

Independent Variables. The two independent variables in this study included:

(1) Resources: the fundamental aspects of work that contribute to successful achievement of an employee's job objectives, including assigned caseloads, time to conduct work, staffing, professional development, career advancement, and technological needs (Demerouti et al., 2001; Lipsky, 2010). This was measured using seven items from the Voice Climate Survey (Langford, 2009). However, because of the novelty of this study's context, principal component analysis was conducted to explore the underlying factor structure of the seven items measuring resources. Inspection of the component matrix indicated two items with values less than .55, the criteria considered acceptable (Comrey & Lee, 1992). The two items were, “I had access to the technology (i.e., stable internet connection, software, laptops, printers) to do my job well,” and “I had access to an appropriate workspace,” (i.e., the technology and space advisors needed to successfully conduct work). The pandemic forced remote work and conditions of home offices may have varied widely among individual advisors with little organizational control over these factors. Therefore, these items were dropped from further analysis. The five items retained measured advisor perceptions about caseloads, time to conduct work, professional development, and career advancement opportunities. Cronbach's alpha (α = 0.84) for the five items indicated good internal consistency. Researchers obtained mean scores for individual responses to the five items, which created a resource variable measured from 1 = strongly disagree to 5 = strongly agree. Higher scores indicated higher levels of resources provided to advisors.

(2) Supervisor Support: the employee's perception of the ability to obtain support from supervisors when needed (Burr et al., 2019). This variable was measured using one item from the Third Version of the Copenhagen Psychosocial Questionnaire (Burr et al., 2019), “When needed, I could count on my supervisor for support.” Responses were coded as a binary variable, where 0 = no and 1 = yes.

Dependent Variables. Coping is defined as the behavior advisors used to master, tolerate, or reduce demands at work. Survey items from the coping scale developed by Tummers et al. (2015) were modified to measure advisor coping behaviors, with the term client replaced with student. It is also noted that coping cannot be measured on a linear scale, as coping behaviors are not mutually exclusive. For example, advisors may choose to respond to student emails outside of business hours (coping by moving toward students), and at the same time limit the amount of time spent with students during appointments (coping by moving away from students). For this reason, the study conducted a principal components analysis with varimax rotation on all items of the coping scale and produced two factors that were used to measure advisor coping.

  1. Moving toward students: The first factor exhibited the highest loadings on four items with behaviors such as uncompensated overtime or time taken from personal activities to help students; this component was labeled moving toward students. Items included: “I started work early and/or finished late to be able to respond to my students in a timely manner,” “I limited my breaks or interrupted my break to keep up with student requests,” “I responded to student emails on my days off,” and “I skipped on personal activities to keep up with my student requests.” The alpha coefficient was .86, which suggests the items have relatively high internal consistency.

  2. Moving away from students: The second factor loaded on seven items that correlated to decreases in advisor service availability to students (rationing) and standardizing interactions with students (routinizing); this component was labeled moving away from students. Items included: “I had to ration my time with students,” “I had to spend less time with students than would be optimal for them,” “I was unable to give students the attention they needed,” “I had to tell students that I have a limited amount of time to meet with them,” “I was unable to help students to the fullest extent I wanted to or the extent I felt they needed,” “I get impatient when students need repeated reminders on matters related to their academic success (i.e., course registration, due dates)” and “I was unable to serve my students in a way that exceeded their expectations or requirements.” The alpha coefficient for these items was .91, which suggests relatively high internal consistency.

The factor scores for the coping behaviors of moving toward students and moving away produced standardized scores, each variable with a mean close to zero and standard deviation of one. Participant scores above zero on each of the coping scales indicated that the advisor identified with the form of coping more frequently than the group's mean use of that same form of coping.

Control Variable. Work experience influenced an individual's response to work stress (Demerouti et al., 2001). Therefore, this study used years of advising experience at the institution as the control variable.

Given the small number of advisors and turnover at the institution, we framed years of experience as a categorical variable in the survey to ensure participant confidentiality. For analysis, this variable was dummy coded, where 1 = over 5 years of advising experience at the institution, and 0 = all else.

Analysis

Researchers screened data for missing values and accuracy; in cases of missing data for the variables of interest, researchers employed a listwise deletion method (n = 30). They then conducted multiple regression analyses to examine the effect of resources and supervisor support on the two dependent variables: coping by moving toward students (Equation 1) and coping by moving away from students (Equation 2). The equations for both models are presented below.

Table 1 contains descriptive statistics of means, standard deviations, and correlations among each variables. The frequencies reveal that advisors cope with stressors through both coping behaviors. However, 54% of advisors report above the mean in personal time use and energy to benefit students, thus relying more on coping behaviors that move them toward students.

Table 1.

Descriptive Statistics and Correlations

Descriptive Statistics and Correlations
Descriptive Statistics and Correlations

To the contrary, 63% of advisors fall below the mean in their use of coping behaviors that move them away from students. Only 37% of advisors in the study report above average moving away coping behaviors.

Factors Influencing Coping Behaviors

After statistical control for years of experience, researchers do not find the first regression model to be significant, which indicates resources and supervisor support have no effect on the extent to which advisors cope by moving toward students. Therefore, hypotheses H1 and H1a have been rejected.

After statistical control for years of experience, researchers found the second regression model, which uses resources and supervisor support as predictors of the extent to which advisors cope by moving away from students, to be significant R2 = [.54], F (3,26) = 9.97, p <.001. This model explains 54% of the variance in advisor behaviors moving away from students. Findings suggest that for every 1 unit increase in resources, advisors are .53 below the group mean in their use of coping by moving away from students (p = .001), and when work conditions shift from no supervisor support to the presence of supervisor support, advisors' coping by moving away from students is .88 below the group average (p = .024). Therefore, an increase in resources and presence of supervisor support reduces the extent to which advisors cope by moving away from students, supporting H2 and H2a. Table 2 outlines regression analysis results for both models.

Table 2.

Regression Coefficients for Coping Behaviors

Regression Coefficients for Coping Behaviors
Regression Coefficients for Coping Behaviors

The purpose of this research is to examine the ways advisors coped at work throughout the pandemic, a time of rapid organizational change and uncertainty. The central argument of the study is that advisors use coping behaviors to make work more manageable. In turn, coping behaviors can have important implications for advising and institutional outcomes.

Descriptive data suggests advisors cope using both forms of coping behaviors, moving toward and moving away from students. Overall, advisors rely more on coping behaviors to benefit students and less on coping behaviors that move away from students. More than half of the advisors included in this study coped by using personal resources and energy to help students at a level above the group mean. Conversely, only 37% of advisors indicated coping by rationing and routinizing services at a level above the group mean. The notion that advisors rely more on behaviors moving toward and less on behaviors moving away from students aligns with the findings of Maynard-Moody and Musheno's (2003) public service workers coping study.

In consideration of the factors that influence advisor coping methods, researchers constructed two theoretical models that linked resources and supervisor support as determinants of coping by moving toward and moving away from students. They tested the models using multiple linear regression and found support for two of the four hypotheses proposed. Researchers did not find the presence of resources and supervisor support to be significant predictors of coping behaviors that move advisors toward students. Regardless of the resources or supervisor support, advisors cope by moving toward students and draw upon professional norms and desires to help students. When advisors cope by moving toward students, they use personal time and energy to meet students' needs. However, overtime work is shown to lead to worker burnout and turnover (Demerouti et al., 2001). Advisor burnout and retention should concern higher education institutions. High advisor turnover is linked to student retention and financial burdens of staff replacement (Cuseo, n.d.).

During times of high stress and demand, to avoid burnout and keep workloads manageable, advisors also rely on moving away coping behaviors such as limiting time with individual students and routinizing services. Resources and supervisor support have a significant impact on the extent to which advisors use moving away coping behaviors. Therefore, when advisors face resource depletion and nonsupportive supervisors, they rely more on behaviors that move them away from students. Further, coping by moving away may be linked to prescriptive advising, a checklist approach to advising that allows advisors to limit the time spent advising individual students. This contrasts with developmental advising, considered a more comprehensive and student-centered approach (Drake, 2011) that may place a heavier time burden on an advisor. Research supports the idea that positive student retention outcomes are more likely through developmental advising than through prescriptive advising (Al-Asmi & Thumki, 2014; Drake, 2011; Harris, 2018; Vianden & Barlow, 2015). Thus, the type of coping advisors use can potentially influence their advising approach, which has broader implications institutional goals of student retention and progression.

A major limitation of this study is its small sample size. As an exploratory study, results are not intended to generalize to a broader advising population but to provide insight into an understudied and novel phenomenon.

Additionally, these findings may be biased against instances of moving away from students. In survey research, respondents may be prone to social desirability bias, for instance, and report behaviors moving toward students, even if actual behavior does not align with their response. Although researchers attempted to reduce social desirability through assurance of confidentiality, the potential for bias cannot be eliminated. Future studies should analyze coping behaviors of advisors by asking students about advisor interactions and behaviors during appointments, especially when advising demand is high.

To a certain degree, workplace stress is part of every job, but worker coping methods are not as often discussed. This exploratory study makes a useful contribution to the literature through conceptualization of advisor coping behaviors used in interactions with students under demanding work conditions and examines the impact of resources and supervisor support on the type of coping behavior used.

During times of high stress and demand, the findings of this study suggest that to keep workloads manageable, advisors rely on coping behaviors that include moving toward and moving away from students. Despite the available resources or supervisor support, advisors cope more by moving toward students through overtime work and use of personal resources to meet work demands. However, reliance upon personal resources to cope with work demands is not sustainable and may result in undesirable effects such as advisor burnout and turnover (Demerouti et al., 2001).

Advisor turnover can be costly for institutions as new advisors must be recruited and trained. In addition, the quality of advising students receive may suffer, which can negatively impact the institutional goals of student retention and persistence. This suggests that college campuses should focus on improving advisor working conditions by providing necessary resources to navigate daily job challenges. Institutions should strive to build a culture of positivity, openness, and collaborative problem-solving and provide professional coaching and development to advising leadership. Advisors require work environments where they feel valued, acknowledged, recognized, and rewarded, and where resources are provided to support a healthy work-life balance.

This study serves as a model to inform administrators on the necessary resources and support needed to strengthen advising practices on college campuses.

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Author notes

This paper and the research behind it would not have been possible without the guidance of Dr. E. Lee Bernick, who provided feedback on this project design and statistical analysis.

Sheetal Survase obtained an MS from Monash University in Public Policy and Management and is pursuing her PhD in Public Affairs from the School of Public Policy and Leadership at the University of Nevada, Las Vegas. Her research focus includes applying public administration theories to organizational change and management. Sheetal Survase may be reached at [email protected]

Elizabeth Johnson is pursuing her PhD in Anthropology and is part of the Evolution and Human Behavior Lab at the University of Nevada, Las Vegas. She advocates for interdisciplinary research, focusing on biocultural approaches to human behavior and health. These approaches include stress response mediation, emotion regulation, and social engagement.