Well-Being and Support Network Affiliations for Black and Indigenous College Students during the COVID-19 Pandemic

Abstract

While much of the research suggests that quality relationships and supportive campus environments shape well-being in college, racialized experiences can moderate the effort students put into their academic and well-being endeavors. However, our understanding of how relationships and networks support student well-being is understudied. This descriptive study employs a critical-relational well-being framework to analyze (n = 1200) survey responses from the Healthy Minds survey to determine perceived institutional and personal well-being support connections for Black and Indigenous college students in the United States before and during the COVID-19 pandemic. A descriptive two-mode social network analysis suggests a slight decrease in support network diversity and network differences in perceived well-being support by the level of well-being and gender. Faculty and advisors were structurally central in Black and Indigenous men’s well-being support and for those with higher well-being, but less central for Black and Indigenous women, and those with lower well-being. While family and friends provided vital social support, campus actors such as professors from class and academic advisors also served central structural roles for students with more diverse networks. Teaching assistants, student affairs staff, and religious affiliations served unique roles for students with fewer support role categories.

1. Introduction

While college enrollment and degree completion are common indicators of student success in higher education, this traditional operationalization offers little space for the complexities of student success, especially for Black and Indigenous students [1,2,3,4]. In addition to the normal stress of higher education, Black and Indigenous students experience racialized trauma and stressful experiences that impact their daily lived experiences [5,6,7,8]. Therefore, while students may exhibit traditional markers of student success—such as degree progression and attainment—those accomplishments may be paired with isolation and racial trauma, especially for students of color at predominantly white institutions (PWIs) [9,10]. In other words, a student can be considered “successful” but become unwell and traumatized by their educational experience. Moreover, for many students, it is the experience of racism and sexism that will often thwart a student’s progress and increase the likelihood that they drop academic majors, transfer institutions, or leave higher education altogether [11,12,13,14].

As a result, there are growing calls for educational scholarship that considers other notions of success, such as satisfaction, personal development, quality of life, and well-being [15,16,17,18,19]. Including well-being within student success is part of a larger initiative to extend higher education’s purpose beyond critical thinking and job placement [20]. Additionally, colleges and universities are increasingly interested in well-being interventions that increase student success and enhance institutional effectiveness [3].

Furthermore, faculty and staff are increasingly expected to prioritize and support student mental health [21,22]. For example, in a study from Boston University, they found that almost 80% of the faculty surveyed were directly addressing student mental health issues, which have only worsened since the COVID-19 pandemic, and there is a lack of training and preparation for faculty [23]. While faculty and other constituents are already engaging in this type of support, there are calls for institutional and structural policies and practices that best facilitate sustainable well-being efforts on campus. Additionally, studies indicate that student well-being decreased during the COVID-19 pandemic [24], furthering the need to study the changing relationships and networks within this context.

This study explores the well-being affiliations of Black and Indigenous college students using a critical-relational well-being framework that combines relational sociology of education and critical social capital [25,26]. I conducted an exploratory social network analysis to answer the following question: Who have been the central well-being support actors for Black and Indigenous college students before and during the COVID-19 pandemic? Findings from 1200 responses from the Healthy Minds study suggest that both off-campus and on-campus individuals exist in students’ well-being networks. Yet, actors have different levels of network centrality and influence, complicating the previous research on ideal models of college integration and the benefit or detriment of off-campus and family interactions. Based on the findings, I argue that current frameworks for student success and well-being might not account for the interaction of on- and off-campus support, or gender differences in relational dispositions. This paper contributes national social network data on the well-being support networks of Black and Indigenous college students before and during the COVID-19 pandemic, with a network analysis perspective on which institutional actors students perceive as within their well-being support networks, and what kind of network roles and power these actors may have.

2. The Literature Review

2.1. Social Networks in Higher Education

The study of networks within higher education is a useful endeavor because it “follows people as they enter a new context with new challenges and stresses, a context where forming a new set of confidants is an option yet retaining the lifelong inner circle of support that many are presumed to have remains appealing” [27] (p. 8). As network processes and outcomes are contextual, there is also evidence to suggest there are distinct influences that shape college student networks which are different from other significant social contexts [28]. There is some consensus that social support and meaningful relationships matter significantly in college [29,30,31] and positive relationships with others are important in maintaining well-being and health in general [32,33,34,35]. Additionally, higher education can play a role in structuring and facilitating student networks. For example, the information and support received from faculty and peers are shown to influence a student’s ability to deal with challenges in higher education [36,37]. This structuring can interrupt or perpetuate inequality and yield disparate outcomes for minoritized students who may not have the social capital to maintain or navigate a particular pathway or grouping [38]. Therefore, understanding those distinct influences is imperative for achieving a holistic comprehension of how higher education can profoundly change student lives and contribute to student success beyond degree attainment.

There are some empirical tensions around whom college students turn to when they need support, with some studies indicating institutional support from faculty, staff, and peers is most important for student success [4,39,40,41,42,43], while others highlight the role of family and friends, especially for students with minoritized identities [44,45,46,47,48,49]. While some argue that networks that include frequent interaction from off-campus ties are a good thing [2,16,47,49,50], others have argued that the most successful student is one that receives the majority of social support from inside the college environment as outside obligations to family or employment can hinder academic success [39,40,41,42,43,51]. For example, traditional models of student involvement from Alexander Astin [52] and Vincent Tinto, posit that the more that students engage on campus, the better. In particular, involvement with faculty and campus life are areas that support student success and student retention. Conversely, time spent on off-campus activities and endeavors (e.g., off-campus jobs) may be seen as a detriment and in direct competition with student success [4,26,40,41,42,43]. This research potentially has significant implications for practice as institutions may steer students away or towards certain types of interactions and support.

2.2. Black and Indigenous Student Support

Newer models of student engagement are less antagonistic toward off-campus endeavors and relations and find that they may be quite useful in supporting student success, especially for minoritized students. For example, Shweta Mishra’s [47] systemic review of social networks, social capital, and social support in higher education found that strong ties in personal networks (consisting of students’ family/parents and communities), and weaker ties through institutional networks (consisting of faculty, peers, and learning communities) contributed to student success. Additionally, familial support in the form of advice, motivation, and guidance was pertinent for both Native American and African American students, highlighting the role that families and communities play in their academic success, as well as the failure of institutions at times to facilitate social capital for minoritized students. Minoritized students tend to seek emotional support from peers with similar backgrounds to bond over shared negative experiences [47]. While student–faculty interactions appear to positively affect students’ well-being regardless of race [3], the impact of such interactions varies by race and ethnicity and contributes differently to the learning gains of students of color [18]. While student organizations and other same-race and same-gender support structures are generally seen as a positive contribution to student success for Black and Indigenous students [47], it is important to note that it is positive social support, interactions, and relationships that foster well-being and student success, and that negative or adverse interactions—especially negative interracial or diverse interactions—can quickly erode well-being and a sense of belonging for students of color [53,54,55]. This highlights the importance of clarifying distinctions between positive and negative interactions and relationships. This current study contributes new research on the interaction of on-campus and off-campus support and the centrality of the different roles of support within student networks that contribute to well-being and student success.

Additionally, research, especially from social and health psychology fields, acknowledges how both actual and perceived support shapes health and well-being [56,57]. For example, within a higher education context, just the perception of students feeling supported or having access to caring individuals was enough to improve student experiences [56]. In fact, “many of the benefits of social support come from the perception that social support is available; that is, that people carry their support networks around in their head” [56] (p. 707). Furthermore, there are gendered and cultural differences in how social support is experienced [58], with female college students communicating more with parents while enrolled at school [59]. Black students in general are far less likely to seek help from formal mental health services such as counselors, and will instead use informal support in community spaces [60]. Other qualitative studies have highlighted informal practices that promote the well-being of students of color, such as turning to friends, family, clergy, or Indigenous healers [61], academic and peer mentoring [62], culturally specific social-networking groups [63]; school attachment practices [64], and pre-collegiate preparations for racist treatment [65,66]. This study will add to the empirical conversation on how network structure (who is central) and network composition (institutional vs. personal support as well as formal vs. informal support) shapes student interactions, student success, and student well-being.

3. Conceptual Framework

Based on previous literature, I argue that well-being research on Black and Indigenous students necessitates including relationships with people, space, land, community, and institutions, while also considering the role of power, identity, discrimination, and racism. To that end, I created a critical-relational well-being framework, which combines elements of critical theory (specifically critical social capital) and relational sociology of education to center and contextualize the role of power and networks within well-being research. Relational sociology of education is a framework that is built from Pierre Bourdieu’s work on relational sociology and in particular, Bourdieu’s conception of habitus, or preferences and inclinations, and field, or social spaces that affirm or reject individual dispositions [67,68]. This theory assumes that all social reality is manufactured through relationships and contains elements of both structure and agency [26,67]. This means that rather than focus on individual variables, attributes, or characteristics, relational sociology focuses on the dynamic process of transactions as the unit of analysis and sees all social phenomena (including well-being) as a relational process [26,68]. Therefore, a relational study brings new and more complete answers to any social reality, especially in higher education [69].

This critical-relational well-being framework also considers the role of social capital, or the resources accrued through relationships that are then cultivated and exchanged into other forms of capital and material and social resources, such as power and influence [67]. These resources are the information, services, and goods that people receive and give depending on their networks. Because social capital is unevenly distributed, social capital is seen as a mechanism to reproduce inequity [63,70]. Critical social capital [25] builds upon traditional frameworks to offer a collective idea of how social relationships can be used in social spaces. Scholars that use critical social capital argue that by centering assets-based racial identity, social–political awareness, and civic engagement, youth and young adults can cultivate empowerment, positive cultural and racial identity, collective social consciousness, and trust [71,72,73,74,75,76]. One of the drawbacks of current network approaches to social capital is that it tends to overlook the larger socio–economic context to connect how unique settings (such as schools) play a role in the presence or absence of capital [71]. As historical tensions and larger structural inequities play a role in shaping who connects, collaborates, and reciprocates with whom [71], conceptual and analytical frameworks that consider both the network and the larger social context are ideal for understanding student support networks.

Therefore, in addition to conceptualizing social capital as networks, resources, and benefits, critical social capital provides a lens to consider how students’ help-seeking behaviors may be a part of a larger collective, political, and systemic struggle for well-being, and how minoritized racial and cultural identities shape access to network connections, important resources, and benefits. This study also considers the possibility within a higher education setting for well-being to result from social capital as a resource cultivated through relationships but also exchanged and even sacrificed to achieve success in an educational setting. This is what Bourdieu would characterize as economic capital or institutional credentials [70]. Overall, I use a combined critical and relational approach along with relational methods to fully capture the well-being experiences of Black and Indigenous students in higher education more holistically and contextually, especially considering how to analyze power within the process of getting and staying well. I lead with a conceptualization of well-being as a critical and relational, co-, and re-constructed habitus (or set of relational principles and dispositions) that shapes individual and collective access to resources and agency, and accounts for the social-historical, power, and political influence of well-being within educational institutions. In particular, I consider how social capital and social support play out within the field of education and the ways that critical social capital might relate to the relational preferences or dispositions for social support (the well-being habitus). This framework guided the selection of relational survey variables and the disaggregation process for the descriptive analysis. The framework also allowed me to connect the study’s findings back to the larger social and historical context.

4. Research Design

This project uses social network analysis (SNA) to analyze the survey data. SNA is a broad term to capture theories, concepts, and techniques for collecting and analyzing relational data [77]. SNA assumes that relationships between interacting units are essential for understanding any social context [78], and helps study how relationship structures provide opportunities, constrain choices, and are associated with social outcomes [26,77]. Relationships between “actors” are central to this research and include multiple factors, including nodes or actors (i.e., people), ties, social relations, interactions, and flows. All these factors can be collected and examined qualitatively, quantitatively, and visually to reveal fascinating processes and mechanisms of how ideas, influence, and information flow from person to person [79]. While network science often collects and studies relational data that examines the data between one set of nodes, meaning that both rows and columns within a sociomatrix are the same entities—either the same people or organizations (also known as one-mode data)—it is also possible to examine relations between two different sets of nodes (two-mode data) [80,81]. This study uses a two-mode or bipartite sociomatrix for analysis), with the rows representing one set of nodes (the students), and the columns representing different types of people who provide support, such as roommates, friends, faculty, and/or advisors. Bipartite networks have been studied in a variety of diverse contexts [82] and provide a unique opportunity to study a relational phenomenon without needing direct access to participants [83,84].

4.1. Data

To answer the research question concerning central well-being support actors for Black and Indigenous college students, it was important to find multi-year national survey data that included information about well-being, relationships, and support. The Healthy Minds study (HMS) is an annual web-based national survey that examines mental health, service utilization, and related issues among undergraduate and graduate students [85]. For over 15 years, the survey has captured self-reported attitudes and behaviors from 850,000 undergraduate students from over 600 colleges and universities. The HMS questionnaire comprised of three standard modules around mental health status and resource/help-seeking utilization, as well as several elective modules ranging from sleep behaviors to diversity and inclusion/campus climate perspectives. Institutions opted into survey participation, which was administered by the HMS research team. Typically, a random sample of 12,000 students from each institution received up to four email invitations to take the survey, and institutions under 12,000 students invited their entire population of students to take the survey [85,86]; the response rates for the years included in this study were 14% and 13%, respectively. This survey is ideal for exploratory network analysis as it includes variables on well-being (i.e., subjective well-being score [15]), student characteristics (e.g., health attitudes, demographic information, and campus involvement), and relational data on whom students reached out to for support.

Table 1. Sociodemographic information of survey sample.

Categories	2019–2020 (n = 600)	2020–2021 (n = 600)
Race Afro-Indigenous Black or African American Native American/American Indian Ethnicity Hispanic	104 (17%) 278 (46%) 218 (36%)   70 (12%)	70 (12%) 290 (48%) 238 (40%)   88 (15%)
Gender Women Men Non-Binary	439 (73%) 143 (24%) 18 (3%)	427 (71%) 151 (25%) 22 (4%)
Age 18–22 23–29 30–39 40+	531 (89%) 47 (8%) 11 (2%) 11 (2%)	419 (70%) 115 (19%) 55 (9%) 11 (2%)
Well-Being Higher well-being Lower well-being	305 (51%) 295 (49%)	315 (53%) 285 (48%)
Institution Type Doctoral Masters Baccalaureate Associates Special Focus	399 (67%) 156 (26%) 22 (4%) 23 (4%) -	56 (9%) 48 (8%) 128 (21%) 366 (61%) 2 (<1%)
Transfer Student	99 (17%)	138 (23%)
First Generation College Student	183 (30%)	199 (33%)
Year in School 1st or 2nd year 3rd or 4th year 5th year+	321 (54%) 258 (43%) 21 (4%)	308 (51%) 263 (44%) 29 (5%)

provides a sociodemographic summary of the sampled survey participants.

From an anonymized public dataset provided by the Healthy Minds Network, I employed a stratified random sampling technique to select 600 cross-sectional responses from the 2019–2020 academic year and 600 cross-sectional responses from the 2020–2021 academic year for a total analytic sample of (n = 1200) responses from Black and Indigenous college students during the survey years of 2019–2021. These data represent a snapshot of experiences and attitudes before and during the COVID-19 pandemic. Given previous studies suggesting differences in well-being for Black and Indigenous students [87,88] and the critical methodological assumptions that the experiences of marginalized communities deserve uplifting in their own empirical right, without need for a reference category or comparison to majority populations [89], the analytic sample includes only Black and Indigenous students. While Black and Indigenous students face different cultural and ethnic challenges, their navigation of higher education is scarred with interlinking historical and traumatic legacy of hegemony, domination, imperialism, white supremacy, and settler colonialism [90,91,92]. Nevertheless, these two student populations may also share in the struggle for education, liberation, and decolonization. Furthermore, disaggregation of the data by historically marginalized groups is a core component of quantitative critical research [93].

4.2. Descriptive Analysis

The two-mode network analysis for this study is in part inspired by and loosely follows Katz and colleague’s [83] analysis of gendered leadership networks in the National Collegiate Athletic Association (NCAA). To build the proxy network data, I used a binary coding system of 1s and 0s to represent connection and support for well-being based on two specific questions within the utilization/help-seeking module of the Healthy Minds study. The first question asked if in the past 12 months students had received counseling or support for mental or emotional health from the following sources: “roommate”, “friend”, “significant other”, “family member”, “professional clinician,” “religious counselor”, “support group”, “other”, or “no one”. The second informal help-seeking question focused on institutional support and asked: “If you had a mental health problem that you believe was affecting your academic performance, which people at school would you talk to?” Students could select options including “professor from one of my classes”, “academic advisor”, “another faculty member”, “teaching assistant”, “student services staff”, “dean of students or class dean”, “other”, or “no one”. I took the responses from these two questions to build a sociomatrix, which is a two-mode tabular representation of connections for all 1200 sample responses (

Table 2. Sample sociomatrix of support connections (truncated).

ID	Friend	Family	Religious	Professor	Advisor	TA	Student Affairs	Dean of Students
1	0	0	1	1	1	0	0	0
2	0	0	0	1	0	0	0	0
3	0	0	0	0	1	0	0	0
5	1	0	0	0	1	0	0	0
6	1	0	0	1	1	0	0	0
8	0	0	0	0	0	0	1	0
10	0	1	0	0	0	0	0	0

). A “1” indicated that the student selected one of these types of individuals as someone that they would reach out to for social–emotional support, thus creating a proxy social support network.

4.3. Measures

Social capital and social support have a wide range of operationalizations within the field of education [94], particularly due to the diversity of definitions. Some theorize that relationships and resources are embedded in networks as a primarily structural process [95], others see social support as available help for psychological and perceptual processing of identity in stressful situations [94]. Nevertheless, analyzing social capital and social support through network measures such as network size, strength, and diversity of support received has been found to be useful in understanding the connection between critical social capital, social support, and well-being [96]. Similar to a study that operationalized network centrality as an indicator of relational capital [96], this study will calculate and observe changes in network centrality before and during the COVID-19 pandemic.

Degree Centrality. For two-mode networks, degree centrality is a count of the number of connections from one set of nodes across to the other set of nodes. It is one of the most used centrality measures within social network analysis [97]. The normalized statistic score ranges from 0 to 1 and indicate the proportion of connections that a node has. In a bipartite network, nodes with higher degree centrality in one set likely have many connections to nodes in the other set.

Eigenvector Centrality. Eigenvector centrality is a network statistic that considers not only the sum of every direct connection but also of indirect connections to take account of the entire network [98]. The normalized score has the largest value of 1, which in a bipartite network would indicate that one node from one set (e.g., support actors) is connected to many nodes on the other set of nodes (e.g., college students), and also those students who select that node are themselves highly connected. Individuals with a high eigenvector have many connections, and their connections have many connections, which suggests a level of popularity within a network.

Bonacich Power Centrality. Bonacich beta-centrality combines the aspects of degree and eigenvector centrality to measure power and influence within a network by considering both network connections and an additional parameter (β) to measure the level of positive reinforcement from those connections to boost centrality [99]. Within a bipartite network, nodes with high positive Bonacich centrality would suggest that they play a key and critical role within the network. Score range and interpretation depend on which beta (β) value is used in the calculations. Positive beta scores range from 0 to 1 and indicate high direct influence of highly connected nodes. Negative beta scores range from −1 to 1 and indicate indirect power and a unique influence on nodes with fewer connections.

Well-being. The flourishing scale measures several aspects of human function such as positive relationships, feelings of competence, and meaning and purpose in life [100]. It assesses social psychological functioning and is widely used in research and practice [101]. In this 8-item self-reported questionnaire, respondents rated the degree to which they agreed or disagreed with a particular statement, such as “I lead a meaningful and purposeful life” or “people respect me”. Response forms ranged from 1—strongly disagree to 7—strongly agree. Total scores range from 8 (lowest possible well-being) to 56 (highest possible well-being). Respondents were coded as having higher well-being if they scored above the national average score of 44.

I used UCINET [102] and RStudio software (version 4.40) to visualize the two-mode networks, identify clusters among support actors, and calculate network centrality measures, such as the degree centrality, eigenvector centrality, and Bonacich power. I then proceeded to disaggregate data and repeat the centrality measures analysis, first between survey years, then disaggregated by high and low well-being, and then again by gender. I compared the nodes with the highest centrality within the disaggregated categories, highlighting notable changes within and between groups.

4.4. Limitations

Many of the limitations of this study center around the dataset characteristics. While further disaggregation by race and ethnicity (e.g., Afro-Caribbean) or tribal affiliation (e.g., Diné, Seneca) would add great value to the study, not all ethnicity-related questions were available for all datasets, preventing comparison by year. Furthermore, since the original survey’s purpose was not geared toward network data, the help-seeking questions were inconsistent in their wording, which could have shaped how students answered. For example, the personal support question asked who did students turn to for support (actual support), whereas the institutional support question asked who students would turn to for support (perceived support). While research suggests that both actual and perceived support shape health outcomes [53], it is difficult to distinguish the two from this dataset. This is why I characterize the data as proxy well-being networks to represent possible perceived and actual support. Lastly, while the Healthy Minds survey is a nationally represented survey, the analytic sample is not, and therefore limits its generalizability; however, it does contain national-level data that can be of value for future research and practice.

5. Findings

Who have been the central well-being support actors for Black and Indigenous college students? Descriptive social network findings reveal that a combination of personal and institutional actors are the most central well-being support actors for Black and Indigenous students overall, both before and during the COVID-19 pandemic, with some distinct differences by level of well-being and by gender. Figure 1 and Figure 2 represent a network visualization of the well-being support networks from the sample by year. Each line represents a connection from one student respondent to a well-being support category (the round gray circles). The size and label of the nodes correspond to the number of times a particular actor was selected, with larger gray circles indicating that more students selected that actor as part of their network. Well-being actors that were more frequently co-selected together are clustered near one another in the visualizations. For example, friends, family, and partners tended to be co-selected together. For network size, the average number of connections in 2019–2021 was 3 and dropped to 2.8 the following year in 2020–2021. For personal connections, friends and family stood out as important connections in the sample, along with partners. For institutional actors, faculty and academic advisors consistently led in the number of selections from survey respondents.

When comparing the support networks before and during the COVID-19 pandemic, there were three important patterns to note. The first is that during the 2020–2021 academic year, there were about 10% fewer connections overall for all students in the sample (down to 1695 from 1807). This indicates that students in the aggregated sample selected fewer support connections during the first year of the pandemic than the year prior. Except for friends, other academic personnel and support groups, most support actors decreased in the number of selections from students, indicating that many students perceived a loss in the diversity of people they could turn to for help, and also suggests that others turned to peers and friends more than ever and/or looked for new avenues of connection with other academic personal or support groups. The second pattern is that there were double the number of isolates in the sample during the COVID-19 pandemic. An isolate is a node that is not connected to any other node within the network. In this case, an isolate in this bipartite network represents a nonresponse to the survey question on help-seeking and social support. More than double the number of students in the analytic sample did not select any options to the question about informal help-seeking and support compared to the previous year (3% in 2019–2020 vs. 6% in 2020–2021). Most respondents did go on to complete other sections of the survey, which suggests that the increase in nonresponse to help-seeking could be a meaningful indication of decreased support. The third pattern to note is the large number of students (over 30%) for both years, that selected no personal connections and/or no institutional connections, indicating a concerning pattern of insufficient support for Black and Indigenous students in this sample. This lack of support remained consistent during the pandemic (with a slight increase of students indicating no personal support (30% to 31%) respectively.

While the number of connections (or degree statistic) is one manner of interpreting centrality, there are other interpretations of influence within a network. A high eigenvector score within this sample means that many students selected similar support categories and indicates that these categories are highly connected in the overall network structure. Family and friends consistently have the highest eigenvector centrality statistics, which suggests that family and friends are often selected by students who are also connected to other popular support categories. Professors from class had the third highest eigenvector centrality for both academic years, suggesting that professors may play an important role with friends and family in providing actual or perceived support for many students before and during the COVID-19 pandemic.

When analyzing for direct power and influence by support category, friends, family, and professors from class again had the highest Bonacich centrality statistics, with relatively little change during the COVID-19 pandemic. This indicates that these support categories were often named by students with diverse networks of many types of individuals providing support. When calculating indirect influence for students before the pandemic, teaching assistants were uniquely mentioned by students who were peripheral in the network due to fewer support categories and may perhaps have fewer options for types of support received by different groups (

Table 3. Centrality scores by survey year.

Year	2019–2020	2020–2021
Top Degree Centrality 2nd Highest Degree 3rd Highest Degree	Friend (0.43) Family (0.36) None Academic (0.36)	Friend (0.41) None Academic (0.35) Family (0.33)
Top Eigenvector Centrality 2nd Highest Eigenvector 3rd Highest Eigenvector	Friend (0.52) Family (0.43) Professor (0.37)	Friend (0.53) Family (0.44) Professor (0.37)
Top Direct Power 2nd Highest Power 3rd Highest Power Indirect Power	Friend (2.06) Family (1.72) Professor (1.48) Teaching Assistant (−2.32)	Friend (2.12) Family (1.76) Professor (1.47) Dean of Students (−0.66)

). During the pandemic, that changed to the dean of students. Overall, the eigenvector and Bonacich networks statistics indicate that, within this sample, there is a core hub of support that students perceived or actually sought support from, and that includes personal ties (friends and family) and institutional connections (professor from class). These role types remained central before and during the COVID-19 pandemic. For students with less diverse networks, teaching assistants and the dean of students appear to have greater power and influence by serving important and unique roles for this population of students with fewer options, and perhaps less social capital and access to resources.

Support Networks by Well-Being and Gender

When disaggregated by level of well-being and by gender, there are important differences in the three central well-being affiliations before and during the COVID-19 pandemic. For example, when disaggregated by level of well-being, a higher percentage of those in the sample with higher well-being selected professors from class and advisors as someone they have or would go to for social–emotional support. As indicated by the indirect Bonacich centrality statistics of −2.42 and −2.86, respectively (see

Table 4. Summary of highest centrality by level of well-being and gender.

	By Well-Being				By Gender
	Higher Well-Being		Lower Well-Being		Women		Men
Centrality Measures	Pre-COVID-19	During	Pre- COVID-19	During	Pre- COVID-19 (40% well)	During (43% well)	Pre-COVID-19 (45% well)	During (53% well)
Top Degree	Advisor (0.40) Friend (0.37) Professor (0.36)	Friend (0.37) Advisor (0.35) Family (0.34)	Friend (0.45) None Academic (0.41) Family (0.36)	Friend (0.44) None Academic (0.41) Family (0.32)	Friend (0.44) Family (0.38) None Academic (0.36)	Friend (0.44) Family (0.36) Advisor (0.29)	Friend (0.39) Professor (0.37) Advisor (0.35)	None Personal (0.43) Advisor (0.39) Prof/Friend (0.31)
Top Eigenvector	Advisor (0.44) Friend (0.44) Professor (0.42)	Friend (0.46) Family (0.45) Advisor (0.42)	Friend (0.55) Family (0.44) Partner/ Professor (0.34)	Friend (0.56) Family (0.42) Partner (0.36)	Friend (0.52) Family (0.46) Partner (0.36)	Friend (0.55) Family (0.47) Partner (0.36))	Friend (0.48) Professor (0.47) Advisor (0.43)	Advisor (0.47) Professor (0.44) Friend (0.39)
Top Direct Bonacich (Power)	Advisor (1.78) Friend (1.76) Professor (1.67)	Friend (1.87) Family (1.80) Advisor (1.71)	Friend (2.12) Family (1.70) Partner (1.39)	Friend (2.24) Family (1.69) Partner (1.46)	Friend (2.08) Friend (1.85) Partner (1.46)	Friend (2.15) Family (1.89) Partner (1.49)	Friend (1.98) Family (1.76) Professor (1.55)	Friend (2.01) Family (1.80) Professor (1.48)
Top Indirect Bonacich (Power)	Other faculty (−2.42)	Other faculty (−2.86)	Religious (−2.78)	None Personal (−1.36)	Other Academic (−1.97)	Religious (−1.83)	Other Academic (−2.07)	Religious (−3.02)

Note. Bold text highlights central institutional support actors.

). Faculty were also serving important and unique role, even with flourishing students that have fewer categories of support, Overall, faculty (both professors from class, and other faculty) have high levels of influence and power to especially support students with higher well-being. In comparison, students with lower well-being tended to select that they had no one at the college or university to seek help from before and during the pandemic, but instead relied on other support from friends (0.45) and family (0.36). This is consistent across all forms of centrality (degree, eigenvector, and Bonacich centrality). With the exception of professors from class with the third highest eigenvector, students with lower self-reported well-being did not indicate institutional actors as central support options neither before nor during the pandemic.

By contrast, advisors and professors held multiple levels of centrality for students with higher well-being, holding top eigenvector centrality (or connect to well-connected students), and higher direct and indirect Bonacich centrality (connected to students with higher and lower network diversity). While institutional support decreased during the COVID-19 pandemic (especially for professors from class), academic advisors continued to be commonly selected as someone students would turn to for help. This suggests that academic advisors may have played a more central role in supporting students with a high level of well-being before and during the COVID-19 pandemic in a way that was not present for students with lower well-being, who mostly sought support from friends, family, and partners.

Network disaggregation by gender also revealed several differences. First, it is important to note that the percentage of students self-reporting higher well-being increased (or stayed the same for Indigenous men) during the pandemic (see Table 4). Black and Indigenous women overall had a lower percentage of well-being before the pandemic compared to men (40% and 45%, respectively), although both groups in the sample increased by several percentage points (43% for women and 54% for men). Black and Indigenous men had a larger percentage of indicating higher well-being during the pandemic, with 57% of Black men self-reporting higher well-being, followed by 50% of Black women, 49% of Indigenous men, and 46% of Indigenous women.

Within help-seeking networks, family and friends overwhelmingly contributed to women’s support before and during the COVID-19 pandemic. The top degree affiliations for Black and Indigenous women were friends (0.44) and family (0.38), and top eigenvector and direct power were family, friends, and partners. Exceptions include the “other academics “category which was selected by women with the least diverse (and potentially less resourceful) support networks, and academic advisors, who emerged as more central to those women’s support during the pandemic. No other institutional actors made the top centrality positions for the women in the sample. This is in stark contrast to the central well-being affiliations for men, which were often comprised of institutional actors and peers. For example, professors from class and friends held top degree, eigenvector, and direct bonacich centrality for men in the sample, before and during the COVID-19 pandemic, while academic advisors held high degree and eigenvector centrality. Academic staff and religious affiliations served as influential support for men with less diverse networks. Outside of peers (who may be institutional or personal support), it is interesting to note to the lack of central personal support from family or partners in the men’s networks, especially compared to women. While family held the second highest Bonacich centrality for men, many other personal connections did not emerge as central support. Relatedly notable is the higher degree centrality of the category “no personal support” from men, indicating that many selected that they had no personal connections (family, partners, or friends) that they could or would go to for mental health and well-being support during the COVID-19 pandemic. Overall, these findings suggest that personal and peer support were more central and influential within women’s support, whereas institutional and peer support were core actors in the men’s well-being support networks before and during the COVID-19 pandemic.

6. Discussion

This study analyzed the well-being affiliations and support networks for Black and Indigenous college students before and during the COVID-19 pandemic and showed meaningful differences in the well-being support network depending on the levels of well-being and gender identity. Overall, the number of ties during the COVID-19 pandemic decreased from the prior year, aligning with other research on the shrinking social networks of college students [38]. Additionally, this study also found that family, friends, academic advisors, and professors from class were commonly named by students within this survey sample, yet had different levels of centrality depending on students’ level of well-being and gender. Institutional support from faculty and academic advisors held top centrality for Black and Indigenous men and those with higher self-reported well-being, while personal and peer support from family, partners, and friends commonly held top centrality for Black and Indigenous women and/or those with lower self-reported well-being. However, students with the least diverse and resourceful networks sought support from a different set of actors, namely other faculty and staff on campus (including teaching assistants, the dean of students, and religious affiliations). This study contributes new network perspectives on whom students perceive as trusted individuals to holistically support them while on campus, and how those network perceptions may change by race, gender, level of well-being, and over time. In particular, the findings point to a set of relational preferences, or a well-being habitus of how and with whom students build and maintain connections that provide beneficial resources.

The study offers several contributions to the field of higher education. While there are studies on well-being that examine individual behaviors and attitudes, this is the first study to provide a methodological contribution to the literature by extracting relational data from secondary survey data and implementing a relational descriptive and power analysis to explore the network and relational components of well-being support for Black and Indigenous college students. Second, this study offers a conceptually meaningful critical-relational well-being framework to guide asset-based empirical research that focuses on factors that support well-being rather than factors that cause disease or mental illness. Third, the results of this study complicate the literature on student engagement and integration that views off-campus and family interactions in college as a distraction and hindrance to success [4,41] and instead prioritizes on-campus support as necessary for retaining students [43]. Finally, this study expands our understanding of success to include well-being as a desired outcome and by viewing on- and off-campus relationships as serving equally important yet perhaps different structural roles within networks.

This study also sheds new insight on as well as complicates gender differences in well-being networks. Family and friends were more central in Black and Indigenous women’s support networks before and during the COVID-19 pandemic. However, women’s networks also included some central institutional actors, most notably academic advisors served an important supportive role in women’s well-being networks during the pandemic. Additionally, Black and Indigenous women’s well-being network mimicked that of those who were low flourishing before the pandemic, aligning with the previous literature indicating that women may have lower well-being [88]. However, this study offers new, perhaps contrary evidence suggesting an increase in Black and Indigenous college women’s self-reported well-being during the COVID-19 pandemic, which warrants further inquiry. This increase may be due to reduced exposure to negative racialized experiences since many students were not on campus. While other studies highlight how Black women have lower well-being than other groups [88], this study offers a possible explanation for well-being differences that include not just if a student has support but the relational differences and preferences in the composition and perception of well-being support. Since campus perceptions such as a sense of belonging and campus climate are co-constructed processes between the institution and students, these findings suggest that institutions that fail to cultivate a positive sense of belonging for Black and Indigenous women may not only contribute to worsening academic outcomes but also may negatively impact their well-being habitus and social support networks. Previous studies suggest that diverse interactions with others [103], validating and incorporating students’ cultures and perspectives [104,105,106], improving the racial campus climate [107], and faculty engagement [108] have all been shown to improve the sense of belonging for women and students with minoritized social identities.

While the findings that men tended to have greater well-being and included more institutional actors for support may lead some to encourage women to mimic the support networks similar to men, and simply add more campus actors, I would caution against this approach. From a relational sociology of education perspective, networks and social capital are relational, co-, and re-constructed spaces that are either affirmed or rejected within a particular field (or context). This means that instead of asking students to change, these findings may be a greater indication that institutions may not be creating conditions to affirm or legitimize women’s well-being habitus and relational dispositions for support. Therefore, expecting women to rely less on personal support or more on institutional actors is not a desired or appropriate expectation for Black and Indigenous women. However, acknowledging that having a sense of belonging is one of the highest predictors of perceived institutional support, colleges and universities can more confidently devote resources and policies that help all students to belong, and specifically Black and Indigenous women. There is also evidence of the positive impact of same-race and same-gender peers and faculty [3,6,47]. Therefore, the drastic underrepresentation of Black and Indigenous women in faculty and administration positions is also a structural and institutional problem that may exacerbate a low sense of belonging, and therefore alter a student’s perceived social support on campus.

Indigenous and Black men have networks that include more central institutional actors than Black or Indigenous women, and a higher percentage self-reported higher well-being before and during the COVID-19 pandemic. Men’s lack of central personal support from a network perspective seems to align with previous studies that argue that the more integrated students are on campus, the more successful they will be [43]; whereas Black and Indigenous women’s well-being affiliations align more with models that emphasize the crucial role of family and friends [47]. These findings suggests that there are some racial and gender differences in how students get and stay well that may not be always considered or accounted for when determining student engagement and student success. I argue that many models of student success and student well-being may not fully capture the complex relational differences and preferences of network support, nor how the integration (or lack thereof) between personal and institutional support shapes students’ well-being. Overall the future of well-being research could greatly benefit from relational engagement frameworks that consider the interrelation of diverse relationships. In this paper, I offer a critical -relational well-being framework that treats well-being as a relational process between familial, personal, and institutional support. Other exemplar models include Kiyama’s and Harper’s concept of family engagement that takes on collectivist and culturally supportive notions of family engagement to support student success [109].

7. Implications

This study contributes research to connect student relationships more concretely to both academic and health outcomes. Results from the bipartite social network analysis seem to suggest that whatever connections students had before the pandemic were somewhat maintained, which suggests that like others, higher education often reproduces the status quo (or current unequal structures [110]. For many students in this sample, higher education was a place to maintain well-being and connections if students already had those connections, but less so a place to attain well-being support if they did not have connections prior to the COVID-19 pandemic. And while more students indicated higher well-being during the pandemic when compared to the previous year, overall support, and especially on-campus support connections decreased over this same time, which warrants further inquiry. Future research can use the Healthy Minds study dataset to examine how students self-reported well-being and networks continued to change as institutions returned to in-person instruction and student housing.

Institutions of higher education are often awash in survey data, which include relational data. Social network analysis and visualization methods present a viable and insightful option for understanding outcomes and experiences from a relational and network perspective. This paper highlights the power of combining relational data with relational methods. Future research can compare the relational and structural components of well-being between students with higher and lower well-being, compare pre-and post-COVID-19 well-being support networks, and analyze any discrepancies between perceived and actual support networks. While this dataset prevented the separation of actual and perceived personal and institutional support, future studies can either collect primary data that do this, or the Healthy Minds study can consider slightly modifying their informal help-seeking questions to differentiate the two types of support. Additionally, a further analysis of within-group differences between Black and Indigenous student populations is warranted, especially considering social economic status, ethnicity, tribal affiliations (e.g., Afro-Latine experiences), and gender experiences beyond the binary.

Additional implications for practice include increasing the agent awareness of institutional actors striving for equitable well-being on campus. Agent awareness is the ability to understand and position oneself within the context of a particular network [104,111]. As the findings suggest, all campus actors can potentially play a role in supporting student’s well-being, and some have greater power to influence the type and quality of institutional support. Institutions can consider increasing and expanding agent awareness and well-being interventions that value integrated on- and off-campus relationships, target support based on network roles, enhance faculty, academic advisor, and staff training and development on network interventions, and overall facilitate relationship-rich educational conditions [30] through mentorship and programming where supportive personal and institutional relationships, especially with those in central network positions are more likely to occur.