Eating (alone) with Facebook: Digital natives' transition to college
First Monday

Eating (alone) with Facebook: Digital natives' transition to college by Giyoung Park

This study explores how communication patterns in social settings are related to one’s transition to a new environment and examines how contextual variables are associated with these relationships. An exploratory, qualitative phase included interviews, focus groups, and anonymous confession posts on Facebook, followed by three quantitative online surveys using college freshman students during their initial semester. Dormitory dining halls were among primary social settings on campus; yet, freshman students did not want to eat dinner alone there. Dinner location was not correlated with sense of belonging; however, underrepresented minority (URM) who had dinner in dormitory dining halls reported lower sense of belonging. URM solo-diners more likely used a screen such as a mobile phone. Solitary URM diners, especially those who used a screen, reported lower sense of belonging early in the initial semester. Text messaging in the dining halls was associated with greater sense of belonging. Furthermore, greater sense of belonging was related to better mental health. URMs’ greater sense of belonging in the initial semester could predict greater academic achievement over the next few semesters; however, non-URMs was unrelated to GPAs.


Research aim and questions
Qualitative data analysis results
Survey results




New technology often generates societal concerns about potential negative effects on people (Csíkszentmihályi, 2013). Television and the Internet, for example, were initially believed they would reduce the need for face-to-face interaction and thus isolate users from social ties (Kraut, et al., 1998; Lofland, 1998). More recently, similar concerns have been raised about social media and smartphones. Such technologies may not have deteriorated community or society (Hampton, et al., 2011), yet they have made changes in how we interact with one another. Mobile phones and the Internet, for instance, have been integrated into our daily lives offering new ways of interpersonal communications beyond physical and temporal co-location. Online and face-to-face communication modes are not exclusive but can be often copresent. Furthermore, interpersonal interaction is influenced by with physical, sociocultural, and temporal contexts (Bronfenbrenner and Morris, 2006; Burleson, 2010). This study explores potential consequences of screens — personal communication gadget and platforms herein, such as mobile phone and the Internet — use in situations where face-to-face interaction opportunities are readily available. The present study aims to find answers to the following questions:

  1. How do communication patterns in social settings influence one’s transition to a new environment?

  2. What and how are contextual variables associated with such patterns using recently arrived college freshman on a college campus?




Geographic physical mobility and communication technologies

Increasing geographic mobility in many societies leads to more frequent detachment from the local social network and adjustment to new physical and social environments. This likely increases stress and loneliness, which puts one’s well-being at risk (Csíkszentmihályi, 2013; Mikal, et al., 2013; Thoits, 1995). Many American college freshmen who move from hometown to college likely experience significant change in social networks (Ellison, et al., 2006). Such changes can increase sense of loneliness and incidence of depression, which can lower academic performance (DeRoma, et al., 2009; Wei, et al., 2005).

Thanks to screens and their prevalence, many people can access their close ties through the Internet virtually anytime and anywhere. A recent report indicated that 77 percent of American adults owned a smartphone; and it became 92 percent among ages 18–29 (Pew Research Center, 2017). Easy access to social support from existing social networks on screens can help one’s transition to a new environment (Mikal, et al., 2013; Wright, et al., 2013). While some studies found social networking sites (SNS) can help social network building in a new environment (e.g., Ellison, et al., 2007; Hampton, 2007; Steinfield, et al., 2008), others reported negative effects such as increased loneliness or decreased quality of in-person interaction (e.g., Brandtzæg, 2012; Turkle, 2015). Curated social media posts that feature happier experiences can undermine audiences’ satisfaction with life (Krasnova, et al., 2013). Social support both from face-to-face and from Facebook interaction was associated with less depression among college students. Yet, face-to-face communication showed greater negative correlation with depression symptoms than communication on Facebook did (Wright, et al., 2013). A more recent study uncovered that SNS usage was associated with lower happiness among those with smaller social capital (Arampatzi, et al., 2018). One way to investigate this further is by considering contextual factors — for example, in what settings, when, etc. social media use operates. Academic performance is among indicators of successful college transition along with sense of belonging and retention. Greater Internet and SNS usage was linked to lower academic achievement (Junco, 2012; Kubey, et al., 2001). One study reported that Internet usage for work was associated with lower GPA while Internet usage at the beginning of day was related to higher GPA (Shields and Kane, 2011), suggesting potential influence of contexts on the relationship between screen use and student outcomes.

Social network building

Frequent casual encounters in public and semi-public/ neighborhood places add vibrant atmosphere to spaces (Carr, et al., 1992; Jacobs, 1961), Semi-public settings such as neighborhood parks are more likely associated with greater regularity and the duration of stay compared to public settings such as malls and urban centers (Demerath and Levinger, 2003). Regular and longer visits to a neighborhood park were associated with greater number of local ties (Kaźmierczak, 2013). In higher education settings, college students have similar life stage and intelligence levels, yet differ in majors, interests, social classes, race, etc. Students likely maintain their weekly activity patterns (e.g., class, dining hall use) throughout the semester, which may contribute to social network formation on campus.


When studying a specific setting (e.g., home, workplace, school), we may overlook a larger picture of the ecological network (e.g., neighborhood, cities) wherein multiple settings and their occupants are situated. Bronfenbrenner’s bioecological theory illustrates one’s relationship with contexts (Bronfenbrenner, 1993; Bronfenbrenner and Morris, 2006). This framework considers immediate daily environments (e.g., school) that are often associated with a specific set of social ties. Accumulated interaction in these settings influence one’s development over time. This framework also notes that one’s experience in one setting could spill over to other settings. For instance, parent-child interaction may be influenced by a parent’s experience at work (Bronfenbrenner and Morris, 2006). Similarly, one’s experience in a dormitory dining hall may affect interpersonal interactions in other settings and an overall college experience. Temporal dimensions — e.g., time of day, duration, regularity vs. stochasticity, developmental stage in life — can be related to one’s physical context. Therefore, context encompasses a wide range of factors including types of settings and associated norms, sociocultural factors, temporal dimensions, individuals’ histories and values that can all function to affect how screen use influences human communication and social connection (Park, 2017). Screens can fit into a bioecological model yet are distinguished from physical environments. Screens are nested in physical settings in which they are used. Unlike physical settings, they are not embedded — screen users carry their screens and associated social ties wherever they go (Park, 2017).

Social network diversity

Social network diversity can contribute to physical and mental health (Cohen, 2004), information acquisition (Granovetter, 1983), and greater upward social mobility (MacDonald, et al., 2005). Campus diversity helps not only minority students’ (e.g., ethnicity, socioeconomic status) college transition but also benefits majority students’ preparation for joining the workforce in increasing global and diverse societies (Howard-Hamilton, et al., 2011; Locks, et al., 2008). However, being a racial minority can be stressful (Burrow and Hill, 2013), and URMs frequently face identity threats (Steele, 2011). Multiple stressors can generate more prominent adverse effects than a single stressor (Evans, et al., 2013). Having such stressors on daily basis, social integration may be harder for URM students (Gonzalez, 2010; Hurtado, et al., 2007). Although many higher education organizations support campus diversity, college dropout rates are significantly higher for students of color and those from lower social class backgrounds (Gonzalez, 2010).

Sense of belonging, social capital, and transition to college

A sense of belonging is perceived integration into a group and is a fundamental human need (Maslow, 1943). Sense of belonging in college is a primary indicator of students’ successful transition to college, both academically and socially, and influences retention rates (Hagerty, et al., 1992; Hurtado, et al., 2007; Locks, et al., 2008; Pittman and Richmond, 2008). Social capital — the sum of resources available through social interaction (Lin, 2001; Putnam, 2001) — can contribute to a sense of belonging. Moreover, underrepresented minority (URM) students may experience a more difficult transition compared to Anglo students that, in part, may reflect lower sense of belonging (Hurtado, et al., 2007).

Recent studies have shown that the effects of college students’ Internet use on social capital and academic achievement may depend on specific situations and on what students do on screens (Shields and Kane, 2011; Valenzuela, et al., 2009). For example, when choosing to be online over opportunities for face-to-face interaction, one’s social capital development may be delayed whereas the same online activity in a dorm room may contribute to social capital (Resnick, 2002). Eating together is certainly crucial in developing a sense of belonging to a group, in forming group culture, which can help greater group performance (Alexander, et al. 1977; Kniffin, et al., 2015; Rapoport, 2005). Goffman (1963) noted that Single’s — the solitary in public — would bring a book, newspaper, or currently, screen as an excuse because of the negative impression of being alone in public. Such excuses, in turn, become a shield to serendipitous encounters. Goffman’s terms, Single and With, will be used throughout the paper to indicate solo diners and diners in groups.



Research aim and questions

This study aims to investigate college freshman students’ communication patterns in daily social settings and to explore the relationships among their communication patterns, associated contextual variables, and adjustment in college. It is important to keep in mind that the college transition experience is unfolding against a background of critical adult development when late adolescents are beginning to separate from their immediate families and often struggle with long-term personal and professional goals. Dormitory dining halls were chosen since they would be amongst primary social places for new college students living on campus. Co-location in the dormitory dining halls can help students make acquaintances and catch up with friends. However, screen use in daily social settings, like dormitory dining halls, may reduce opportunities to diversify or broaden social networks. The primary focus of this study is to investigate online and face-to-face communication patterns in the specific settings that they occur within rather than the effects of activities on screen in general. Because this is a relatively new scholarly topic, the present study involved methodological triangulation including focus groups, interviews, anonymous Facebook posts, and surveys to answer the a variety of research questions, described below. Retention and six-year graduate rates are often a measure of college transition studies; however, they were not used in the present study because the institution where this study was conducted had very high retention and graduate rates compared to national averages. Initial research questions were:

Q1. How does dining in the dormitory dining hall help social network building?

Q2. How is screen use in the dining hall associated with transition to college?

Q3. How are immediate social environments (e.g., Single vs. With, with friends vs. acquaintances or strangers) in the dining hall associated with screen use?

Q4. What are the relationships among sense of belonging, mental health, and academic achievement?




This study utilized sequential mixed methods that consisted of two phases. Phase 1 explored millennial college students’ screen use and college transitional processes using focus groups, interviews, and anonymous Facebook posts towards the end of the spring semester in 2013. Phase 2 conducted online surveys to document freshman students’ screen use patterns and college transition processes over the following fall semester. This study continued collecting anonymous Facebook posts during Phase 2 for additional insights.


This study was conducted in a large university in the northeastern U.S. The freshman residence hall cluster had two dining halls, and the cluster was away from upper year residence halls or off-campus restaurants. Having no other primary dining options available, these two dining halls were almost exclusively used by freshmen. One of the cashiers confirmed that over 90 percent of weekday diners and over 80 percent of weekend diners were freshmen.

Interviews and focus groups

Interviews and focus groups used convenience sampling and recruited freshmen and sophomores from social science classes plus student employees and managers of the freshmen dining complexes through campus dining group in the spring semester in 2013. The student employees and managers were recruited only for the focus groups. The student managers were upper classmen who had work in the dining halls since their freshman year and participated in the focus groups on behalf of the campus dining during their work hours in their office. The student employees received a small cash payment as they participated in this study outside their dining hall shifts. The other participants received a research participation credit. The interviews intended to understand the adjustment process of freshmen in college while the focus groups primarily explored screen use and social behavior patterns in the dining halls. Each focus group included two or three participants as the topic was highly relevant to their own experiences thus they had much to share. Both were semi-structured and started with the following questions:

Interview questions

  • When you were about to move to campus, what were you worried about?
  • Where did you make friends during your freshman year?
  • How often do you talk to your parents, siblings, and high school friends?
  • How did you handle stress or hardships during your freshman year?
  • What does it feel like when dining alone?

Focus group questions

  • Where did you make friends during your freshman year?
  • If and how did your on-campus friendship change over the semester or over the year?
  • How did the dining halls facilitate opportunities to make new friends during your first semester on campus?
  • What do solitary diners do?

Interviews and focus groups were conducted in a small classroom and lasted about an hour. Focus group and interview sessions were voice-recorded and transcribed into text for analysis.

Facebook confession posts

A Facebook confession page was dedicated to the institution, allowing anyone on campus to post anonymously. This page remained active during this study, generating posts about friendship, romantic relationships, exams, struggles, and various opinions. More than 3,000 Facebook users followed this page as of October 2015. These anonymous Facebook posts were not initially included in this study but added later during Phase 1 as supplementary data after focus group participants indicated many of their peers subscribed. Only original, anonymous posts about social network building or hardships on campus during Phases 1 and 2 (May–December 2013) were used, excluding replies to posts.

Online surveys

Online surveys were conducted in the third, eighth, and twelfth weeks (survey rounds 1, 2, and 3, respectively) during the 15-week-long fall semester in 2013 using Qualitrics. The survey weeks were selected based on the focus groups and interviews as well as on the academic calendar to avoid exam periods while capturing the transitional process. Survey participants were actively recruited through in-person advertisement and three residence hall directors. As attrition over the semester was expected, additional participants were recruited after first and second rounds. Participants received a survey link on the same day of week across survey rounds, and day of week was randomized. An e-mail reminder was sent the night before, an online survey link was e-mailed shortly after dinner time. Upon the completion of the survey, an instant lottery was drawn for a prize. Because the surveys recruited new freshman, the participants of Phase 1 in the spring semester and Phase 2 in the following fall did not overlap. The surveys measured the following categories:

1) Dining locations of the day.
2) Social environments at each meal — whom they ate with (check all apply)

  • — Friends
  • — Acquaintances
  • — Strangers
  • — No one

3) Activities on screen during each meal (check all apply)

  • — Text messaging
  • — E-mail
  • — Social media
  • — Music listening
  • — Homework or work
  • — Checking the time
  • — Other

4) Sense of belonging to college: An adapted 18-item (Cronbach’s α =.80–.88), five-point Likert scale from the Psychological Sense of School Membership (PSSM) (Goodenow, 1993). The original scale was developed for junior high school students but has been adapted for studies using college students (e.g., Pittman and Richmond, 2008). An additional item, “I have made many friends in [the campus] dining hall” was included in the survey to measure if the dining hall afforded social networking building.

5) Mental health: A five-item (Cronbach’s α=.74–.89), four-point Likert scale, MHI-5 (Mental Health Inventory) was used. Receiver operating curve (ROC) analysis results showed that MHI-5 (area under curve, AUC=.892) was compatible to its longer version (MHI-18, AUC=.897) and two other major mental health scales (Berwick, et al., 1991).

6) Demographic information questions: Gender, race and other minorities (e.g., first-generation in college), and hometown resident or international student were controlled for in the analysis.

Attrition during the surveys was a concern. Transition to college could be stressful, which could lead survey participants to drop out. A long survey with many text entries could discourage participants to continue particularly when responding to the survey on a smartphone. The online surveys therefore minimized the number of questions and removed open-ended text responses to reduce attrition. The survey categories 1–3 above were reviewed by several colleagues for face validity. Survey respondents’ GPAs were acquired from the registrar.

Analysis methods

Focus groups, interviews, and Facebook posts were coded using Atlas.ti software for thematic analysis (Vaismoradi, et al., 2013). Hierarchical linear model (HLM) was employed for continuous outcomes, and repeated measures logistics was used for binary outcome variables. IBM SPSS Statistics 23 was used. All models were simplified to include only statistically significant predictor and control variables (p<.05).

Social environments at meals (survey category #2 above) were coded in two ways: 1) Single versus With; and, 2) social relationships. When multiple relationships were selected, the strongest friendship was used — for instance, a meal with a friend and a stranger was coded as ‘with friend’. However, only Single versus With was used in the analyses because those ‘with a stranger’ and URMs ‘with an acquaintance’ were few. Screen use was coded in two ways — first, whether screens were used or not (binomial screen use) for any activities and second, how many screen activities (0–6) were performed during meals (cumulative screen activities). Exclusive ‘checking-the-time’ was not considered screen use in either screen use measure because it would be equivalent to looking at a watch or a clock. Screen use was also tested as an outcome in relation to other explanatory variables because they varied together.



Qualitative data analysis results

Four focus groups of freshmen or sophomores; three groups of student-employees; and, one group of student-managers were recruited. In addition, this study conducted eight interviews with freshman or sophomore participants. Among approximately 3,000 Facebook confession posts created during data collection, 45 relevant posts were collected.

Migrating into a new environment and communal eating

Social integration was what students were most afraid of before moving to campus. An interviewee stated that she had wanted a roommate whom she could go to dinner with. A few participants reported they much appreciated the group dinner their dormitories organized on the first day. Focus groups, interviewees, and confessors indicated that ‘dinner groups’ formed within the first two to four weeks, and such groups would often consist of peers from the same dorm floor or suite. After this stage, those who were not able to be in a dinner group struggled with social integration. Seventeen confession posts mentioned loneliness or lack of friends whereas three posts mentioned struggles with academic transition. A quote below emphasizes the importance of local social capital. Twelve confessors reported experiencing mental health issues such as depression and no desire to live, and five of them also mentioned difficulties in social transition.

“... This school tore me up into little pieces and I can’t wait to get home. Despite that however, I am so incredibly grateful to be here. ... [Friends] are SO important, no matter how supportive family is, they don’t fully understand your struggle nor are they here to provide comfort when needed. ...” — a freshman confessor on Facebook, at the end of initial semester’s final exam period (20 December 2013).

Social networking sites (SNS) may facilitate social group formation before moving to campus. An in-state interviewee met a few incoming peers from her hometown on Facebook and then in person before moving to campus. She and her hometown peers formed a dinner group upon matriculation, which made her less active in social network building during the first semester. This could have occurred to other in-state students as well as international students; therefore, in-state and international student statuses were controlled for in the survey analysis. Freshman dining halls are close to residence halls, across a bridge from classrooms, about a half of a mile to a mile away. Focus groups and interviewees reported they often grabbed breakfast and left instead of eating in or had lunch nearby between classes; and they became feeling less uncomfortable when eating alone later in the initial semester. Yet, eating alone dinner in the dining halls remains something to avoid, confirming Goffman’s (1963) Single-versus-With typology. Two sophomores admitted that they ate snack or had pizza delivered to their dorm room to avoid dining alone. Two confessions described their social isolation with eating alone including the one quoted below. Student dining hall managers and employees confirmed that solo diners were more likely to use their mobile phones and that Single’s more likely came during off-peak hours or chose the less-busy dining hall between the two.

“I haven’t eaten a meal with the company of one or more people in ages. ... I guess it’s just me, my phone, and my computer.” — A Facebook confessor (22 October 2013)

Study participants reported they had often sought social support from family but not from their high school friends. They explained their hometown friends showed off their college life on SNS such as posting pictures of having a good time with new friends. Two interviewees mentioned their hometown friends did not understand their struggles in college. A sophomore interviewee used to call her mother every morning when eating in the freshman dining hall so that she would not eat alone even though her mother would just hear crunching sound from her eating cereals. Another called her older siblings to ask how they made transition to college and get social support from them. Eating together is one common form of social support from on-campus peers. A sophomore formed a dinner group with his dormitory suite mates and ate together throughout the initial semester. He said, “... [We] wouldn’t let each other eat alone for the most part.” Students indicated the dormitory dining halls were still among primary social hubs on campus. Two participants from the dining halls made friends with strangers in the dining halls; yet, this was not common for other students. It was more common to make friends through mutual friends than to become friends with strangers in the dining halls.

Campus diversity

Seven out of the eight interviewees were non-URMs. They felt the campus community was much more diverse than their hometown but greater diversity did not challenge their transition to college. URMs’ transitional process was better described in the confession posts. A confessor described this as a ‘tension’ or a ‘fear’ between black and white students (16 October 2013). URM students with other minority backgrounds (e.g., low-income, first-generation-in-college) perceive additional barriers from affluent URMs on a daily basis and may experience greater struggles. Another confessor wrote, “I dream of being a white, straight, blonde-haired, blue-eyed male, born into a rich and prestigious family on the east coast. I wish I was born into the Kennedy or Bush families. I don’t want to be black, poor, and gay anymore. I hate my life.’ (8 November 2013). After this point of the semester, five other confessors wrote about racism and racial identity.




The following hypotheses reflected the findings from the exploratory and qualitative portions of this study and were tested using the survey responses. The survey documented race to control for in the analysis. However, consistent main and moderating effects of URM emerged. Therefore, the effects of URM are discussed extensively in the results.

H1: Students who ate dinner in the dormitory dining hall will report greater sense of belonging.

H2: Singles in the dining hall will more likely use a screen.

H3: Single diners will report lower degrees of sense of belonging.

H4: Screen-users in the dining hall will indicate lower sense of belonging.

H5a: Single screen-users in the dining halls will report lower sense of belonging.

H5b: Single screen-users in the dining halls will have lower mental-health scores.

H6a: URM students will report lower degrees of sense of belonging.

H6b: URM students will report lower mental health.

H7a: Greater sense of belonging will be correlated with better mental health.

H7b: Greater sense of belonging will be related to higher academic achievement.

H7c. Better mental health will be associated with higher academic achievement.



Survey results

Survey participants

Two hundred and thirteen freshmen completed at least one of three online survey rounds (152, 119, 121 participants in rounds 1, 2, 3, respectively). Sixty-two students completed all three rounds, and 55 students did two. The sample demographics were largely equivalent to the freshman population but had a greater percentage of females and a smaller proportion of international students than the population (Table 1). The institution defined URM as one or any combination of American Indian/Alaska Native, black, native Hawaiian/Pacific islander, or Hispanic/Latino according to its freshman profile.


Table 1: Sample and population descriptive statistics.
VariablesSample (%)Population (%)
Underrepresented minorities (URM)22%22.1%
In-state31% 30.2%
International 6%10.8%
First generation in college13%12.1%
Total number2133,282


The following analyses focus on environmental and behavioral factors during dinner because study participants indicated communal dinner was more important and due to the distance between the dining halls and the main campus, breakfast and lunch diners were scarce among the survey participants.

Initial explorations of survey outcome variables

The original, 18-item, Psychological Sense of School Membership scale results were compared to its revised, 19-item scale with an additional item, “I have made many friends in [the campus] dining hall.” The two versions had equivalent Cronbach alphas (.91) and were highly correlated (r=.995, p=.001, N=387), and the additional item’s correlation coefficient was .31 (p<.001, N=387). This study used the revised 19-item. Correlations among cumulative screen use, sense of belonging, mental health, and the first-semester GPAs were tested including all survey participants regardless of dining locations (Table 2). The two indicators of successful college transition — sense of belonging and mental health — were correlated (r=.68, .59, .55 in rounds 1, 2, 3, respectively, Figure 1) but not with screen use.


Table 2: Means and standard errors of cumulative screen activities (screen), sense of belonging (belong), mental health (mental), and academic achievement (GPA).
Note. The numbers after variable names indicate time of measurement. For example, Belong1 is sense of belonging measure in survey round 1, and GPA1 is GPAs in semester 1. *p<.05, **p<.01 (2-tailed)..
VariableMean (SD)Correlation
1. Screen11.21 (1.24) 1.33**.43**.11-.13-.11.05-.07.07-.30**
2. Screen21.14 (1.18) 1.47**.17.12.09-.13-.02.05-.07
3. Screen31.05 (1.21)  1.15.12 .*-.01
4. Belong13.70 (.52)   1.65**.65**.68**.53**.59**.05
5. Belong23.70 (.59)    1.78**.50**.59**.67**.12
6. Belong33.69 (.48)     1.55**.52**.55**.41**
7. Mental13.00 (.50)      1.58**.65**.00
8. Mental22.91 (.52)         1.71**.03
9. Mental32.96 (.49)        1.25**
10. GPA13.38 (.56)         1



Sense of belonging and mental health during freshman's initial semester using a subsample of participants who completed all three online survey rounds
Figure 1: Sense of belonging and mental health during freshman’s initial semester using a subsample of participants who completed all three online survey rounds.


Survey timing was considered categorical throughout the analyses because outcomes might have a non-linear relationship over the semester. Null growth curve model [1 tests indicated that the odds of screen use were equivalent across the initial semester. No growth patterns were found in cumulative screen activities, sense of belonging or mental health [2]. Lastly, academic achievement analyses used the same mixed model but with semester as the time unit. GPAs increased over five semesters in a linear manner (β=.01, SE=.01, p=.024, CI=[.00, .02]); therefore, semester was treated as continuous. Sense of belonging and mental health were also examined as explanatory variables of academic achievement due to their temporal precedence.

Dinner location

The majority of survey participants had dinner in one of the two freshman dining halls (65.8, 72.7, 58.4 percent in rounds 1, 2, 3, respectively). The interviewees reported that freshman students would have dinner in other locations such as fraternity or sorority houses more often later in the initial semester, which explains the decreased percentage of dining hall visitors in round 3.

Both binomial screen use [3] and cumulative screen activities in the dining hall were equivalent to the ones in other locations. Text messaging was the most common screen activity across settings (M=.44, SD=.50) followed by social media (M=.26, SD=.44) and email (M=.26, SD=.44, Table 3). Text messaging and social media use are discussed in the following analyses because the other activities were insignificant. Only text messaging was associated with dinner location (β=1.10, SE=.33, p=.001, CI=[.46, 1.75]). The odds of text messaging in the dining halls was e^(β)=3.01 times the odds in other non-dining-hall settings. URMs and non-URMs were equivalent in screen use.


Table 3: Percentage of screen users for each screen activity in the dormitory dining halls, non-dining-hall settings, and across settings.
Note: *p<.05, **p<.01.
Screen activityFreshman dining hallOther settingsTotal
Text messaging51%**24%45%
Social media 30%18%27%
Music listening3%14%5%
Other screen use8%14%9%
Binomial screen use66%55%63%


H1: Students who ate dinner in the dormitory dining hall will report greater sense of belonging.

Neither dinner location nor URM had a main effect, but they interacted on sense of belonging [4]. URMs who ate dinner in the freshman dining halls reported lower sense of belonging (β=-.28, SE=.13, p=.025, 95% CI=[-.53, -.04]) across the semester, rejecting H1. Mental health was not associated with dinner location or with URM. The following few sections about social environments and screen use focus on those who had dinner in the dining halls.

Social environments in the dining hall

H2: Singles in the dining hall will more likely use a screen.

Eating alone (Single) had no main effect on the odds of screen use (binomial) and marginally interacted with survey timing. URM had no main effect or interaction with survey timing. However, URM Singles’ odds of screen use was 3.32 times Withs’ or non-URM Singles’ (β=1.20, p<.001). Therefore, H2 held true only for URMs. Singles in the second round reported approximately one more screen activity compared to Single’s in other rounds or to With’s across rounds (β=1.07, SE=.45, p=.019, CI=[.18, 1.96]). Single was not associated with individual screen activities.

H3: Single diners will report lower degrees of sense of belonging.

Single had no main effect on sense of belonging. However, URM Single’s reported lower sense of belonging (β=-.92, SE=.40, p=.022, CI=[-1.71, -.13]) only in the first round compared to With’s (Figure 2). Therefore, H3 held true only for URMs early in the initial semester. Eating alone in the dining hall had no main effect or interaction with URM on mental health.


Social environment in the dining halls and sense of belonging in the first survey round
Figure 2: Social environment in the dining halls and sense of belonging in the first survey round.


Screen use in the dining hall

H4: Screen use in the dining hall will indicate lower sense of belonging.

Sense of belonging was not associated with binomial screen use but increased with cumulative screen activities (β=.07, SE=.03, p=.011, CI=[-.02, .12]), which rejected H4. URMs reported lower sense of belonging (β=-.33, SE=.15, p=.032, CI=[-.63, -.03]) in the same model. Text messaging and social media use were insignificant.

Neither of the screen-use measures had a main effect, but they interacted with URM and survey round on mental health. With the binomial screen use in the model, URMs’ mental health was lower (β=-.57, SE=.19, p=.003, CI=[-.94, -.20]), but its interaction with survey timing canceled out this association in the first and second rounds. On the contrary, URM screen-users reported better mental health (β=.69, SE=.24, p=.005, CI=[.21, 1.17]); and its three-way interaction with survey timing reversed this association in rounds 1 and 2. Consequently, only in the third round, URM non-screen-users’ mental health was noticeably lower while URM screen-users’ was equivalent to non-URMs (Figure 3). The cumulative screen activity analysis generated similar results. Text messaging was insignificant. Social media use had no main effects but interacted with URM and survey timing in a similar trend to Figure 3. URM’s social media use was associated with better mental health ((β=.80, SE=.26, p=.016, CI=[.09, .82]) but only in the third round due to its interaction with URM and survey timing.


The interaction between underrepresented minority (URM) and binomial screen use in the dormitory dining halls on freshmen mental health in the third round using the estimated values controlling for demographic variables
Figure 3: The interaction between underrepresented minority (URM) and binomial screen use in the dormitory dining halls on freshmen mental health in the third round using the estimated values controlling for demographic variables. URMs’ social media use resulted in a similar pattern.


The interaction between screen use and social environments

Screen use and Single in the dining hall were tested together for their interaction effects. The three-way interaction of screen, Single, and URM and their four-way interaction with survey timing were initially explored but removed from the initial model [5] due to statistical insignificance. As binomial and cumulative screen use measures had similar results, only the results of binomial screen use measure are discussed.

H5a: Single screen-users in the dining halls will have lower sense of belonging.

Single, screen use, and URM had no main effects on sense of belonging. URM interacted with Single and with screen use in the dining hall but only in the first round, lowering URM Single’s (β=-1.08, SE=.31, p=.001, CI=[-1.68, -.48]) and UMR screen users’ sense of belonging (β=-.60, SE=.26, p=.019, CI=[-1.10, -.10]). Screen use and Single did not interact on belonging. Considering their interactions with survey round, URM Single’s sense of belonging was significantly lower than others, and URM Single screen-users’ was lowest (Figure 4a and Appendix). H5a was supported only for URMs in the first round. On the contrary, text messaging in the dining halls was linked to greater sense of belonging (β=.12, SE=.05, p=.021, CI=[.02, .23]) across the survey rounds and regardless of URM. Social media use in round 1 was associated with greater sense of belonging (β=.24, SE=.11, p=.036, CI=[.02, .46]) while URM Single’s belonging was lower (β=-.94, SE=.30, p=.002, CI=[-1.53, -.34]) in the same model. It did not interact with Single on sense of belonging.

H5b: Single screen-users in the dining halls will have lower mental-health scores.

Single and screen use had no main effects but interacted with survey timing on mental health, resulting in Single screen-users’ lower mental health in the first round (β=-1.08, SE=.42, p=.011, CI=[-1.92, -.25]). URMs’ mental health was lower in the third round; yet URM screen users’ higher mental health in the same round countered this association, leaving URM non-screen users’ mental health lower than others (Figure 4b and Appendix). H5b was not supported. Single and text messaging were only marginally associated. When tested with social media, Single became insignificant.


The interaction between URM and Single on sense of belonging in round 1
Figure 4a: The interaction between URM and Single on sense of belonging in round 1.



The interaction between URM, Single, and screen use on mental health in round 3
Figure 4b: The interaction between URM, Single, and screen use on mental health in round 3.


Sense of belonging

H6a: URM students will report lower degrees of sense of belonging.
H7a: Greater sense of belonging will be correlated with better mental health.

This and next sections used all survey responses including those who did not eat dinner in the dining hall as sense of belonging and mental health were not dining-location specific variables. URMs’ sense of belonging (M=3.63, SD=.52) was statistically equivalent to their counterparts (M=3.68, SD=.48), which rejected H6a. The higher sense of belonging, the better mental health (β=.45, SE=.05, p<.001, CI=[.35, .54]), holding H7a true. No growth patterns over the semester were found. URMs’ greater sense of belonging (β=.20, SE=.09, p=.037, CI=[.01, .38]) could buffer their lower mental health (β=-.73, SE=.35, p=.037, CI=[-1.42, -.05]). URMs whose sense of belonging was 3.70 — that was about the mean – or higher were estimated to have equivalent or better mental health than non-URMs with same belonging scores (Figure 5a).


The interaction between sense of belonging and URM on mental healthThe interaction between sense of belonging and URM on academic achievement
Figure 5a: The interaction between sense of belonging and URM on mental health.Figure 5b: The interaction between sense of belonging and URM on academic achievement.


H7b: Greater sense of belonging will be related to higher academic achievement.

Since sense of belonging had no growth patterns, individuals’ mean sense of belonging score across the survey rounds was used to examine its relation to academic achievement [6]. URMs’ GPAs were lower (β=-1.59, SE=.54, p=.004, CI=[-2.66, -.51]) than their peers. Sense of belonging had no main effect but interacted with URM on academic achievement (β=.36, SE=.15, p=.015, CI=[.07, .65]). The slopes in Figure 5b met at 4.4 sense-of-belonging score. H7b held true only for URMs.

Mental health

H6b: URM students will report lower mental health.
H7c.: Better mental health will be associated with higher academic achievement.

URMs’ mean mental health (M=2.93, SD=.54) was equivalent to their counterparts (M=2.97, SD=.46), rejecting H6b. Similar to sense of belonging, mental health did not have a growth pattern. Therefore, individuals’ mean mental-health scores were used to test the association between mental health in the initial semester and academic achievement over the five semesters (M=2.96, SD=.48). Mental health had no main effect on academic achievement, and URMs’ higher mental health was marginally associated with an increase in GPA. H7c. was not supported. Table 4 summarizes hypothesis test results.


Table 4: Summary of hypothesis tests.
Dinner location
H1: Students who ate dinner in the dormitory dining hall will report greater sense of belonging.Rejected
Social environment in the dining hall
H2: Singles in the dining hall will more likely use a screen.Supported only for URMs
H3: Single diners will report lower degrees of sense of belonging.Supported only for URMs early in the initial semester (round 1)
Screen use in the dining hall
H4: Screen use in the dining hall will show lower sense of belonging.Rejected
Social environment and screen use in the dining hall
H5a: Single screen-users in the dining halls will report lower sense of belonging.Supported only for URMs early in the initial semester (round 1)
H5b: Single screen-users in the dining halls will have lower mental-health scores.Rejected
Underrepresented minority (URM) 
H6a: URM students will report lower degrees of sense of belonging.Rejected
H6b: URM students will report lower mental health.Rejected
The relationships among sense of belonging, mental health, and academic achievement
H7a: Greater sense of belonging will be correlated with better mental health.Supported
H7b: Greater sense of belonging will be related to higher academic achievement.Supported only among URMs
H7c: Better mental health will be associated with higher academic achievement.Rejected



This study examined the transition of freshmen to college, focusing on dormitory dining halls where online and face-to-face interaction opportunities would coexist. The present study found the dormitory dining halls were still important for daily social activities and social capital building on campus, supporting previous research about communal eating (Alexander, et al., 1977; Kniffin, et al., 2015; Rapoport, 2005). Yet, freshmen were afraid of dining there alone. Moreover, URMs’ sense of belonging was lower when having dinner in the dining hall than when eating somewhere else, indicating that the dining hall itself may exacerbate feelings of isolation for URMs. The likelihood of screen use in the dining hall was much higher for solitary URMs than for URMs with peers or non-URMs. Furthermore, solitary URM diners who used a screen reported significantly lower sense of belonging early in the initial semester. This study found small positive effects of screen use, especially text messaging. However, their magnitudes were much smaller than URMs. These interactions between URMs, use of communication technology, and social isolation represent a unique contribution to the field.

Sense of belonging and mental health were moderately correlated. The effect of belonging on mental health was greater for URMs, and greater sense of belonging was associated with URMs’ greater academic achievement. Note these correlations were not mean causal because successful academic adjustment could boost the other two outcomes even before students received initial semester GPAs. Non-URMs’ belonging or mental health was not correlated with academic achievement.

This study has several major limitations. First, the survey sample size was small and used one college campus in a small college town. Second, surveys were conducted only three times in the semester, and the questions were limited to the meals of the survey day to increase the accuracy of the answers while reducing attrition. This, in turn, might not encompass students’ general social behavior in the dining halls, especially those who participated only once or twice. Third, the surveys were not able to document the dynamic between screen use and in-person interaction. If one used a screen while waiting for peers to arrive, for example, she was categorized as non-solitary screen-user even though she was temporarily alone until her peers arrived. Fourth, screen use activities were not documented in detail such as how long and for what the survey participants used a screen. Future studies are encouraged to ask whom they interacted with on a screen to better understand underlying mechanisms.

Despite the limitations, this study offers several findings of potential interest and suggests avenues for future research. First, the associations between screen use and college transition may be moderated by contextual factors including settings, social environments, and individual background. Other college campuses, urban settings, and workplace can be among potential future study sites. Second, the moderating effects of URM and temporal dimensions on the relations between screen use and college transition are a new finding. More patterns emerged among URM students who were more likely vulnerable, and the patterns varied during the semester. Other temporal dimensions, such as peak vs. off-peak and how long one stayed in the dining hall, are worth investigation. Third, this study found small positive associations of social media and text messaging in the dining halls on sense of belonging controlling for solitary dining. Lastly, Goffman’s (1963) Single vs. With typology held true with the presence of screens both in quantitative and qualitative work of the present study.




Screens are now a new type of environment integrated into our daily lives. One of the key contributions of the present study is how screens interact with other contextual factors — specifically, the interactions among solitary dining, screen, and URM. Instead of weakening the influence of non-screen contexts, screens may moderate or perhaps reinforce the effects of contextual factors. The roles of screens in complex human ecology need further explorations for a more comprehensive knowledge of our social well-being. End of article


About the author

Dr. Giyoung Park is an environmental psychologist and registered architect and studies human well-being in relation to environmental design. She was a graduate student in human behavior and design at Cornell University when she conducted this study. She is currently a senior design researcher at HKS Architects.
E-mail: gp249 [at] cornell [dot] edu



I am grateful for Professor Gary W. Evans at Cornell University who guided this doctoral research work and inspired me in many ways. I also thank my research assistants who helped this research work. This work was supported by Grace Dimelow, Orrilla Wright Butts, Home Economics Extension, and Jean Failing Fellowships, and Student and Academic Services, both from Cornell University.



1. Repeated measures logistic regression estimates log-odds or logit — that is, the natural log value of the odds of an event — is p/(1-p) where p is the probability. Denoting screenik for an individual k’s screen use at time point i, the null initial growth model is:

2. The sense of belonging, for example, of an individual k at time point i would be:
Level 1: belongingikok1k(roundik)+εik
Level 2: βok000k
γ00 is a parameter intercept, and γ10 is the parameter variances among survey rounds. βok and β1k are the intercept and the survey-round coefficient of the individual k; ζ0k and ζ1k are the deviations from the population intercept and survey-round coefficient.

3. The initial model was:
logit (screenik)=βok1k(roundik)+β2k(locationik)+β3k(locationik)( roundik)+β4k(URMk)+β5k(URMk)( roundik)+β6k(locationik)(URMk)+β7k(locationik)(URMk)( roundik)+εik

4. The initial time-varying mixed model for the sense of belonging for individual k at survey-round i is:
Level 1: belongingikok1k(roundik)+εik
Level 2: βok0001(locationik)+γ02(URMk)+γ03(locationik)(URMk)+ζ0k
β1k = γ1011(locationik)+γ12(URMk)+γ13(locationik)(URMk)+ζ1k

5. The initial growth curve model for the sense of belonging for individual k at survey-round i is:
Level 1: belongingikok1k(roundik)+εik
Level 2: βok0001(screen.biik)+γ02(Singleik)+γ03(URMk)+γ04(screen.biik)(Singleik)+γ05(screen.biik)(URMk)+γ06(Singleik)(URMk)+ζ0k

6. The initial growth model was:
Level 1: GPAjkok1k(semesterjk)+εjk
Level 2: βok0001(belongk)+γ02(URMk)+γ03(belongk)(URMk)+ζ0k



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Appendix: The associations between Single vs. With and screen use in the dining hall on (A) sense of belonging and (B) mental health
Note: Survey round 3 was the reference level. *p<.05, **<.01. URM means underrepresented minority.
 (A) Sense of belonging(B) Mental health
ParameterβSEdfSig.95% CIβSEdfSig.95% CI
[Round=1]-.11.08187.76.200-.27.06 -.16.11116.79.171 -.38.07
URM × [Round=1].34.20213.89.084-.05.73.62*.26128.
URM × [Round=2].14.17 174.70.429-.20.48 .52*.23114.
Single × [Round=1].22.17220.84.180-.10.55 .25.30192.54.403.34.85
Single × [Round=2].09.14183.67.513-.19.37-.88.46174.21.055-1.78.02
Screen × [Round=1].21.11201.50.054-.
Screen × [Round=2].01.12192.22.904-.
Single × URM.11.25297.70.641-.37.60      
Single × URM × [Round=1]-1.08**.31219.86.001-1.68-.48      
Single × URM × [Round=2]-.07.36299.24.852-.78.65      
Single × Screen      .25.28192.20.374-.31.81
Single × Screen × [Round=1]      -1.08*.42201.65.011-1.92-.25
Single × Screen × [Round=2]      .89.50169.60.075-.091.88
Screen × URM.23.18242.45.204-.13.58.77**.24176.70.001.301.23
Screen × URM × [Round=1]-.60*.26239.37.019-1.10-.10 -.84*.33143.74.012-1.50-.19
Screen × URM × [Round=2] -.10.25213.23.687-.60.40-.80*.34180.14.019-1.46-.13


Editorial history

Received 3 March 2018; revised 22 September 2018; accepted 22 October 2018.

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This paper is licensed under a Creative Commons Attribution 4.0 International License.

Eating (alone) with Facebook: Digital natives’ transition to college
by Giyoung Park.
First Monday, Volume 23, Number 11 - 5 November 2018

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