Feelings of Belonging May Indicate Students’ Risk of Depression

Social support is essential to well-being, but research suggests that this connection can manifest in many different ways, each with its own unique influence on mental health. In the case of depression, our sense of belonging may serve as a particularly strong predictor of well-being, reported Janine M. Dutcher (Carnegie Mellon University) and colleagues in Psychological Science. This may be especially true for college students, whose risk of developing depression has almost doubled over the past 20 years, Dutcher and colleagues noted. 

“Belonging is important throughout the life span, but feeling like one belongs is particularly important during life transitions, such as the first year of college,” the researchers wrote. “This connection to the university community is often referred to as ‘school belonging,’ which is thought to be the extent to which students feel personally accepted, respected, included, and supported by others in the school social environment.” 

Through a series of three studies, Dutcher and colleagues found that students’ daily sense of belonging at the beginning of their freshman semester predicted their depression symptoms at the end of the semester even after controlling for current depression symptoms, social interaction, and feelings of social fit or loneliness. 

During each study, students began the semester by self-reporting their symptoms of depression, sense of social fit, and feelings of belonging. Belonging was measured by asking participants to rate one simple statement on a scale from 1 to 7: “Today, I feel like I belong at [school name].” 

More on social connectedness and well-being


In the initial exploratory study of 157 students and the first confirmatory study of 121 students, participants then reported their sense of belonging at the end of each day for one week at the beginning, middle, and end of the semester. In the second confirmatory study, 172 students did this reporting for one week at the beginning and end of both the winter and spring semesters. 

During assessment weeks, participants also completed measures of social interaction, social fit, and symptoms of depression four times each day. 

This method, known as ecological momentary assessment, allows participants to report their feelings as they happen, Dutcher and colleagues explained. This can help generate more accurate data—particularly among people with depression, who have been found to recall events more negatively than they were experienced at the time. 

In all three studies, students’ feelings of belonging were found to predict their symptoms of depression as much as four months in advance, with students who reported lower belonging earlier in the semester becoming more depressed by the middle and end of the semester.  

Feelings of loneliness, but not the number of social interactions that students reported having each day, were also found to predict symptoms of depression. This suggests that depression may be more closely related to how we perceive our relationships and position within a community than to whether or not we are socializing with others, the researchers noted. 

“These daily feelings of belonging provide an important signal for changes in depressive symptomatology,” Dutcher and colleagues wrote. “This could have important implications for interventions to mitigate depressive symptoms in first-year university students because early detection of risk can allow for both earlier intervention and more proactive preventative strategies.” 

Reference: Dutcher, J. M., Lederman, J., Jain, M., Price, S., Kumar, A., Villalba, D. K., Tumminia, M. J., Doryab, A., Creswell, K. G., Riskin, E., Sefdigar, Y., Seo, W., Mankoff, J., Cohen, S., Dey, A., & Creswell, J. D. (2022). Lack of belonging predicts depressive symptomatology in college students. Psychological Science, 33(7), 1048–1067. https://doi.org/10.1177/09567976211073135  

Feedback on this article? Email [email protected] or login to comment.


APS regularly opens certain online articles for discussion on our website. Effective February 2021, you must be a logged-in APS member to post comments. By posting a comment, you agree to our Community Guidelines and the display of your profile information, including your name and affiliation. Any opinions, findings, conclusions, or recommendations present in article comments are those of the writers and do not necessarily reflect the views of APS or the article’s author. For more information, please see our Community Guidelines.

Please login with your APS account to comment.