Article ; Online: Community belongingness during COVID-19 predicts anxiety and depression treatment change in college students.
Psychotherapy research : journal of the Society for Psychotherapy Research
2022 Volume 33, Issue 1, Page(s) 118–129
Abstract: Objective: Community belongingness has been shown to be related to mental health outcomes in college students; however, little work has evaluated whether community belongingness impacts treatment change, especially during the COVID-19 pandemic, when ... ...
| Abstract | Objective: Community belongingness has been shown to be related to mental health outcomes in college students; however, little work has evaluated whether community belongingness impacts treatment change, especially during the COVID-19 pandemic, when social isolation and mental health concerns are exacerbated. Accordingly, the current study evaluated community belongingness as a predictor of treatment change for anxiety and depression in a university counseling center. Method: Participants included 516 young adults with clinical levels of anxiety or depression who attended at least two individual therapy sessions at a university counseling center during fall 2020. Participants completed broad measures of psychosocial functioning at each session. Results: Paired-samples Conclusion: These results suggest improving community belongingness on college campuses may be a way to buffer mental health and improve treatment outcomes for students seeking psychological services. Specific clinical and educational recommendations for ways to improve community belongingness are discussed. |
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| MeSH term(s) | Humans ; Male ; Female ; Young Adult ; Universities ; Students/psychology ; COVID-19/epidemiology ; Anxiety/psychology ; Anxiety/therapy ; Depression/psychology ; Depression/therapy ; Community Integration/psychology ; Social Isolation ; Mental Health/statistics & numerical data ; Counseling ; Treatment Outcome |
| Language | English |
| Publishing date | 2022-05-03 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 1080323-3 |
| ISSN | 1468-4381 ; 1050-3307 |
| ISSN (online) | 1468-4381 |
| ISSN | 1050-3307 |
| DOI | 10.1080/10503307.2022.2071654 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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