Depression trajectories and their associations with academic performance and sleep patterns among first-year college students

BACKGROUND: Depressive symptoms have been on the rise among young adults, with the transition to college, particularly the first year, being a critical period of vulnerability. Despite prior research on depression trajectories in college students, limited longitudinal studies have explored unique depressive symptom trajectory groups among first-year students and their associations with academic achievement (GPA), sleep patterns, and whether sociodemographic factors are associated with certain trajectories. METHODS: This study analyzed a pre-existing dataset that was collected over two waves from a private university (spring semester 2017 and 2018). The final pooled sample resulted in first-year undergraduate students (N = 271) who reported on their depressive symptoms (CES-D scale) at the start and end of the semester, signed a release record for their fall and spring term GPA, and provided continuous sleep data across the academic spring term with Fitbits. K-means + + clustering was conducted to form depressive symptom trajectory groups. ANOVAs, Watson-Williams, and Dunnett's post hoc comparison tests were employed to examine how the resulting trajectory groups were associated with GPA and sleep outcomes (bedtime, waketime, total sleep time, time in bed). Associations between sociodemographic variables and trajectory groups were investigated using chi-square tests. RESULTS: K-means + + clustering identified four trajectory groups: low-stable (n = 109), increasing (n = 72), decreasing (n = 51), and high-stable depressive symptoms (n = 39). The low-stable and decreasing group had a higher spring term GPA (M = 3.44 and M = 3.39, respectively) compared to the increasing and high-stable groups (M = 3.22 and M = 3.18, respectively). The low-stable group generally had an earlier wake time and bedtime, greater total sleep time and time in bed, relative to the decreasing and increasing trajectory groups. Gender, ethnicity, international student status, and first-generation student status were not associated with trajectory groups. CONCLUSIONS: Consistent with prior work, there are unique depression trajectory groups among first-year college students that represent stability and change of depressive symptoms over the course of a spring semester. Favorable trajectories (low-stable and decreasing symptoms) are associated with better academic performance and sleep habits.

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Publication Details

Journal
BMC Psychology
Published
2026-05-02
DOI
https://doi.org/10.1186/s40359-026-04404-w
Primary Topic
Grit, Self-Efficacy, and Motivation
Type
article
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article

Depression trajectories and their associations with academic performance and sleep patterns among first-year college students

Kasey G. Creswell, Michael Tumminia, Janine M. Dutcher, Sheldon Cohen et al.
BMC Psychology
Grit, Self-Efficacy, and Motivation
article

Depression trajectories and their associations with academic performance and sleep patterns among first-year college students

Kasey G. Creswell, Michael Tumminia, Janine M. Dutcher, Sheldon Cohen, Daniella K. Villalba, Kirk Warren Brown, Stephen Price, Asal Yunusova, Caitlin Huang, Kunal Joshi, J David Creswell
article en

Abstract

BACKGROUND: Depressive symptoms have been on the rise among young adults, with the transition to college, particularly the first year, being a critical period of vulnerability. Despite prior research on depression trajectories in college students, limited longitudinal studies have explored unique depressive symptom trajectory groups among first-year students and their associations with academic achievement (GPA), sleep patterns, and whether sociodemographic factors are associated with certain trajectories. METHODS: This study analyzed a pre-existing dataset that was collected over two waves from a private university (spring semester 2017 and 2018). The final pooled sample resulted in first-year undergraduate students (N = 271) who reported on their depressive symptoms (CES-D scale) at the start and end of the semester, signed a release record for their fall and spring term GPA, and provided continuous sleep data across the academic spring term with Fitbits. K-means + + clustering was conducted to form depressive symptom trajectory groups. ANOVAs, Watson-Williams, and Dunnett's post hoc comparison tests were employed to examine how the resulting trajectory groups were associated with GPA and sleep outcomes (bedtime, waketime, total sleep time, time in bed). Associations between sociodemographic variables and trajectory groups were investigated using chi-square tests. RESULTS: K-means + + clustering identified four trajectory groups: low-stable (n = 109), increasing (n = 72), decreasing (n = 51), and high-stable depressive symptoms (n = 39). The low-stable and decreasing group had a higher spring term GPA (M = 3.44 and M = 3.39, respectively) compared to the increasing and high-stable groups (M = 3.22 and M = 3.18, respectively). The low-stable group generally had an earlier wake time and bedtime, greater total sleep time and time in bed, relative to the decreasing and increasing trajectory groups. Gender, ethnicity, international student status, and first-generation student status were not associated with trajectory groups. CONCLUSIONS: Consistent with prior work, there are unique depression trajectory groups among first-year college students that represent stability and change of depressive symptoms over the course of a spring semester. Favorable trajectories (low-stable and decreasing symptoms) are associated with better academic performance and sleep habits.

BMC Psychology
Carnegie Mellon University (US)
Openalex Percentile: Top 9%
Grit, Self-Efficacy, and Motivation
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