Research on fatigue symptom trajectories and influencing factors among nursing undergraduates

Fatigue among nursing undergraduates significantly impacts academic performance, clinical practice, and mental health. Previous studies have predominantly employed cross-sectional designs, overlooking the dynamic and heterogeneous nature of fatigue progression. Identifying distinct fatigue trajectories and their predictors is crucial for developing targeted interventions. This study sought to identify distinct fatigue symptom trajectories among nursing students and to investigate the factors linked to these patterns.

This study recruited 260 nursing undergraduates at T1 (Week 2 of the semester). Follow-up assessments were conducted at T2 (Week 10 of the semester) and T3 (Week 18 of the semester).Fatigue symptoms were measured using the Multidimensional Fatigue Inventory (MFI).Latent Class Growth Model(LCGM) was employed to identify distinct trajectories of fatigue symptoms among the nursing undergraduates.

LCGM identified three fatigue symptom trajectory classes: High-fatigue-decline group (18.5%), Medium-fatigue-ascending group (45.4%), and Low-fatigue-ascending group (36.1%). Multinomial logistic regression indicated that, at T3, nursing undergraduates with anxiety (OR = 3.233) or insomnia (OR = 2.425)were more likely to be classified into the medium-fatigue-ascending group compared with those in the low-fatigue-ascending group. Furthermore, male students were more likely to be categorized into the medium-fatigue-ascending group rather than the high-fatigue-decline group (OR = 3.356).

Nursing undergraduates display heterogeneous fatigue trajectories, shaped significantly by mental health and sleep quality, with predictors varying across trajectory classes. Tailored interventions based on these patterns are recommended to improve fatigue management and mental health support in nursing education.

Not applicable.