In the digital era, smartphones have deeply integrated into the lives of nursing students, reshaping daily routines and exerting potential impacts on their well-being. However, the intricate and inconsistent associations among smartphone use, sleep quality, and depressive symptoms necessitate in-depth longitudinal investigation, especially considering nursing students' future critical roles in healthcare.

This thesis comprises two complementary studies. Study Ⅰ , a three-year longitudinal research initiated in 2018, involved 1,716 nursing freshmen from three Chinese public medical universities, while Study Ⅱ adopted a qualitative approach.

Study Ⅰ was reported in three interconnected papers, each leveraging different phases of the longitudinal dataset. Paper Ⅰ (Baseline Analysis): Employing stratified cluster sampling, this paper evaluated the self - rated frequencies of 12 smartphone activities in the past week and measured depressive symptoms using the Patient Health Questionnaire (PHQ-9). Among the sample, 83.0% (1,424) were female, with a mean age of 18.90±1.39 years. Principal component analysis (PCA) identified two distinct usage patterns: “entertainment pattern” and “communication pattern”. Logistic regression, controlling for socio-demographic and smartphone use covariates, revealed that the “ communication pattern” significantly increased the odds of moderate and above depressive symptoms (AOR = 1.529; 95% CI = 1.286–1.818; P < .001).

Paper Ⅱ (Baseline - Extended Analysis): Also based on the baseline data, this  paper  explored  the  relationships  among  depressive  symptoms, problematic smartphone use, and cumulative risk factors. By constructing a composite risk score through comprehensive assessment of individual, family, and social factors, it demonstrated that an increase in risk factors was significantly associated with higher depressive symptom scores (F = 322.229, df = 1, P < .001). Additionally, the combination of poor sleep quality and problematic smartphone use formed a high - risk cluster linked tomore severe depressive symptoms (P < .001).

Paper Ⅲ  (Longitudinal Trajectory Analysis): Utilizing group-based trajectory modelling (GBTM), this paper traced the three-year trajectories of depressive symptoms, problematic smartphone use, and sleep quality. Logistic  regression  analysis  showed  that  persistent  high  levels  of problematic smartphone use (OR = 50.15, 95% CI: 24.71–101.80, P < .001), poor sleep quality (OR = 5.59, 95% CI: 1.15–27.29, P < .05), and their co - occurrence (OR = 128.96, 95% CI: 43.80 – 379.69, P < .001) significantly influenced depressive symptom trajectories, with the co - occurrence having the most detrimental effect.

In Study Ⅱ, Paper Ⅳ employed semi-structured focus-group interviews and inductive content analysis to explore nursing students’ experiences regarding smartphone use, sleep, and emotions. Four key themes emerged: 1) Narratives of loss of control at the fingertips: a spectrum of behaviors from identity transformation to everyday indulgence, 2) A virtual habitat in the palm of your hand: the smartphone as an extended space for emotion and cognition,  3)  The  double-edged  sword  effect  of  smartphone  use: psychological tidal fluctuations and physiological load accumulation, and 4) The emotional black hole of late-night screens: the closed-loop devouring effect of smartphone - sleep - emotion. These themes vividly illustrated the complex interplay among smartphone use, sleep, and mental health.

Collectively,  these  studies,  progressing  from  cross-sectional  baseline analysis to longitudinal trajectories and qualitative insights, systematically investigated the multifaceted relationships among smartphone use, sleep quality, and depressive symptoms in nursing students. The findings contribute to theoretical understanding and provide practical guidance fordeveloping targeted interventions to enhance nursing students' mental health.