Sleep‐Timing Types and Weekend Catch‐Up Sleep Patterns Associated With Above‐Threshold Anxiety Symptoms in College Students: 28‐Day Objective Monitoring

The study had two core aims: (1) to identify data-driven sleep-wake timing and 4-week weekend catch-up sleep ratio (WCS ratio) patterns among college students through 28-day objective monitoring; (2) to quantify the combined associations between multidimensional sleep profiles and anxiety symptoms. A two-phase design was used. We recruited 182 undergraduates (mean age = 19.3, SD = 1.09) for 28-day millimetre-wave radar sleep tracking and psychological tests. Study 1 adopted k-means and DTW time-series clustering, extracting two sleep-wake timing patterns (Post-midnight, n = 161; Pre-midnight, n = 21) and two WCS-ratio trajectories (decreasing, n = 90; increasing, n = 92), regarded as exploratory short-term behavioural patterns. Study 2 performed logistic regression, sensitivity tests, and cumulative indicator analysis. Key results: (1) Poor sleep quality (OR = 1.98, 95% CI [1.47, 2.66]), shorter weekday sleep duration (OR = 0.52, 95% CI [0.29, 0.92]), pre-midnight sleep timing (OR = 9.84, 95% CI [2.01, 48.06]), an increasing WCS-ratio pattern (OR = 3.88, 95% CI [1.14, 13.23]), and severe negative life events (OR = 6.22, 95% CI [1.24, 31.34]) predicted higher anxiety score. Sleep quality, weekday sleep duration, and life stress remained robust in sensitivity analyses; continuous sleep and WCS indicators showed no stable predictive effects. (2) Cumulative analysis found a non-linear threshold effect: symptoms of anxiety tend to rise when multiple sleep and stress factors co-occur. These findings suggest that monitoring multifaceted sleep-related behaviours, especially their long-term dynamics, may aid in identifying college students with elevated anxiety symptoms.