Time Management Behavior Structural Equation Model Predicts Global Sleep Quality in Traditional Entry University Students

ABSTRACT

Background

Poor sleep is commonplace among traditional entry university students. Lifestyle modifications, such as time management behaviors, may improve sleep quality by allocating sufficient time for sleep and mitigating stress-associated sleep latency inefficiencies.

Purpose

The purpose of our study was to evaluate time management behaviors as predictors of sleep quality in traditional entry university students. We hypothesized that time management behaviors would predict perceived control of time, which in turn, would predict global sleep quality.

Methods

A cross-sectional convenience sample of university students (n = 302) completed a 73-item instrument comprised the Pittsburgh Sleep Quality Index and the Time Management Behavior scale. Model building procedures included exploratory factor analysis, confirmatory factor analysis, and structural equation modeling.

Results

Our specified model identified significant paths between setting goals and priorities (β = .261; p = .012), mechanics of time management (β = .210; p = .043) and preference for organization (β = .532; p < .001) for perceived control of time (R² = .300 p < .001). We further identified a significant path between perceived control of time and global sleep quality (R² = .196, p = .022).

Discussion

Our study suggests that time management behaviors are associated with global sleep quality.

Translation to Health Education Practice

Health education interventions addressing sleep quality of traditional entry university students should consider incorporating time management behaviors.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Heart, Lung, & Blood Institute, National Institutes of Health, Bethesda, MD, under Grant [1K01HL145128]; National Institutes of Health Loan Repayment Program, Division of Loan Repayment, National Institutes of Health, Bethesda, MD, under Grant [L30HL15969].