Jia Dong, Hailong Zhang, Jianjian Zhao, Ruikai Yuan
The results indicated that higher short-video music consumption prospectively predicted lower attentional control across both intervals (βs = -0.17 and -0.12); better attentional control predicted lower subsequent academic procrastination (βs = -0.23 and -0.14) and higher subsequent academic flow (βs = 0.18 and 0.14); and higher academic procrastination predicted lower subsequent academic flow (βs = -0.20 and -0.14). Bootstrapped indirect effects from short-video music consumption to academic procrastination (βs = 0.024) and academic flow (βs = -0.024) through attentional control were significant, as was the indirect effect from attentional control to academic flow through procrastination (βs = 0.031).
INTRODUCTION: Short-video platforms have become deeply embedded in Chinese university students' daily routines, and the music delivered through algorithmically curated short clips differs in important ways from traditional, self-selected music listening.
METHODS: The present study tested whether algorithm-driven short-video music consumption is prospectively associated with attentional control, academic procrastination, and academic flow across one academic term. A three-wave longitudinal survey was conducted across one academic term, with measurement intervals of approximately 6 weeks. Chinese university students (N = 920 at Time 1; N = 820 retained at Time 3) completed measures of short-video music consumption, attentional control, academic procrastination, and academic flow at each wave. An observed-variable cross-lagged panel model was estimated to examine autoregressive stability and hypothesized cross-lagged paths, with reverse paths and baseline daily short-video use included for robustness.
RESULTS: The results indicated that higher short-video music consumption prospectively predicted lower attentional control across both intervals (βs = -0.17 and -0.12); better attentional control predicted lower subsequent academic procrastination (βs = -0.23 and -0.14) and higher subsequent academic flow (βs = 0.18 and 0.14); and higher academic procrastination predicted lower subsequent academic flow (βs = -0.20 and -0.14). Bootstrapped indirect effects from short-video music consumption to academic procrastination (βs = 0.024) and academic flow (βs = -0.024) through attentional control were significant, as was the indirect effect from attentional control to academic flow through procrastination (βs = 0.031).
DISCUSSION: The findings highlight the value of distinguishing intentional music listening from algorithmically delivered short-video music consumption when considering students' academic self-regulation in contemporary digital media environments.