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Background and objective Short-form video (SFV) platforms are widely used among university students and provide brief, personalized, and rewarding content. This may encourage repeated scrolling, frequent phone checking, and difficulty maintaining sustained academic focus. This study aimed to describe the proportion of King Saud University students reporting high SFV reward expectancy in this sample, and to examine its association with study-session fragmentation and self-reported deep-work impairment. Methods A cross-sectional analytical study was conducted among students at King Saud University, Riyadh, Saudi Arabia. Data on SFV reward expectancy, study-session fragmentation, and deep-work impairment were collected using a structured electronic questionnaire. Pearson's and Spearman's correlations were used for bivariate analysis, and hierarchical multiple linear regression was used to estimate associations adjusted for demographic, academic, and device-use covariates, with standardized coefficients, 95% confidence intervals, collinearity diagnostics, and residual checks reported. Results A total of 514 students were included in the analysis. High SFV reward expectancy was reported by 58.4% of respondents (95% CI: 54.1–62.6%). SFV reward expectancy was positively correlated with study-session fragmentation ( r = 0.646, 95% CI 0.593–0.694, p < 0.001) and with deep-work impairment ( r = 0.518, 95% CI 0.452–0.578, p < 0.001). In fully adjusted models, each one-point increase in SFV reward expectancy was associated with a 0.441-point higher fragmentation score (95% CI 0.379–0.503, β = 0.499, p < 0.001) and a 0.357-point higher deep-work impairment score (95% CI 0.288–0.426, β = 0.431, p < 0.001). Associations were attenuated but remained statistically significant after adjustment. Conclusion High SFV reward expectancy was commonly reported in this sample and was significantly associated with greater study-session fragmentation and greater self-reported deep-work impairment, independent of measured demographic, academic, and device-use characteristics. Because the design is cross-sectional and all measures were self-reported, these findings are associative and cannot establish temporal order or causation. These findings highlight the need for longitudinal and intervention research using objective measures to evaluate the underlying mechanisms and to inform strategies promoting healthier technology use among university students.
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Alsahly et al. (2026) studied this question.
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