Development and validation of a nomogram to predict short video addiction among nursing students in China

There is a high prevalence of short video addiction (SVA) among Chinese nursing students. This study was aimed at establishing a risk prediction model for SVA among this population. Two rounds of cross-sectional survey were performed, with 620 nursing students from Jinzhou included in T1 (July 2024) survey to perform model establishment and internal validation, and 293 nursing students from Guangzhou included in T2 (February, 2025) survey to perform external validation. Participants were invited to complete a panel of questionnaires to measure SVA using the Short Video Addiction Scale (SVAS) and 22 candidate SVA predictors. A visual nomogram was plotted and its performance was evaluated using area under the receiver operating characteristics curve (AUC), calibration curve and decision curve analysis (DCA). A sex-based subgroup analysis was also conducted. A 31.3% SVA prevalence was revealed among Chinese nursing students. Academic stress, social interaction anxiety, sleep disorders, depressive symptoms, anxiety symptoms, and whether from a single-parent family were identified as significant factors for SVA nomogram construction. The nomogram performed well in the training cohort, internal validation cohort, and external validation cohort as evidenced by the AUC (0.809, 0.831, and 0.839, respectively), calibration curves and DCA curves. Subgroup analysis showed that this model performed well in both male and female nursing students. Our present study developed a predictive nomogram for SVA among Chinese nursing students via integration of six salient predictors, including academic stress, social interaction anxiety, sleep disorders, depressive symptoms, anxiety symptoms, and whether from a single-parent family. This nomogram is potentially useful for universities and educators in identifying nursing students more likely to develop SVA and in developing tailored preventive interventions to reduce the prevalence of this condition.

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Publication Details

Journal
BMC Nursing
Published
2025-06-06
DOI
https://doi.org/10.1186/s12912-025-03325-0
Citations
2
Primary Topic
Mind wandering and attention
Type
article
Field-Weighted Citation Impact
2.86
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article

Development and validation of a nomogram to predict short video addiction among nursing students in China

Liyuan Tian, Hongliang Dai, Wenfeng Xu, M. Cui
2 citations
BMC Nursing
Mind wandering and attention
2.86
article

Development and validation of a nomogram to predict short video addiction among nursing students in China

Liyuan Tian, Hongliang Dai, Wenfeng Xu, M. Cui
article en
2 citations

Abstract

There is a high prevalence of short video addiction (SVA) among Chinese nursing students. This study was aimed at establishing a risk prediction model for SVA among this population. Two rounds of cross-sectional survey were performed, with 620 nursing students from Jinzhou included in T1 (July 2024) survey to perform model establishment and internal validation, and 293 nursing students from Guangzhou included in T2 (February, 2025) survey to perform external validation. Participants were invited to complete a panel of questionnaires to measure SVA using the Short Video Addiction Scale (SVAS) and 22 candidate SVA predictors. A visual nomogram was plotted and its performance was evaluated using area under the receiver operating characteristics curve (AUC), calibration curve and decision curve analysis (DCA). A sex-based subgroup analysis was also conducted. A 31.3% SVA prevalence was revealed among Chinese nursing students. Academic stress, social interaction anxiety, sleep disorders, depressive symptoms, anxiety symptoms, and whether from a single-parent family were identified as significant factors for SVA nomogram construction. The nomogram performed well in the training cohort, internal validation cohort, and external validation cohort as evidenced by the AUC (0.809, 0.831, and 0.839, respectively), calibration curves and DCA curves. Subgroup analysis showed that this model performed well in both male and female nursing students. Our present study developed a predictive nomogram for SVA among Chinese nursing students via integration of six salient predictors, including academic stress, social interaction anxiety, sleep disorders, depressive symptoms, anxiety symptoms, and whether from a single-parent family. This nomogram is potentially useful for universities and educators in identifying nursing students more likely to develop SVA and in developing tailored preventive interventions to reduce the prevalence of this condition.

BMC NursingVol. 24(1)
Jinzhou Medical University (CN)
Openalex Percentile: Top 10%
Mind wandering and attention
2.86
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Development and validation of a nomogram to predict short video addiction among nursing students in China — Liyuan Tian, Hongliang Dai, et al. · BMC Nursing (2025) | TGRS Research Map | TGRS