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“低头族”量表的有效性:识别行人风险群体的敏感性和特异性。

Validity of the Smombie Scale: Sensitivity and specificity in identifying pedestrian risk group.

作者信息

Oh Sumi, Park Sunhee

机构信息

College of Nursing, Health and Nursing Research Institute, Jeju National University, Jeju-si, Jeju Special Self-Governing Province, South Korea.

College of Nursing, Hanyang University, Seongdong-gu, Seoul, South Korea.

出版信息

Digit Health. 2024 Aug 7;10:20552076241271851. doi: 10.1177/20552076241271851. eCollection 2024 Jan-Dec.

DOI:10.1177/20552076241271851
PMID:39119555
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11307350/
Abstract

OBJECTIVE

The objective of this study was to determine the most effective cut-off point for the Smombie Scale and evaluate its ability to screen for pedestrian safety risks among young adults.

METHODS

Data were obtained from an online sample of 396 Korean young adults aged 18-39 years. Latent profile analysis was used to distinguish the risk group as a reference measure for the Smombie Scale. Discriminative power was assessed using sensitivity, specificity, receiver operating characteristic (ROC) curves, and the area under the ROC curve. The cut-off points were estimated from the Youden index and the balanced score.

RESULTS

The latent profile analysis showed two different classes: "risk group" of 17.8% and "others." Based on the latent profile analysis, sensitivity, and specificity analysis showed that an adequate cut-off point of 2.78 of five points or higher was associated with a high risk of distracted walking.

CONCLUSION

The Smombie Scale is a good predictor of problematic smartphone use on the road and can be used as a screening tool for assessing risk levels among young adult pedestrians.

摘要

目的

本研究的目的是确定“僵尸行人量表”最有效的临界值,并评估其筛查年轻成年人行人安全风险的能力。

方法

数据来自396名年龄在18 - 39岁的韩国年轻成年人的在线样本。潜在剖面分析用于区分风险组,作为“僵尸行人量表”的参考指标。使用敏感性、特异性、受试者工作特征(ROC)曲线和ROC曲线下面积评估判别能力。临界值由约登指数和平衡分数估计得出。

结果

潜在剖面分析显示出两个不同类别:占17.8%的“风险组”和“其他组”。基于潜在剖面分析,敏感性和特异性分析表明,五分制中2.78分及以上的适当临界值与分心行走的高风险相关。

结论

“僵尸行人量表”是道路上智能手机使用问题的良好预测指标,可作为评估年轻成年行人风险水平的筛查工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37ef/11307350/276257bee16d/10.1177_20552076241271851-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37ef/11307350/18335800a1bf/10.1177_20552076241271851-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37ef/11307350/276257bee16d/10.1177_20552076241271851-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37ef/11307350/18335800a1bf/10.1177_20552076241271851-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/37ef/11307350/276257bee16d/10.1177_20552076241271851-fig2.jpg

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