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中职学生手机成瘾:潜在类型、鉴定标准以及核心激活症状

Secondary vocational school students’ smartphone addiction: Latent types, identification criteria, and core activating symptoms

摘要: 中职学生手机成瘾常被视为中等职业教育亟待解决的“顽瘴痼疾”。为探究中职学生手机成瘾的潜在类型、鉴定标准以及核心激活症状,采用方便抽样法,从7所中职学校选取2669名学生,采用简版问题性手机使用量表对其实施调查。借助潜在剖面分析技术、ROC分析技术以及网络分析技术,进行数据分析。结果发现:(1)中职学生手机成瘾可划分为2类:正常型(31.5%)与风险型(68.5%);(2)鉴定为“风险型”的最佳截断值为25(量表总分大于25),66.82%的中职学生存在手机成瘾风险;(3)基于鉴定为“风险型”被试的数据,在正则化偏相关网络中,“SA09”节点(对应症状为“失去控制”)的强度中心性最大,“SA04”节点(对应症状为“戒断反应”)次之,即“风险型”中职学生的手机成瘾核心症状为“失去控制”与“戒断反应”,而在贝叶斯网络中,“SA09”节点与“SA04”节点的优先级并列最高,即“失去控制”与“戒断反应”是手机成瘾的核心激活症状。基于此,要“营造安全和谐的成长环境”、“大规模筛查并多方验证”、“以培育自我控制能力为重心”以及“以人性化为抓手”,以充分发挥家校共育的联合作用。

Abstract: Smartphone addiction among secondary vocational school students is often considered as a stubborn problem which urgently needs to be addressed in secondary vocational education. To explore the latent types, identification criteria, and core activating symptoms of smartphone addiction among secondary vocational school students, a convenience sampling method was used to select 2669 students from 7 secondary vocational schools. The Short Version of the Mobile Phone Problem Use Scale was used to survey them. Latent profile analysis, ROC analysis and network analysis were implemented for data analysis. The results show: (1) Smartphone addiction among secondary vocational school students could be divided into two categories, i.e. Normal Type(31.5%) and Risky Type(68.5%); (2) The optimal cutoff value for identifying as Risky Type was 25 (with a total score of the scale greater than 25), and 66.82% of secondary vocational school students were at risk of smartphone addiction; (3) Based on the data of subjects identified as Risky Type, in the regularized partial correlation network, the node SA09(corresponding to the symptom Loss of Control) had the greatest Strength, followed by the node SA04(corresponding to the symptom Withdrawal), which indicated that Loss of Control and Withdrawal were the core symptoms of smartphone addiction among secondary vocational school students who were at risk of smartphone addiction, while in the Bayesian network, both the node SA09 and the node SA04 had the highest priority, which suggested that both Loss of Control and Withdrawal were the core activating symptoms of smartphone addiction. Based on these, creating a safe and harmonious growth environment, conducting large-scale screening and multi-party verification, focusing on the cultivation of self-control ability as the starting point, and taking humanization as the starting point are demanded, so as to fully leverage the joint role of Family-School Coeducation.

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[V1] 2025-01-13 09:29:53 PSSXiv:202501.01422V1 下载全文
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