大学生学业拖延负性情绪和自我控制与智能手机成瘾的交叉滞后分析

王文婷; 宋金秋; 张忠楼

doi:10.16835/j.cnki.1000-9817.2025305

大学生学业拖延负性情绪和自我控制与智能手机成瘾的交叉滞后分析

doi: 10.16835/j.cnki.1000-9817.2025305

1.
广州城市职业学院数字商贸学院, 广东 510000
2.
哈尔滨师范大学体育科学学院
3.
哈尔滨体育学院民族传统体育学院

基金项目:

广州市教育局2024年高校科研项目 2024312469

广州城市职业学院2025年校级科研课题 KYSZ2025007

详细信息

作者简介:
王文婷(1986-), 女, 江苏沛县人, 博士, 讲师, 主要研究方向为大学生心理健康、思想政治教育

通讯作者:
宋金秋, E-mail: 282329824@qq.com

利益冲突声明 所有作者声明无利益冲突。
中图分类号: R179 B844.2 C913.5 TN916.9
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- 被引次数: 0
出版历程
- 收稿日期: 2025-07-31
- 修回日期: 2025-09-14
- 刊出日期: 2025-10-25

Cross-lagged analysis of academic procrastination, negative emotions and self-control, and smartphone addiction among college students

1.
Digital Business College of Guangzhou City Polytechnic, Guangzhou 510000, Guangdong Province, China

摘要

摘要: 目的探索大学生学业拖延、负性情绪、自我控制与智能手机成瘾之间的因果关系, 为促进大学生心理健康和学业成就提供参考。方法选用多阶段整群随机抽样方法, 抽取广州市某高校452名大一年级学生为研究对象, 使用学业拖延量表(PASS)、抑郁-焦虑-压力量表(DASS-21)、自我控制量表和智能手机成瘾量表(SAS-SV)作为测量工具, 于2024年10月(T1)、2025年2月(T2)和2025年5月(T3)完成3次问卷调查。运用交叉滞后模型分析大学生学业拖延、负性情绪、自我控制与智能手机成瘾的因果关系。结果大学生SAS-SV量表平均分为(40.52±1.96), 大一新生智能手机成瘾率为43.1%。大学生学业拖延、负性情绪与智能手机成瘾在不同时间段两两之间呈正相关(r=0.30~0.62), 自我控制与其他3个变量间呈负相关(r=-0.72~-0.34)(P值均 < 0.05)。交叉滞后模型结果显示, T1和T2学业拖延、负性情绪均可正向预测T2和T3智能手机成瘾(T1→T2, β值分别为0.22, 0.35;T2→T3, β值分别为0.21, 0.24), 自我控制负向预测智能手机成瘾(T1→T2, β=-0.32;T2→T3, β=-0.26)(P值均 < 0.05);反向因果回归模型中, T1和T2智能手机成瘾均可正向预测T2和T3学业拖延及负性情绪(T1→T2, β值分别为0.09, 0.24;T2→T3, β值分别为0.10, 0.35, P值均 < 0.05), 但对自我控制预测作用无统计学意义(T1→T2, β=-0.04;T2→T3, β=-0.03, P值均>0.05)。结论大学生学业拖延、负性情绪与智能手机成瘾互为因果关系, 自我控制单向预测智能手机成瘾。
- 情绪 /
- 自我 /
- 行为, 成瘾 /
- 精神卫生 /
- 学生
Abstract: Objective To explore the causal relationship between academic procrastination, negative emotions, self-control, and smartphone addiction among college students, so as to provide theoretical reference for promoting their mental health and academic achievement. Methods A multi-stage cluster random sampling method was used to select 452 first-year students from a university in Guangzhou as the research subjects. Procrastination Assessment Scale- Student (PASS), The Depression Anxiety Stress Scale (DASS-21), Self Control Scale, and Short Version of the Smartphone Addiction Scale (SAS-SV) were used as measurement tools. Three questionnaire surveys were completed in October 2024 (T1), February 2025 (T2), and May 2025 (T3). Coss-lagged models were utilized to analyze the causal relationship between academic procrastination, negative emotions, self-control, and smartphone addiction. Results The SAS-SV scale for college students showed an average score of (40.52±1.96), with 43.1% of freshmen exhibiting smartphone addiction.Positive correlations were observed between academic procrastination, negative emotions, and smartphone addiction across different time points, while self-control exhibited negative correlations with these three variables (r=0.30-0.62, -0.72 to -0.34, all P < 0.05). Cross-lagged model results indicated that academic procrastination and negative emotions at T1 and T2 positively predicted smartphone addiction at T2 and T3 (T1→T2, β=0.22, 0.35; T2→T3, β=0.21, 0.24; all P < 0.05). Self-control negatively predicted smartphone addiction (T1→T2, β=-0.32; T2→T3, β=-0.26; both P < 0.05). In reverse-causality regression models, smartphone addiction at T1 and T2 positively predicted academic procrastination and negative emotions at T2 and T3 (T1→T2, β=0.09, 0.24; T2→T3, β=0.10, 0.35; all P < 0.05), but no statistically significant predictions were found for self-control (T1→T2, β=-0.04; T2→T3, β=-0.03; both P>0.05). Conclusion Academic procrastination and negative emotions exhibit bidirectional causality with smartphone addiction among college students, while self-control unidirectionally predicts smartphone addiction.
- Emotions /
- Ego /
- Behavior, addictive /
- Mental health /
- Students
注释:

1) 利益冲突声明 所有作者声明无利益冲突。

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图 1 大学生学业拖延、负性情绪和智能手机成瘾的交叉滞后分析

注: *P < 0.05，**P < 0.01。

Figure 1. Cross-lagged analysis of academic procrastination, negative emotions and smartphone addiction among college students

下载: 全尺寸图片幻灯片

图 2 大学生学业拖延、自我控制和智能手机成瘾的交叉滞后分析

注：^*P < 0.05，^**P < 0.01。

Figure 2. Cross-lagged analysis of academic procrastination, self-control, and smartphone addiction among college students

下载: 全尺寸图片幻灯片

表 1 不同人口学特征大学生智能手机成瘾得分(x±s)

Table 1. Scores of smartphone addiction among college students with different demographic characteristics(x±s)

人口学指标	选项	人数	得分	t值
性别	男	163	29.63±0.72	0.14
	女	289	31.24±1.32
专业	理科	104	30.08±1.52	-1.09
	文科	348	31.97±0.86
居住地	城镇	284	29.81±0.92	0.05
	农村	168	29.75±0.68
是否独生子女	是	29	33.48±1.92	2.08^*
	否	313	29.43±0.57
是否有留守经历	是	88	31.09±1.17	1.19
	否	364	29.45±0.61
是否为班干部	是	90	28.71±1.36	-0.98
	否	362	30.04±0.59
注：^*P < 0.05。

下载: 导出CSV

表 2 不同时间阶段大学生学业拖延、负性情绪、自我控制与智能手机成瘾间的相关性分析(r值，n=452)

Table 2. Correlation analysis of main research variables at different time periods among college students(r, n=452)

变量	T1学业拖延	T1负性情绪	T1自我控制	T1智能手机成瘾	T2学业拖延	T2负性情绪	T2自我控制	T2智能手机成瘾	T3学业拖延	T3负性情绪	T3自我控制
T1负性情绪	0.35^**
T1自我控制	-0.44^**	-0.53^**
T1智能手机成瘾	0.60^**	0.62^**	-0.72^**
T2学业拖延	0.38^**	0.53^**	-0.38^**	0.48^**
T2负性情绪	0.58^**	0.62^**	-0.40^**	0.54^**	0.56^**
T2自我控制	-0.53^**	-0.40^**	0.46^**	-0.34^**	-0.38^**	-0.46^**
T2智能手机成瘾	0.58^**	0.42^**	-0.42^**	0.46^**	0.39^**	0.41^**	-0.43^**
T3学业拖延	0.35^**	0.37^**	-0.41^**	0.40^**	0.44^**	0.41^**	-0.37^**	0.37^**
T3负性情绪	0.40^**	0.47^**	-0.48^**	0.35^**	0.46^**	0.56^**	-0.39^**	0.38^**	0.41^**
T3自我控制	-0.53^**	-0.53^**	0.48^**	-0.46^**	-0.63^**	-0.36^**	0.30^**	-0.37^**	-0.41^**	-0.56^**
T3智能手机成瘾	0.57^**	0.52^**	-0.42^**	0.48^**	0.42^**	0.53^**	-0.60^**	0.40^*	0.53^**	0.49^**	-0.40^*
注：^P < 0.05，^*P < 0.01。

下载: 导出CSV

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