大学生手机成瘾的双路径机制：基于机器学习与网络分析的风险因子与保护因子研究
The Dual-Pathway Mechanism of Smartphone Addiction in College Students: A Study of Risk and Protective Factors Using Machine Learning and Network Analysis
摘要: 目的：解析与预测影响青少年手机成瘾的多维度因素交互作用机制。方法：采用方便抽样法选取554名大学生，施测青少年正念量表(CAMM)、病人健康问卷抑郁量表(PHQ-9)、智能手机成瘾量表(SAS-SV)、大学生压力量表(SSCS)、社交互动焦虑量表(SIAS)、心理韧性量表简版(CD-RISC-10)及家庭亲密度和适应度量表(FACESII-CV)。运用LASSO回归和随机森林机器学习算法分析108个相关特征，筛选核心因子，并构建偏相关网络分析交互机制。结果：筛选出16个核心因子(涉及PHQ-9、SSCS、CD-RISC-10、FACESII-CV和SIAS)，网络分析显示，抑郁集群(尤其“对事物专注有困难”)与手机成瘾联系最紧密。CD-RISC-10与FACESII-CV集群则与手机成瘾呈负相关，起缓冲作用。结论：抑郁症状是手机成瘾的核心风险因素，而心理韧性和积极的家庭功能是重要的保护性因子，揭示了手机成瘾的双路径机制。
Abstract: Objective: To investigate and predict the multidimensional interactive mechanisms influencing adolescent smartphone addiction. Methods: A total of 554 university students were recruited via non-random convenience sampling. Participants completed the following validated instruments: the Child and Adolescent Mindfulness Measure (CAMM), Patient Health Questionnaire-9 (PHQ-9), Smartphone Addiction Scale-Short Version (SAS-SV), College Student Stress Scale (SSCS), Social Interaction Anxiety Scale (SIAS), 10-item Connor-Davidson Resilience Scale (CD-RISC-10), and Family Adaptability and Cohesion Evaluation Scale II-Chinese Version (FACESII-CV). Utilizing LASSO regression and Random Forest machine learning algorithms, 108 associated features were analyzed to identify core predictors. A partial correlation network was subsequently constructed to elucidate interaction mechanisms. Results: Sixteen core factors (spanning PHQ-9, SSCS, CD-RISC-10, FACESII-CV, and SIAS domains) were identified. Network analysis revealed that the depression cluster—particularly the item “difficulty concentrating”—exhibited the strongest association with smartphone addiction. Conversely, the CD-RISC-10 and FACESII-CV clusters demonstrated negative correlations with smartphone addiction, indicating a buffering effect. Conclusion: Depressive symptomatology constitutes a core risk factor for smartphone addiction, whereas psychological resilience and positive family functioning serve as significant protective factors. This evidence delineates a dual-path mechanism underlying smartphone addiction involving both risk and protective pathways.
文章引用：姜广涛, 梅祉曈, 杨美荣 (2025). 大学生手机成瘾的双路径机制：基于机器学习与网络分析的风险因子与保护因子研究. 心理学进展, 15(9), 277-287. https://doi.org/10.12677/ap.2025.159518

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