【作者】 张淑洁； 田雨； 石洁茹； 王鹏； 孟维璇； 司英栋；

【Author】 Zhang Shujie;TianYu;Shi Jieru;Wang Peng;Meng Weixuan;Si Yingdong;School of Psychology, Shandong Normal University;

【机构】 山东师范大学心理学院；

【摘要】 根据第四十次中国互联网发展统计报告(2017年),全国学生网民人数达到1.8亿人,占全国网民人数的24%。研究表明,网络成瘾的中学生通常患有身体健康问题、学校表现差、攻击性强、与家庭关系恶劣。因此,研究中国高中生网络成瘾机制、建立有效的网络成瘾干预技术势在必行。在此背景下,作者采用纵向追踪研究,利用交叉滞后模型,使用《社会支持量表》、《孤独量表》和《中文网络成瘾量表》,考察了社会支持的三个维度(客观支持、主观支持、支持的利用率)、孤独感和网络成瘾的四个维度(强迫性互联网使用和戒断反应、网络成瘾耐受性、时间管理问题、人际和健康问题)的关系。分别在在学年开始时(T1)、6个月后(T2)和1年后(T3)进行问卷调查。共有169名高中学生(88名女生和81名男生,平均年龄=18.31岁)完成了全部三次测量。研究结果表明:(1)T1的客观社会支持和支持的利用度显著负性预测T2的孤独;(2)T2的孤独显著负性预测T3的客观社会支持和支持的利用度;(3)T1的强迫性互联网使用和戒断反应、时间管理问题显著正向预测T2的孤独;(4)T2的孤独显著正向预测T3的强迫性互联网使用和戒断反应、网络成瘾耐受性、时间管理问题、人际和健康问题;(5)T1的主观社会支持直接影响T3的网络成瘾耐受性和时间管理问题;(6)T2的孤独在T1的客观社会支持与T3的强迫性互联网使用和戒断反应、时间管理问题、人际和健康问题的关系中起到完全中介作用;(7)T2的孤独在T1的主观社会支持和T3的人际和健康问题的关系中起到完全中介作用。更多还原

【Abstract】 According to the 40 th China Statistical Report on Internet Development(2017), 751 million Chinese citizens use the Internet. Among them, 185 million are students(24.8%). Numerous studies have demonstrated that postsecondary students with Internet addiction typically experience physical health problems, poor school performance, aggressive tendencies, and problems with family relationships and social connections. Therefore, investigating how postsecondary students acquire Internet addiction and developing effective intervention techniques for Internet addiction are imperative. This short-term longitudinal study examined the associations among three dimensions of social support(objective support [OS], subjective support [SS], and support utilization [SU]), loneliness, and the four dimensions of Internet addiction(compulsive Internet use [CIU] & withdrawal from Internet addiction [WIA], tolerance of Internet addiction [TIA], time-management problems [TMPs], and interpersonal and health problems [IHP]) in a Chinese sample. Using Social Support Rating Scale, Loneliness Scale and Chinese Internet Addiction Scale. A total of 169 postsecondary first-year students(88 girls and 81 boys; mean age = 18.31 years) participated in the study. The questionnaire measurements were taken at the beginning of the school year(T1), 6 months later(T2), and 1 year later(T3). Cross-lagged and structural equation modeling analyses indicated that(a) OS(T1) and SU(T1) negatively predicted loneliness(T2); and loneliness(T2) negatively predicted OS(T3) and SU(T3);(b) CIU & WIA(T1) and TMPs(T1) positively predicted loneliness(T2); and loneliness(T2) positively predicted CIU & WIA(T3), TIA(T3), TMP(T3), and IHP(T3);(c) SS(T1) directly affected TIA(T3) and TMP(T3); and(d) loneliness(T2) played a mediating role in the relationships between OS(T1) and CIU(T3), OS(T1) and TMP(T3), OS(T1) and IHP(T3), and SU(T1) and IHP(T3).更多还原