Hangzhou Vocational &Technical College, Zhejiang, 310018, Hangzhou, China.
Department of Education, Universiti Teknologi Malaysia, 81310 UTM, Johor Bahru, Malaysia.
BMC Public Health. 2022 Aug 13;22(1):1548. doi: 10.1186/s12889-022-13915-1.
According to the validation literature on items of Young's Internet Addiction Test (IAT), this study rephrased disputable items to improve the psychometric properties of this Chinese version of IAT and identify the presence of differential item function (DIF) among demographic and Internet use factors; detect the effect of demographic and Internet use factors on IAT after adjusting for DIF.
An online questionnaire was distributed to college students in Zhe Jiang province in two stage. The 1st phase study collected 384 valid responses to examine the quality of IAT items by using Rasch Model analysis and exploring factor analysis (EFA). The online questionnaire was modified according to the 1st phase study and distributed online for the 2nd phase study which collected a total of 1131 valid responses. The 2nd phase study applied confirmatory factor analysis (CFA) and a multiple indicator multiple causes (MIMIC) model to verify the construct of IAT, potential effect of covariates on IAT latent factors, as well as the effect of differential item functioning (DIF).
Rasch model analysis in the 1st phase study indicated a 5-point rating scale was performed better, no sever misfit was found on item. The overall property of Chinese version IAT with the 5-point scale was good to excellent person and item separation (2.66 and 6.86). A three-factor model was identified by EFA. In the 2nd phase study, IAT 13 were detected with DIF for gender in MIMIC model. After correcting DIF effect, the significant demographic and Internet use factors on IAT were time spent online per day, year 3, year 2, general users.
Item improvement was efficient that the problematic items found in literature was performed good in this study. The overall psychometric property of this Chinese version IAT was good with limited DIF effect in one item. Item improvement on IAT13 was encouraged in the future study to avoid gender bias and benefit for epidemiology on PIU.
根据 Young 的互联网成瘾测试(IAT)项目的验证文献,本研究重新表述了有争议的项目,以提高该中文版 IAT 的心理测量特性,并确定人口统计学和互联网使用因素之间存在差异项目功能(DIF);检测人口统计学和互联网使用因素对调整 DIF 后 IAT 的影响。
本研究采用两阶段在线问卷调查的方式,对浙江省大学生进行调查。第一阶段研究共收集了 384 份有效问卷,采用 Rasch 模型分析和探索性因素分析(EFA)检验 IAT 项目的质量。根据第一阶段的研究结果对在线问卷进行了修改,并进行了第二阶段的研究,共收集了 1131 份有效问卷。第二阶段研究采用验证性因素分析(CFA)和多指标多原因(MIMIC)模型,验证 IAT 的结构、协变量对 IAT 潜在因素的潜在影响,以及差异项目功能(DIF)的影响。
第一阶段研究的 Rasch 模型分析表明,采用 5 点评分量表效果更好,项目无严重不拟合。采用 5 点量表的中文版 IAT 的整体性能为良好至优秀的个人和项目分离(2.66 和 6.86)。EFA 确定了一个三因素模型。在第二阶段研究中,在 MIMIC 模型中发现 13 个 IAT 存在性别差异。在纠正 DIF 效应后,对 IAT 有显著影响的人口统计学和互联网使用因素是每天上网时间、3 年级、2 年级、普通用户。
改进项目的效果显著,文献中发现的有问题的项目在本研究中表现良好。中文版 IAT 的整体心理测量特性良好,仅存在一个项目的 DIF 效应有限。未来的研究应鼓励改进 IAT13,以避免性别偏见,有利于网络成瘾的流行病学研究。