中文版无手机恐惧量表的修订

该研究以国外学者Caglar Yildirim和Ana-Paula Correia于2015年编制的Nomophobia量表为基础,修订出了适用于国内的中文版无手机恐惧量表。研究首先使用探索性结构方程模型对量表结构进行初探; 其次使用项目反应模型进行项目分析并根据其分析结果对项目进行修改和筛选,最终形成正式版量表; 最后对正式版量表其进行信效度检验,并再次对量表题目进行项目分析。最终量表共16道题目,包括害怕无法获得信息、害怕失去便利、害怕失去联系和害怕失去网络连接4个维度; 总量表的Cronbach α系数为0.931,四维度的α系数分别为:0.789,0.816,0.887和0.896。CFA验证性结果显示量表结构较好(χ2/df=3.91,RMSEA=0.067,TLI=0.941,CFI=0.952,SRMR=0.04); 使用手机成瘾倾向量表作为校标的结果显示二者之间相关为0.626,效度良好。最终量表项目区分度在1.734,4.806]之间,四维度区分度均值为2.1765,2.72,3.2925和3.883,项目难度参数在-1.830,4.806]之间。综上结果显示该研究编制的无手机恐惧量表各项指标均达到了心理测量学要求,可供后续研究使用

Revisement of Nomophobia Scale for Chinese

Generalization theory is widely used in various psychological evaluation practices.Budget and cost are the problems that cannot be neglected in the research of measurement.When there is a budget constraint,the generalization theory needs to consider how to design a measurement program with relatively high reliability and feasibility,which requires the optimal sample size to be estimated by some means.Lagrange multiplication is a more mature method for estimating the optimal sample size under the budget constraints in generalization theory.Some influencing factors of optimal sample size estimation under the budget constraints in generalization theory,such as the influence of total budget rounding,are discussed,and some follow-up solutions are also proposed,such as deducing the unified formula of Lagrange multiplication