Internet Users' Information Privacy Concerns (IUIPC-10) is one of the most endorsed privacy concern scales. It is widely used in the evaluation of human factors of PETs and the investigation of the privacy paradox. Even though its predecessor Concern For Information Privacy (CFIP) has been evaluated independently and the instrument itself seen some scrutiny, we are still missing a dedicated confirmation of IUIPC-10, itself. We aim at closing this gap by systematically analyzing IUIPC's construct validity and reliability. We obtained three mutually independent samples with a total of $N = 1031$ participants. We conducted a confirmatory factor analysis (CFA) on our main sample. Having found weaknesses, we established further factor analyses to assert the dimensionality of IUIPC-10. We proposed a respecified instrument IUIPC-8 with improved psychometric properties. Finally, we validated our findings on a validation sample. While we could confirm the overall three-dimensionality of IUIPC-10, we found that IUIPC-10 consistently failed construct validity and reliability evaluations, calling into question the unidimensionality of its sub-scales Awareness and Control. Our respecified scale IUIPC-8 offers a statistically significantly better model and outperforms IUIPC-10's construct validity and reliability. The disconfirming evidence on the construct validity raises doubts how well IUIPC-10 measures the latent variable information privacy concern. The sub-par reliability could yield spurious and erratic results as well as attenuate relations with other latent variables, such as behavior. Thereby, the instrument could confound studies of human factors of PETs or the privacy paradox, in general.
翻译:互联网用户的信息隐私关注(IUIP-10)是人们最认可的隐私关注范围之一,在评估PET的人类因素和调查隐私悖论时广泛使用。尽管其前身对信息隐私关注(CFIP)进行了独立评估,而且该文书本身也看到了一些检查,但我们仍然缺少对IUIPPC-10本身的专项确认。我们的目标是通过系统分析IUPC-10的构建有效性和可靠性来缩小这一差距。我们获得了三个相互独立的样本,总金额为1031美元的参与者。我们对主要样本进行了确认要素分析(CFA)。我们发现弱点后,我们建立了进一步的因素分析,以肯定IUIPPC-10的维度。我们建议重新指定IUIPPC-8的仪器,其心理测量特性得到了改善。我们确认IUPC-10的验证样本具有总体三维性,但我们发现IUPC-10的构建有效性和可靠性评估始终存在缺陷,质疑其子级认识和控制的单一性和一致性。我们关于IUPC-8的精确度研究规模和不确定性在IUPC-10I的精确度上提出了一种统计上的可靠度。