Emotional Reactions to Cybersecurity Breach Situations: Scenario-Based Survey Study.
Emotional Reactions to Cybersecurity Breach Situations: Scenario-Based Survey Study.
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DOI：
10.2196/24879
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发表时间：
2021-05-12
影响因子：
7.4
通讯作者：
Roesch EB
中科院分区：
文献类型：
--
作者：
Budimir S;Fontaine JRJ;Huijts NMA;Haans A;Loukas G;Roesch EB
随着互联网互联性的不断扩大，特别是物联网的最新发展，人们越来越面临网络安全漏洞的风险，这可能对其个人和职业生活产生深远的影响，并产生心理和心理健康影响。我们的目的是识别网络安全漏洞最具代表性的场景之一（智能安全摄像头被黑客攻击）所触发的情绪过程的维度结构，并探索哪些人格特征与这些情绪维度系统相关。来自英国和荷兰的总共 902 名参与者报告了他们因网络安全漏洞场景引发的情绪过程。此外，他们还报告了自己的“大五人格”特征，以及弹性、过度控制（内化问题）和控制不足（攻击性）人格类型的关键指标。主成分分析揭示了情绪过程的清晰的三维结构：情绪强度、主动反应与战斗/逃跑反应，以及情感与认知/动机反应。回归分析显示，更多的内化问题（β=.33，P<.001）、复原力（β=.22，P<.001）和宜人性（β=.12，P<.001）以及更少的情绪稳定性（β=–.25，P<.001）对于更高的情绪强度具有显着的预测价值。更多的内化问题 (β=.26, P<.001)、攻击性 (β=.25, P<.001) 和外向性 (β=.07, P=.01) 和更少的复原力 (β=–.19, P<.001)、宜人性 (β=–.34, P<.001)、意识 (β=–.19, P<.001) 和开放性 (β=–.22, P<.001) 对于相对更多的战斗/逃跑比主动反应具有显着的预测价值。更少的内化问题（β=–.32，P<.001）和更多的情绪稳定性（β=.14，P<.001）和攻击性（β=.13，P<.001）对于认知/动机反应比情感反应相对更高的显着性具有显着的预测价值。为了充分描述网络安全漏洞引发的情绪过程，除了一般的负面情感维度之外，还需要两个维度。这种多维结构进一步得到情感维度与人格特征的差异关系的支持。所发现的情绪结构可用于一致预测谁因网络安全漏洞经历而面临长期心理健康问题的风险。
With the ever-expanding interconnectedness of the internet and especially with the recent development of the Internet of Things, people are increasingly at risk for cybersecurity breaches that can have far-reaching consequences for their personal and professional lives, with psychological and mental health ramifications. We aimed to identify the dimensional structure of emotion processes triggered by one of the most emblematic scenarios of cybersecurity breach, the hacking of one’s smart security camera, and explore which personality characteristics systematically relate to these emotion dimensions. A total of 902 participants from the United Kingdom and the Netherlands reported their emotion processes triggered by a cybersecurity breach scenario. Moreover, they reported on their Big Five personality traits, as well as on key indicators for resilient, overcontrolling (internalizing problems), and undercontrolling (aggression) personality types. Principal component analyses revealed a clear 3-dimensional structure of emotion processes: emotional intensity, proactive versus fight/flight reactions, and affective versus cognitive/motivational reactions. Regression analyses revealed that more internalizing problems (β=.33, P<.001), resilience (β=.22, P<.001), and agreeableness (β=.12, P<.001) and less emotional stability (β=–.25, P<.001) have significant predictive value for higher emotional intensity. More internalizing problems (β=.26, P<.001), aggression (β=.25, P<.001), and extraversion (β=.07, P=.01) and less resilience (β=–.19, P<.001), agreeableness (β=–.34, P<.001), consciousness (β=–.19, P<.001), and openness (β=–.22, P<.001) have significant predictive value for comparatively more fight/flight than proactive reactions. Less internalizing problems (β=–.32, P<.001) and more emotional stability (β=.14, P<.001) and aggression (β=.13, P<.001) have significant predictive value for a comparatively higher salience for cognitive/motivational than affective reactions. To adequately describe the emotion processes triggered by a cybersecurity breach, two more dimensions are needed over and above the general negative affectivity dimension. This multidimensional structure is further supported by the differential relationships of the emotion dimensions with personality characteristics. The discovered emotion structure could be used for consistent predictions about who is at risk to develop long-term mental well-being issues due to a cybersecurity breach experience.
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