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Predicting Students' Security Behavior Using Information-Motivation-Behavioral Skills Model

机译:运用信息动机行为技能模型预测学生的安全行为

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The Information-Motivation-Behavioral Skills (IMB) Model has shown reliability in predicting behaviors related to health and voting. In this study, we examine whether the 1MB Model could predict security behavior among university students. Using a cross-sectional design and proxy IMB variables, data was collected from 159 Finnish students on their security threats' awareness (representing IMB's information variable), attitude toward information security and social motivation (replacing IMB's motivation variable), self-efficacy and familiarity with security measures (variables related to IMB's behavioral skills), and self-reported security behavior (1MB outcome variable). An analysis conducted with PLS-SEM v3.2 continued that the IMB Model was an appropriate model to explain and predict security behavior of the university students. Path analysis showed that behavioral skills measures predict security behavior directly, while students' information and motivation variables predicted security behavior through behavioral skills (self-efficacy and familiarity with security measures). The findings suggest that the security behavior of students can be improved by improving threat knowledge, their motivation and behavioral skills - supporting the use of the IMB Model in this context and combination with existing predictors.
机译:信息动机行为技能(IMB)模型已显示出预测与健康和投票有关的行为的可靠性。在这项研究中,我们研究了1MB模型是否可以预测大学生的安全行为。使用横截面设计和代理IMB变量,从159名芬兰学生那里收集了有关他们的安全威胁的意识(代表IMB的信息变量),对信息安全的态度和社会动机(取代IMB的动机变量),自我效能和熟悉程度的数据安全措施(与IMB行为技能有关的变量)和自我报告的安全行为(1MB结果变量)。使用PLS-SEM v3.2进行的分析继续指出,IMB模型是解释和预测大学生安全行为的合适模型。路径分析表明,行为技能测度直接预测安全行为,而学生的信息和动机变量则通过行为技能(自我效能和对安全测度的熟悉程度)预测安全行为。研究结果表明,可以通过提高威胁知识,他们的动机和行为技能来改善学生的安全行为-支持在这种情况下结合使用IMB模型并与现有预测变量结合使用。

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