# The Effect of Countermeasure Readability on Security Intentions
## 6 Discussion  
The main research question this study aims to answer is: how does the readability of cybersecurity countermeasures influence security intentions? The results of the analysis of our framework confirm that countermeasure readability affects security intentions through self-efficacy since H5 and H12 are supported. The study demonstrates countermeasure readability is significantly predicted by countermeasure awareness (H2), meaning the more familiar one is with security measures, the easier the measure will be perceived to read. H1 was not supported, implying that a reader's disposition to reading about countermeasures does not affect their perceived readability. The data suggest countermeasure readability is a critical determinant of self-efficacy (H5). This means that when people are exposed to security controls that help them safeguard against a cyber threat, they feel more confident applying these when they perceive them to be easy to read. In line with previous research [10, 45, 52], the results indicate that self-efficacy is a significant predictor of security intentions (H12). When individuals believe or feel confident they can implement a countermeasure, they are likely to have the intention to carry out the security measure. Countermeasure readability does not predict response cost (H6 was rejected); that is, the readability of a presented countermeasure does not affect how much mental or \begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Hypothesis** & **Path Coefficient** & **T Stat.** & \(\mathbf{F^{2}}\) & \(\mathbf{2.5\%CI}\) & \(\mathbf{97.5\%CI}\) & **Supported?** \\ \hline H1: CRD\(\rightarrow\)CR & \(-0.074\) & \(-0.671\) & \(0.020\) & \(-0.223\) & \(0.205\) & No \\ H2: TA\(\rightarrow\)PS & \(0.440\) & \(1.386\) & \(-0.491\) & \(0.240\) & \(0.706\) & Yes \\ H3: TA\(\rightarrow\)PV & \(-0.392\) & \(-1.235\) & \(-0.614\) & \(0.181\) & \(0.487\) & No \\ H4: CR\(\rightarrow\)SE & \(0.322\) & \(1.892\) & \(0.047\) & \(0.138\) & \(0.719\) & No \\ H5: CR\(\rightarrow\)RC & \(-0.142\) & \(-0.522\) & \(-0.714\) & \(0.015\) & \(0.372\) & Yes \\ H6: CA\(\rightarrow\)CR & \(0.758\) & \(10.047\) & \(0.611\) & \(1.184\) & \(0.899\) & No \\ H7: CA\(\rightarrow\)SE & \(0.487\) & \(2.764\) & \(0.071\) & \(0.223\) & \(0.770\) & Yes \\ H8: CA\(\rightarrow\)RC & \(-0.201\) & \(-0.743\) & \(-0.703\) & \(0.033\) & \(0.410\) & No \\ H9: CA\(\rightarrow\)RE & \(0.547\) & \(2.928\) & \(0.080\) & \(0.426\) & \(0.760\) & Yes \\ H10: PS\(\rightarrow\)SI & \(-0.021\) & \(-0.139\) & \(-0.257\) & \(-0.005\) & \(0.343\) & No \\ H11: PV\(\rightarrow\)SI & \(-0.073\) & \(-0.685\) & \(-0.223\) & \(-0.008\) & \(0.206\) & No \\ H12: SE\(\rightarrow\)SI & \(0.575\) & \(3.563\) & \(0.192\) & \(0.190\) & \(0.794\) & Yes \\ H13: RC\(\rightarrow\)SI & \(-0.096\) & \(-0.803\) & \(-0.340\) & \(0.007\) & \(0.129\) & No \\ H14: RE\(\rightarrow\)SI & \(-0.036\) & \(-0.277\) & \(-0.210\) & \(-0.014\) & \(0.297\) & No \\ H15: SN\(\rightarrow\)SI & \(0.296\) & \(2.308\) & \(0.042\) & \(0.179\) & \(0.542\) & Yes \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Overview of PLS-SEM results of structural model analysis. financial effort people think implementing the measure takes. As a result, countermeasure readability only influences security intentions through self-efficacy. Confirmation of H7 and H9 mean awareness of countermeasures is a significant antecedent of the coping appraisal mechanisms self-efficacy and response efficacy. The awareness of threats was not found to be a significant determinant of perceived severity (H3) and perceived vulnerability (H4). More specifically, this implies that evoking awareness of cyber threats or appealing to fear is not enough to steer people to desired security behavior if they do not know of countermeasures or do not know how to counteract cyber threats. This conforms to findings by [PERSON] and [PERSON] [10], [PERSON] and [PERSON] [77], and [PERSON] et al. [78].