# The Impact of Digital Safety Competence on Cognitive Competence, AI Self-Efficacy, and Character
## 2 Materials and Methods
### Measurement  
The European Commission's DIGCOMP 2.0 framework defines digital competence as \"the confident, critical and responsible use of, and engagement with, digital technologies for learning, at work and for participant in society\" (p. 10, [70]). To measure ethical and safety digital practices, we adopted the scale developed by [PERSON] [71], which is based on the DIGCOMP framework. Digital Safety Competence encompasses an individual's  
Figure 1: A hypothesized model of the mediating role of AI self-efficacy.  
ability to manage digital practices, personal data safety, and online privacy within digital environments. This includes managing identity, protecting personal data, knowing digital risks (e.g., identity theft, cyberbullying), and behaving ethically online. We employed this framework for two reasons: its widespread adoption in digital competence research, as evidence in a recent review study [72], and its validated application among Chinese students [5,73], who share similar backgrounds with our study participants. Furthermore, the scale has been used and validated among high school [74] and university students [75]. A total of 14 items (e.g., _I carefully considered where and how digital content is saved and stored_) were selected for the current study. Participants rated on a 7-point Likert scale from \(1=\)_\"To a very small degree\"_ to \(7=\)_\"To a very large degree\"_. The results of a confirmatory factor analysis supported the unidimensional factor structure of this scale (\(X^{2}\): 110.241, df = 73, RMSEA = 0.057 (90%CI: 0.03-0.08), CFI = 0.913, SRMR = 0.064). The internal consistency was good (0.81).  
Cognitive competence and moral competence were measured using the short version of the Chinese Positive Youth Development Scale (CPYDS-S) [76]. We used three items for moral competence (e.g., _I keep my promise_) and four items for cognitive competence (e.g., _I know how to see things from different angles_) on a 6-point Likert scale (0 = _Strongly disagree_ to 5 = _Strongly agree_). The confirmatory factor analysis shows that this scale supports the two-factor structure of this scale (\(X^{2}\): 16.687, df = 13, RMSEA = 0.042 (90%CI: 0.000-0.094), CFI = 0.973, SRMR = 0.042). In the present study, the internal consistency for cognitive competence is acceptable (0.73) but marginally satisfactory for moral competence (0.50).  
We used four items to measure AI self-efficacy. These items were based on [PERSON] and [PERSON]'s work [77]. The reliability and validity of this scale have been supported [78]. The response format consists of a 5-point Likert scale. Example of items _\"I have a clear understanding of different GenAI tools\"_. A composite score is used in the present study.  
We measure AI ethics with an item about the awareness of AI ethics on a 6-point Likert scale (_\"I am aware of the potential issues, such as accuracy, ethics, and academic integrity, associated with using GenAI tools.\"_). In addition, demographic questions, such as gender, age, and program of study information, were asked.