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Basic Statistical Analysis The basic statistical analysis provided descriptive statistics for the variables of interest. The mean age of participants was 21.42 years (SD = 1.84). The mean comfort level with sharing personal data was 2.55 (SD = 1.12). The perceived safety of data management had a mean score of 2.60 (SD = 0.84). Detailed descriptive statistics for all variables are presented in Table 1.

Analysis of Variance (ANOVA) Comfort Level by Perceived Privacy Risks An ANOVA was conducted to examine the effect of perceived privacy risks on the comfort level with sharing personal data. The results indicated that perceived privacy risks did not have a significant effect on comfort levels, F(1, 51) = 2.67, p = .108.

Comfort Level by Perceived Safety An ANOVA was conducted to examine the effect of perceived safety on the comfort level with sharing personal data. The results indicated a significant effect of perceived safety on comfort levels, F(1, 51) = 7.49, p = .009. Participants who perceived higher safety reported higher comfort levels with sharing personal data.

T-Tests Comfort Level by Gender T-tests were conducted to compare the comfort levels with sharing personal data between genders. The results for the Personalized Study Assistant Comfort indicated no significant difference between males (M = 2.87, SD = 1.32) and females (M = 3.03, SD = 1.32), t(49.35) = -0.46, p = .649. Similarly, no significant differences were found for Health and Wellness AI Companion Comfort and Career and Job Recommendation Tool Comfort.

Multiple Regression Analysis Multiple regression analyses were conducted to predict comfort levels based on perceived privacy risks, perceived safety, age, gender.

Personalized Study Assistant Comfort The regression model for Personalized Study Assistant Comfort was not significant, F(5, 47) = 1.77, p = .137, with an R² of .16. Perceived safety was a significant predictor (β = .56, p = .010), indicating that higher perceived safety was associated with higher comfort levels.

Health and Wellness AI Companion Comfort The regression model for Health and Wellness AI Companion Comfort was not significant, F(5, 47) = 0.58, p = .712, with an R² of .06. None of the predictors were significant.

Career and Job Recommendation Tool Comfort The regression model for Career and Job Recommendation Tool Comfort was significant, F(5, 47) = 2.83, p = .026, with an R² of .23. Both perceived privacy risks (β = .32, p = .033) and perceived safety (β = .46, p = .024) were significant predictors, indicating that higher perceived privacy risks and safety were associated with higher comfort levels.

Visualizations Histogram of Comfort Level A histogram of the comfort level with sharing personal data showed a relatively normal distribution with a slight skew towards lower comfort levels.

Violin Plot of Comfort Level by Gender A violin plot with a boxplot overlay indicated that the distribution of comfort levels was similar across genders, with no significant differences observed.