Descriptive statistics regarding sexual behavior of the complete take to and you can the three subsamples regarding energetic profiles, previous profiles, and you can low-users

Getting solitary decreases the level of unprotected complete sexual intercourses

In regard to the number of partners with whom participants had protected full sex during the last year, the ANOVA revealed a significant difference between user groups (F_{(2, 1144)} = , P 2 = , Cramer’s V = 0.15, P Figure 1 represents the theoretical model and the estimate coefficients. The model fit indices are the following: ? 2 = , df = 11, P 27 the fit indices of our model are not very satisfactory; however, the estimate coefficients of the model resulted statistically significant for several variables, highlighting interesting results and in line with the reference literature. In Table 4 , estimated regression weights are reported. The SEM output showed that being active or former user, compared to being non-user, has a positive statistically significant effect on the number of unprotected full sexual intercourses in the last 12 months. The same is for the age. All the other independent variables do not have a statistically significant impact.

Production of linear regression model entering demographic, dating programs use and you can intentions from set up parameters given that predictors getting just how many protected full sexual intercourse’ people certainly effective users

Returns out of linear regression design typing group, relationship programs usage and intentions out of setting up parameters once the predictors to own how many secure full sexual intercourse’ couples certainly one of active pages

Hypothesis 2b A second multiple regression analysis was run to predict the number of unprotected full sex partners for active users. The number of unprotected full sex partners was set as the dependent variable, while the same demographic variables and dating apps usage and their motives for app installation variables used in the first regression analysis were entered as covariates. The final model accounted for a significant proportion of the variance in the number of unprotected full sex partners among active users (R 2 = 0.16, Adjusted R 2 = 0.14, F-change_{(step 1, 260)} = 4.34, P = .038). In contrast, looking for romantic partners or for friends, and being male were negatively associated with the number of unprotected sexual activity partners. Results are reported in Table 6 .

Wanting sexual partners, several years of software application, being heterosexual were definitely with the quantity of unprotected complete sex couples

Output off linear regression model typing market, matchmaking applications use and you will objectives off construction parameters since predictors getting exactly how many exposed complete sexual intercourse’ partners one of active pages

Looking for sexual couples, numerous years of software use, being heterosexual was indeed certainly regarding the quantity of unprotected full sex lovers

Production regarding linear regression design entering demographic, relationship software utilize and you may intentions regarding construction variables since the predictors for how many unprotected complete sexual intercourse’ partners one of effective users

Hypothesis 2c A third multiple regression analysis was run, including demographic variables and apps’ pattern of usage variables together with apps’ installation motives, to predict active users’ hook-up frequency. The hook-up frequency was set as the dependent variable, while the kissbridesdate.com look at these guys same demographic variables and dating apps usage variables used in the previous regression analyses were entered as predictors. The final model accounted for a significant proportion of the variance in hook-up frequency among active users (R 2 = 0.24, Adjusted R 2 = 0.23, F-change_{(step 1, 266)} = 5.30, P = .022). App access frequency, looking for sexual partners, having a CNM relationship style were positively associated with the frequency of hook-ups. In contrast, being heterosexual and being of another sexual orientation (different from hetero and homosexual orientation) were negatively associated with the frequency of hook-ups. Results are reported in Table 7 .