Detailed analytics about sexual habits of your own complete take to and you may the three subsamples of active pages, previous profiles, and low-profiles
Being solitary reduces the amount of unprotected full 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 https://kissbridesdate.com/hr/whatsyourprice-recenzija/ groups (F(dos, 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.
Output out of linear regression model typing demographic, dating apps usage and you may intentions regarding set up parameters because the predictors for exactly how many protected complete sexual intercourse’ couples certainly effective pages
Yields off linear regression design entering demographic, relationships apps need and you can motives out of construction variables due to the fact predictors having just how many protected full sexual intercourse’ partners certainly active users
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 .
Seeking sexual partners, several years of software utilization, being heterosexual was certainly associated with the amount of exposed full sex partners
Yields of linear regression design typing demographic, matchmaking software usage and you will intentions of setting up parameters given that predictors to possess just how many unprotected full sexual intercourse’ lovers one of energetic profiles
Searching for sexual partners, several years of app use, being heterosexual was positively on the quantity of unprotected full sex people
Productivity off linear regression model entering market, relationships software use and you will aim away from construction details once the predictors to own exactly how many unprotected full sexual intercourse’ couples certainly productive profiles
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 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 one, 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 .