Detailed statistics about sexual routines of the complete test and you may the three subsamples of productive users, former pages, and you can low-users

Getting unmarried reduces the level of exposed 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 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.

Yields away from linear regression model https://kissbridesdate.com/hr/blog/latinske-stranice-i-aplikacije-za-upoznavanje/ entering market, relationships apps use and you will aim regarding setting up variables because predictors having the number of secure full sexual intercourse’ lovers among energetic users

Efficiency from linear regression model typing demographic, relationships software need and motives of installations variables because the predictors to own what amount of safe complete sexual intercourse’ partners among 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 .

In search of sexual couples, years of software use, being heterosexual was in fact seriously associated with the number of unprotected full sex couples

Productivity of linear regression design typing demographic, relationships applications usage and you can objectives regarding installations variables while the predictors to own exactly how many unprotected complete sexual intercourse’ partners certainly one of active profiles

Finding sexual people, numerous years of application application, being heterosexual have been certainly for the level of exposed complete sex lovers

Output out of linear regression design typing market, relationship programs usage and you will aim out of installations details since the predictors getting how many exposed complete sexual intercourse’ lovers certainly active 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 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_{(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 .