Detailed statistics related to sexual habits of one’s overall attempt and the three subsamples of effective users, former pages, and you will non-users
Getting solitary decreases 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 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.
Efficiency out of linear regression design entering market, dating applications incorporate and you can purposes from installation parameters because the predictors to own how many protected complete sexual intercourse’ couples certainly one of active pages
Output from linear regression design entering market, matchmaking software need and you may motives off installation details because the predictors to own the amount of secure full sexual intercourse’ couples one of productive 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 one, 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 .
Trying to find sexual couples, many years of software application, and being heterosexual have been certainly with the number of unprotected complete sex lovers
Returns out-of linear regression model entering group, dating applications need and you will intentions from set up variables once the predictors to possess just how many unprotected full sexual intercourse’ partners one of productive users
Seeking sexual partners, several years of software use, and being heterosexual were positively of number of unprotected full sex lovers
Efficiency out of linear regression model typing demographic, matchmaking programs need and you can intentions off set up variables because the predictors to own the amount of exposed full sexual intercourse’ lovers certainly energetic 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(step 1, 266) = 5.30, P = .022). App access frequency, looking for sexual partners, having a CNM relationship prettiest girls in the world 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 .