Detailed analytics pertaining to sexual habits of one’s complete sample and the three subsamples from energetic users, previous users, and you will non-pages
Becoming solitary reduces the quantity 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(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.
Returns off linear regression design entering group, relationships programs need and you will purposes regarding setting up parameters because the predictors to possess just how many secure complete sexual intercourse‘ lovers one of effective profiles
Returns of linear regression design typing group, relationship software use and you may objectives off setting up parameters given that predictors for the amount of secure complete sexual intercourse‘ lovers 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(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 .
Shopping for sexual people, several years of software use, and being heterosexual were positively from the amount of exposed complete sex partners
Output away from linear regression design typing group, relationship applications usage and motives out of installations variables given that predictors to possess what amount of unprotected complete sexual intercourse‘ couples certainly productive pages
Seeking sexual people, many years of application application, and being heterosexual was in fact definitely associated with level of unprotected complete sex couples
Returns out-of linear regression design typing group, relationships programs need and you may objectives from construction variables given that predictors to have the number of exposed full sexual intercourse‘ lovers among productive pages
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) his comment is here = 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 .
