Descriptive analytics related to sexual habits of one’s full shot and you can the 3 subsamples out of active pages, previous users, and low-pages
Getting solitary decreases the level of unprotected complete sexual intercourses
In regard to the number of partners with whom kissbridesdate.com Internett 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.
Efficiency away from linear regression design entering market, matchmaking software usage and you can motives from set up details while the predictors to have the amount of protected full sexual intercourse’ partners among productive pages
Output regarding linear regression design typing demographic, dating apps use and you will objectives of setting up details once the predictors having what amount of protected full sexual intercourse’ partners certainly effective profiles
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 .
Seeking sexual people, many years of application use, being heterosexual had been seriously of the quantity of unprotected complete sex people
Efficiency away from linear regression design entering demographic, matchmaking apps utilize and aim away from installment details just like the predictors getting what number of unprotected complete sexual intercourse’ couples certainly one of energetic profiles
In search of sexual lovers, numerous years of software utilization, and being heterosexual was in fact surely on the number of unprotected complete sex lovers
Productivity away from linear regression design entering group, matchmaking software utilize and you will intentions away from setting up parameters while the predictors to own just how many exposed full sexual intercourse’ lovers among active 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) = 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 .