Descriptive statistics about sexual practices of the complete decide to try and you may the three subsamples away from productive profiles, previous users, and you can non-pages
Being unmarried reduces the number 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(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 https://kissbridesdate.com/no/nederlandske-bruder/ 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 typing group, relationship applications use and you may aim of set up variables as predictors having how many secure complete sexual intercourse’ couples certainly one of effective pages
Productivity from linear regression model entering group, dating apps need and you may intentions out of installment variables because the predictors for the amount of safe complete sexual intercourse’ people among energetic 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(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, years of application usage, and being heterosexual had been certainly regarding the quantity of unprotected full sex partners
Productivity out of linear regression model typing group, relationships programs usage and you can aim out of setting up details given that predictors to own how many unprotected full sexual intercourse’ partners among energetic users
Shopping for sexual lovers, numerous years of application usage, being heterosexual was indeed surely of this amount of exposed complete sex partners
Returns of linear regression model entering group, matchmaking programs utilize and you may intentions regarding construction parameters because predictors to have the number of exposed complete sexual intercourse’ lovers one of 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(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 .
