Descriptive analytics regarding sexual routines of total sample and you will the three subsamples from effective pages, previous users, and you may non-profiles
Are 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(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.
Productivity out-of linear regression design entering group, relationships software use and you may intentions out-of installation variables given that predictors to have the number of protected complete sexual intercourse’ people certainly active profiles
Productivity away from linear regression design entering group, dating programs incorporate and you can motives off installation parameters once the predictors to have just how many protected full sexual intercourse’ couples certainly active 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 .
Interested in sexual lovers, many years of software use, and being heterosexual was basically undoubtedly from the amount of exposed complete sex lovers
Returns from linear regression design entering market, matchmaking apps utilize and you will motives of installation parameters given that predictors to own the number of exposed full sexual intercourse’ couples among productive profiles
Trying to find sexual partners, years of app usage, and being heterosexual had been definitely on the level of unprotected complete sex lovers
Efficiency regarding linear regression model typing demographic, relationships applications usage and you can purposes regarding installment parameters because the predictors to have exactly how many exposed complete sexual intercourse’ partners one of 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) = 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 https://kissbridesdate.com/fi/blogi/miten-saada-saada-postimyynti-morsian/ 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 .
