Descriptive statistics linked to sexual habits of your own total shot and you can the 3 subsamples away from energetic profiles, former users, and you can non-users
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, daterer Taiwanese kvinner pГҐ nettet 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 model typing demographic, matchmaking applications use and you can objectives regarding installment parameters as the predictors for what number of secure full sexual intercourse’ lovers certainly one of productive profiles
Returns off linear regression design typing group, dating apps need and you can purposes off setting up details given that predictors getting the amount of secure complete sexual intercourse’ couples certainly one of effective 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 .
Wanting sexual couples, numerous years of software use, and being heterosexual have been positively from the level of unprotected full sex lovers
Output out-of linear regression design typing group, relationship programs incorporate and you may objectives from setting up variables due to the fact predictors getting how many unprotected full sexual intercourse’ couples certainly one of effective profiles
Searching for sexual partners, many years of software application, being heterosexual were seriously for the quantity of exposed full sex couples
Efficiency off linear regression design typing market, relationships apps usage and you will motives from construction variables due to the fact predictors having what number of unprotected complete sexual intercourse’ lovers among energetic 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 one, 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 .
