Variations in Sexual Behaviours Among Dating Applications Users, Former Profiles and Low-users
Detailed statistics related to sexual practices of complete sample and you may the 3 subsamples of energetic users, former users, and you will non-profiles
Being unmarried reduces the quantity of unprotected full 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 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.
Production regarding linear regression design entering market, relationship software utilize and you will purposes away from set up details since predictors for the amount of safe full sexual intercourse’ partners certainly energetic pages
Output regarding linear regression design typing group, dating applications incorporate and you may motives away from installation parameters while the predictors to have just how many secure full sexual intercourse’ lovers among active 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 mladenka Venezuelan.14, F-change(step 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 application, and being heterosexual was basically surely of level of exposed full sex people
Returns out of linear regression design entering demographic, matchmaking apps need and you can purposes from construction variables while the predictors getting the number of unprotected complete sexual intercourse’ lovers one of productive profiles
Searching for sexual partners, many years of application use, and being heterosexual was indeed seriously from the level of exposed full sex lovers
Efficiency regarding linear regression design entering demographic, dating apps incorporate and you will aim regarding setting up parameters due to the fact predictors to possess how many exposed full sexual intercourse’ couples one of effective 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 .
