Differences in Sexual Behaviors Among Matchmaking Software Users, Former Pages and you can Low-profiles

Detailed statistics linked to sexual practices of your full try and you may the three subsamples away from productive pages, previous users, and you may non-users

Being single decreases the amount of exposed 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 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 of linear regression model entering market, dating software use and you may objectives from installation details because predictors to have the number of safe full sexual intercourse’ partners certainly productive pages

Yields of linear regression model typing demographic, relationships apps need and purposes out-of installation details due to the fact predictors to possess the number of 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 see this here 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 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 .

Seeking sexual partners, several years of software application, and being heterosexual was basically surely for the quantity of unprotected complete sex people

Yields away from linear regression design typing group, relationships programs usage and you can purposes off setting up details due to the fact predictors for how many unprotected full sexual intercourse’ lovers among energetic pages

Shopping for sexual couples, several years of application application, and being heterosexual was seriously of this level of exposed complete sex partners

Yields away from linear regression model entering market, relationship programs utilize and you may aim away from construction variables since predictors to possess what amount of exposed complete sexual intercourse’ couples among active users

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 .