Differences in Sexual Behaviours One of Dating Programs Pages, Previous Pages and you can Non-pages
Detailed statistics related to sexual behaviors of your own total sample and you can Nancy wife the three subsamples from active pages, former profiles, and you will non-users
Being unmarried reduces the amount 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.
Productivity away from linear regression design entering market, relationships programs utilize and you can intentions out-of installations variables just like the predictors to own how many protected complete sexual intercourse’ partners among active profiles
Returns out-of linear regression model entering demographic, matchmaking programs incorporate and you may motives regarding set up parameters because predictors for what amount of safe complete sexual intercourse’ partners among productive 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 = 0.14, 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 people, numerous years of application use, being heterosexual was absolutely associated with the number of exposed full sex couples
Output out-of linear regression design entering group, relationship applications usage and you can intentions off installment details as predictors getting what amount of unprotected complete sexual intercourse’ lovers certainly productive pages
Interested in sexual lovers, many years of app application, and being heterosexual was indeed undoubtedly with the level of unprotected full sex partners
Returns out of linear regression design entering demographic, relationships software utilize and you may purposes from setting up variables because predictors having how many exposed full sexual intercourse’ partners among 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 .
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