17 Fev Differences in Sexual Habits One of Relationships Apps Pages, Previous Users and you can Non-profiles
Detailed statistics connected with sexual routines of full test and the three subsamples from effective pages, previous pages, and you can low-profiles
Are single reduces the level 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.
Production out-of linear regression design entering demographic, relationship programs utilize and you may intentions out-of installment details due to the fact predictors to have how many protected complete sexual intercourse’ people certainly one of productive pages
Productivity off linear regression design typing market, relationships software usage and you may motives out of installment details once the predictors to have exactly how many safe complete sexual intercourse’ lovers certainly one of energetic pages
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 .
Looking for sexual people, numerous years of software utilization, and being heterosexual was in fact surely regarding the quantity of exposed complete sex couples
Production out-of linear regression design entering market, dating applications utilize and you can objectives out-of installation parameters as predictors getting how many exposed full sexual intercourse’ lovers certainly one of productive pages
Trying to find sexual couples, numerous years of software application, being heterosexual had been surely associated with amount of unprotected complete sex partners
Yields out-of linear regression design typing demographic, relationship programs need and you can motives regarding construction details once the predictors to possess exactly how many exposed full sexual intercourse’ lovers certainly one of effective pages
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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 .