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Variations in Sexual Habits Certainly Dating Apps Users, Previous Pages and you may Low-profiles

Detailed analytics about sexual routines of one’s overall test and the three subsamples off effective pages, former pages, and you may low-pages

Getting unmarried decreases the number of exposed complete sexual intercourses

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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.

Efficiency off linear regression model typing market, matchmaking apps need and you can aim out-of installment variables since the predictors to possess the number of protected complete sexual intercourse’ lovers among productive profiles

Yields from linear regression design entering demographic, relationship apps use and you may purposes of set up details given that predictors getting the number of protected full sexual intercourse’ lovers one of productive 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(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 .

In search of sexual partners, numerous years of app utilization, and being heterosexual was in fact certainly for the quantity of unprotected complete sex couples

Production off linear regression design entering market, dating programs need and you may purposes away from installations parameters since the predictors to possess how many unprotected complete sexual intercourse’ lovers certainly energetic profiles

Seeking sexual lovers, years of software usage, being heterosexual was in fact undoubtedly regarding the quantity of exposed complete sex lovers

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Returns regarding linear regression design typing demographic, relationship software incorporate and you will intentions of construction parameters because predictors to have exactly how many unprotected full sexual intercourse’ people certainly energetic profiles

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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(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 .