Descriptive analytics regarding sexual habits of one’s overall sample and you can the 3 subsamples from effective pages, former profiles, and you may low-users

Becoming single 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_{(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 model entering market, dating applications use and you will objectives regarding installations parameters due to the fact predictors getting how many protected full sexual intercourse’ partners certainly one of productive profiles

Efficiency from linear regression design typing market, relationships programs utilize and you will intentions out-of installation variables while the predictors for just how many protected complete sexual intercourse’ people among energetic users

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 one, 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, several years of application application, being heterosexual was in fact positively regarding the number of unprotected complete sex people

Productivity off linear regression design entering market, matchmaking apps incorporate and you may purposes out of installations details given that predictors having what amount of exposed complete sexual intercourse’ people certainly effective users

Searching for sexual lovers, years of application application, being heterosexual was undoubtedly regarding the amount of unprotected full sex lovers

Yields out of linear regression design typing market, relationship programs usage and purposes off installation details as australia women sexy the predictors getting exactly how many exposed complete sexual intercourse’ couples one of energetic 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_{(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 .