Descriptive analytics related to sexual behavior of the full take to and you can the 3 subsamples out-of active users, former users, and you will non-profiles
Becoming solitary decreases the level of exposed 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 er Brasiliansk kvinner 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 from linear regression model entering market, relationships applications usage and you may purposes regarding installations variables due to the fact predictors to possess what amount of protected full sexual intercourse’ couples certainly productive users
Output away from linear regression model entering demographic, matchmaking apps need and aim out of set up parameters since the predictors for exactly how many safe full sexual intercourse’ partners certainly effective 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 .
Interested in sexual people, numerous years of software utilization, and being heterosexual had been surely associated with the quantity of unprotected complete sex people
Production of linear regression model entering demographic, matchmaking apps utilize and you may purposes away from installment variables as predictors to possess how many unprotected complete sexual intercourse’ partners one of productive pages
Looking for sexual lovers, several years of software application, being heterosexual was in fact positively from the quantity of unprotected full sex partners
Efficiency off linear regression design entering demographic, relationship apps need and aim regarding set up variables as predictors to possess exactly how many unprotected complete sexual intercourse’ people certainly one of productive 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 .