Descriptive statistics related to sexual behavior of the total attempt and you will the three subsamples out-of active pages, former profiles, and you will non-profiles
Are single reduces the level 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.
Yields away from linear regression model entering demographic, relationship apps utilize and you can intentions away from installment parameters once the predictors to have the number of safe complete sexual intercourse’ couples certainly active profiles
Output of linear regression model typing demographic, matchmaking programs utilize and intentions of setting up details as the predictors having just how many protected full sexual intercourse’ lovers among effective 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 georgian women for marriage 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 .
Searching for sexual couples, many years of software application, and being heterosexual was definitely from the amount of exposed complete sex lovers
Output out-of linear regression model typing group, relationships applications usage and you may aim out of installation variables since the predictors to own exactly how many unprotected full sexual intercourse’ lovers one of effective pages
Finding sexual people, years of software utilization, and being heterosexual was indeed positively of level of unprotected full sex couples
Output from linear regression design entering demographic, matchmaking applications utilize and aim off set up parameters as predictors for just how many exposed complete sexual intercourse’ people certainly energetic pages
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 .