Descriptive analytics associated with sexual habits of one’s total test and you may the three subsamples out-of effective profiles, previous profiles, and non-profiles
Becoming single 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(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.
Output off linear regression design entering group, dating applications usage and you will aim out-of installment parameters given that predictors having just how many secure complete sexual intercourse’ couples certainly one of active users
Returns from linear regression model sexy eastern european girls typing demographic, relationships programs need and motives out-of installations variables due to the fact predictors to possess what number of safe full sexual intercourse’ lovers among productive 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 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 .
Selecting sexual people, many years of software use, being heterosexual was in fact surely on the amount of unprotected complete sex partners
Production off linear regression model entering group, relationships applications usage and you will aim from installation parameters as predictors having how many exposed complete sexual intercourse’ lovers among effective pages
Searching for sexual lovers, several years of app use, and being heterosexual had been definitely from the number of exposed full sex people
Efficiency out of linear regression design entering demographic, matchmaking software usage and you may aim off installment details as the predictors to possess exactly how many exposed full sexual intercourse’ couples certainly one of effective 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(step one, 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 .