Detailed statistics connected with sexual practices of one’s total attempt and the three subsamples from productive profiles, previous profiles, and non-profiles

Are single reduces the amount of exposed complete 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 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 out-of linear regression model entering market, dating apps usage and you can purposes regarding installment details just like the predictors to own just how many secure complete sexual intercourse’ couples one of energetic users

Yields off linear regression model typing demographic, relationships programs incorporate and you can aim out-of installation parameters while the predictors getting the number of secure complete sexual intercourse’ people among effective 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_{(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 partners, years of app use, and being heterosexual have been surely of amount of unprotected full sex lovers

Production away from linear regression design entering market, relationship software utilize and you can purposes regarding set up variables as the predictors to possess how many unprotected complete sexual intercourse’ lovers certainly active users

Shopping for sexual couples, many years of app usage, being heterosexual was in fact surely with the number of unprotected full sex lovers

Returns out of linear regression model typing market, dating apps utilize and you may motives out-of installations details once the predictors to possess the number of unprotected complete sexual intercourse’ partners among effective users

Hypothesis 2c A third multiple regression analysis was run, including demographic variables Manila wife 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 .