Differences in Sexual Habits Certainly Relationship Applications Profiles, Previous Profiles and you can Low-profiles

Descriptive statistics about sexual behaviors of your total shot and the three subsamples out-of productive profiles, previous profiles, and you may non-profiles

Being solitary reduces the number of unprotected full sexual intercourses

In regard to the number of partners with whom participants had protected full sex during Tysk kone 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 out-of linear regression design typing demographic, relationships programs use and you can motives off construction parameters while the predictors having just how many protected full sexual intercourse’ people among energetic pages

Output from linear regression design typing market, dating apps incorporate and you will purposes of setting up details as the predictors to possess the amount of safe complete sexual intercourse’ partners certainly one of active 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 .

Interested in sexual couples, several years of application use, and being heterosexual were certainly with the quantity of exposed complete sex partners

Output out of linear regression model entering demographic, relationship apps incorporate and you will motives of installations parameters because the predictors to own what number of unprotected complete sexual intercourse’ lovers certainly one of productive profiles

Finding sexual lovers, numerous years of software use, and being heterosexual was in fact surely on the quantity of unprotected complete sex couples

Yields away from linear regression design typing group, matchmaking software use and you may aim off installation parameters due to the fact predictors having just how many exposed full sexual intercourse’ partners certainly energetic profiles

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 .