Differences in Sexual Behaviours Among Relationship Programs Users, Former Pages and you can Low-users

Detailed analytics regarding sexual routines of the complete try and you can the 3 subsamples out of effective pages, previous profiles, and you may low-users

Becoming 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_{(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.

Output out-of linear regression model typing market, matchmaking applications usage and sexy cartagena girls aim from installment parameters due to the fact predictors for exactly how many protected complete sexual intercourse’ people certainly one of energetic profiles

Returns from linear regression model entering market, relationship apps utilize and you can intentions out-of installations details since predictors having exactly how many protected complete sexual intercourse’ lovers among 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 1, 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 .

In search of sexual lovers, several years of app utilization, and being heterosexual was basically surely of the level of unprotected complete sex people

Productivity off linear regression model entering demographic, relationship apps use and you will aim regarding setting up parameters because predictors for exactly how many exposed complete sexual intercourse’ couples among active pages

Trying to find sexual lovers, years of software use, being heterosexual was basically positively of number of exposed complete sex people

Returns of linear regression design typing market, dating software use and you can intentions off construction details since the predictors to own what number of exposed full sexual intercourse’ couples among energetic 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 .