Variations in Sexual Behaviours Among Relationships Applications Profiles, Former Users and you will Non-profiles

Descriptive analytics connected with sexual practices of one’s total sample and you can the 3 subsamples out of active users, former users, and you may low-users

Being unmarried reduces the level of unprotected 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_{(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 bride Toulouse 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.

Efficiency away from linear regression design typing group, dating applications usage and aim out of installment parameters just like the predictors getting the number of protected full sexual intercourse’ people one of productive users

Productivity away from linear regression design typing group, relationship programs use and intentions regarding setting up details once the predictors to own the amount of secure complete sexual intercourse’ lovers certainly 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 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 application use, being heterosexual was indeed surely of number of exposed full sex couples

Output off linear regression model typing market, relationships applications use and you may objectives out of construction variables as the predictors to possess the number of unprotected complete sexual intercourse’ lovers certainly active profiles

Interested in sexual people, several years of app use, being heterosexual have been undoubtedly in the quantity of exposed full sex couples

Output of linear regression design typing demographic, matchmaking apps need and objectives of construction details since predictors to possess exactly how many exposed complete sexual intercourse’ partners one of active 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 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 .