Descriptive analytics related to sexual behavior of one’s overall shot and you may the three subsamples out-of active users, previous users, and you may low-users

Getting unmarried decreases the quantity of exposed full sexual intercourses

In Sri Lankan vakre kvinner 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.

Productivity out-of linear regression model typing group, matchmaking apps need and you can intentions out of setting up variables because predictors for the amount of secure full sexual intercourse’ couples certainly one of productive users

Output from linear regression model entering group, relationships software usage and you may motives out of installment variables since the predictors to possess the amount of safe full sexual intercourse’ lovers one of productive users

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 .

Finding sexual partners, years of application utilization, being heterosexual was basically absolutely in the amount of exposed complete sex people

Productivity from linear regression design typing demographic, matchmaking programs incorporate and you may intentions regarding construction parameters just like the predictors for what amount of exposed complete sexual intercourse’ people certainly productive profiles

Looking for sexual lovers, many years of application usage, and being heterosexual was in fact definitely for the amount of exposed full sex partners

Yields away from linear regression model typing group, matchmaking software usage and you can aim of installation details since the predictors getting what number of exposed complete sexual intercourse’ lovers one of effective 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 .