Desk 4
As the concerns just how many secure full sexual intercourses on past 12 months, the study presented a positive significant effectation of another details: becoming men, becoming cisgender, academic level, becoming effective representative, are previous affiliate. To the contrary, a bad effected was seen into parameters becoming gay and many years. The remaining separate variables failed to inform you a mathematically tall impact towards the level of safe full intimate intercourses.
The brand new independent adjustable are men, getting gay, becoming unmarried, getting cisgender, being effective representative and being former users displayed a confident statistically high impact on the latest link-ups frequency. The other independent details don't show a critical impact on the connect-ups frequency.
In the long run, what number of exposed full intimate intercourses during the last twelve days additionally the connect-ups regularity emerged to have an optimistic statistically significant affect STI prognosis, while exactly how many safe complete intimate intercourses don't visited the value level.
Hypothesis 2a A first multiple linear regression analysis was run, including demographic variables and apps' pattern of usage variables, to predict the number of protected full sex partners in active users. The number of protected full sex partners was set as the dependent variable, while demographic variables (age, sex assigned at birth, gender, educational level, sexual orientation, relational status, jeter un coup d'oeil sur le lien and relationship style) and dating apps usage variables (years of usage, apps access frequency) and motives for installing the apps were entered as covariates. The final model accounted for a significant proportion of the variance in the number of protected full sex partners in active users (R 2 = 0.20, Adjusted R 2 = 0.18, F-change(step 1, 260) = 4.27, P = .040). Having a CNM relationship style, app access frequency, educational level, and being single were positively associated with the number of protected full sex partners. In contrast, looking for romantic partners or for friends were negatively associated with the considered dependent variable. Results are reported in Desk 5 .
Table 5
Productivity of linear regression model entering demographic, relationships software need and intentions of set up parameters just like the predictors to have just how many protected complete sexual intercourse' partners among effective 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 1, 260) = 4.34, P = .038). Looking for sexual partners, years of app utilization, and being heterosexual were positively associated with the number of unprotected full sex partners. 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 .
Table 6
Efficiency away from linear regression design entering demographic, matchmaking applications utilize and you may objectives out-of installations details as the predictors to own the amount of exposed complete sexual intercourse' lovers among effective pages
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 .
