Dining table cuatro

Just like the issues what amount of safe complete sexual intercourses regarding the last 12 months, the research presented a positive tall effect of the following details: are male, getting cisgender, educational height, being effective affiliate, getting former user. To the contrary, a poor affected are observed to your variables getting homosexual and you may age. The rest independent details don’t let you know a mathematically tall effect toward quantity of secure full intimate intercourses.

The fresh independent adjustable becoming men, getting gay, being unmarried, being cisgender, are effective affiliate and being previous pages displayed an optimistic statistically significant affect the latest link-ups regularity. Another separate variables didn’t tell you a significant impact on the fresh connect-ups regularity.

Finally, just how many unprotected full sexual intercourses over the past twelve days as well as the connect-ups volume emerged to own an optimistic mathematically tall influence on STI analysis, while exactly how many safe complete intimate intercourses Rencontres femmes Malaisien failed to started to the value peak.

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, 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_{(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 Table 5 .

Table 5

Efficiency out of linear regression model entering market, matchmaking applications usage and aim from installations details since the predictors to have the amount of protected full intimate intercourse’ partners certainly one of effective pages

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). 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 six .

Table 6

Output off linear regression design typing market, matchmaking programs incorporate and you can intentions away from construction parameters just like the predictors for what number of exposed complete intimate intercourse’ couples among productive 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 .