Desk cuatro
Given that questions just how many safe full intimate intercourses regarding past 1 year, the analysis exhibited a positive significant aftereffect of the second details: are men, becoming cisgender, instructional level, are active user, becoming former user. On the other hand, a bad effected try seen toward parameters getting gay and decades. The rest separate details did not tell you a statistically high feeling toward level of protected complete sexual intercourses.
The fresh new separate varying becoming men, are homosexual, becoming single, are cisgender, becoming active member and being previous users displayed a confident mathematically extreme effect on the hook-ups volume. One other separate parameters don’t tell you a critical effect on the link-ups volume.
Fundamentally, what amount of unprotected complete intimate intercourses over the past several weeks therefore the hook up-ups regularity came up to have a confident statistically extreme influence on STI analysis, while just how many secure complete intimate intercourses failed to visited the benefits 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, 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
Production of linear regression model entering demographic, relationship software usage and you can intentions off construction parameters while the predictors for what number of secure complete sexual intercourse’ lovers 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 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 Dining table six .
Table 6
Output out of linear regression design typing group, relationship apps need and you can aim from installations details since predictors for the amount of unprotected full intimate intercourse’ lovers certainly energetic users
Hypothesis 2c https://brightwomen.net/fr/femmes-guatemalan/ 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 .