Correlates of Tinder Use and Risky Sexual Behaviors in Young Adults

Abstract

Tinder is a frequently used geosocial networking application that allows users to meet sexual partners in their geographical vicinity. Research examining Tinder use and its association with behavioral outcomes is scarce. The objectives of this study were to explore the correlates of Tinder use and risky sexual behaviors in young adults. Participants aged 18–26 were invited to complete an anonymous online questionnaire between January and May 2016. Measures included sociodemographic characteristics, Tinder use, health related behaviors, risky sexual behaviors, and sexual attitudes. Associations among these variables were estimated using multivariate logistic regressions. The final sample consisted of 415 participants (n = 166 Tinder users; n = 249 nonusers). Greater likelihood of using Tinder was associated with a higher level of education (OR = 2.18) and greater reported need for sex (OR = 1.64), while decreased likelihood of using Tinder was associated with a higher level of academic achievement (OR = 0.63), lower sexual permissiveness (OR = 0.58), living with parents or relatives (OR = 0.38), and being in a serious relationship (OR = 0.24). Higher odds of reporting nonconsensual sex (OR = 3.22) and having five or more previous sexual partners (OR = 2.81) were found in Tinder users. Tinder use was not significantly associated with condom use. This study describes significant correlates of using Tinder and highlights a relationship between Tinder use with nonconsensual sex and number of previous sexual partners. These findings have salience for aiding public health interventions to effectively design interventions targeted at reducing risky sexual behaviors online.

Introduction

Over the last few years, the Internet and geosocial networking (GSN) applications have emerged as popular forums to meet potential sexual partners. For example, a survey of a large Swedish sample found that 35% of men and 40% of women aged 18–65 met a sexual partner online.¹ The GSN application Tinder, established in 2012, has become increasingly popular.^2,3 Tinder allows users to anonymously view a handful of profile pictures in their geographic vicinity and ‘like’ another user by swiping right or “pass” by swiping left. Mutually interested users are ‘matched’ and can then chat, meet, and engage in a sexual or romantic relationship. While the number of visits to classic dating sites (e.g., Match.com and OkCupid) has been constant in the last year, the number of users of GSN applications (e.g., Tinder) is increasing.^4,5 Tinder has an estimated 50 million users worldwide, with 39% between 16 and 24 years of age.^6,7 Young adults who have an interest in sexual exploration may use apps such as Tinder.⁸ Tinder is fast, casual, easy to use, and the preferred dating application among college students.⁹ For example, a recent study found that 17% of participants reported that they engaged in casual sex on a Tinder date.¹⁰

There is a great necessity to study partner-seeking behaviors online in general and to evaluate Tinder use specifically, as there have been assertions of a relationship between Tinder use and undesirable outcomes. For example, the Rhode Island Department of Health (2015) released a press statement describing a sexually transmitted infection (STI) “epidemic” and indicated that the increase of STIs has been attributed to the use of social networking sites (such as Tinder) to arrange casual and anonymous sexual encounters.¹¹

There is limited research investigating the characteristics of emerging GSN application (e.g., Tinder) users and associated behaviors, with most research evaluating partner seeking on the Internet (although not Tinder per se).⁷ Previous studies have shown that an increase of online sexual activity among young adults, including seeking sexual partners on the Internet, is associated with a lower Grade Point Average (GPA),¹² older age,^12–14 higher comfort or interest in sexually related topics, and less religiosity.¹⁵ One study found no significant difference in sexual permissiveness between Tinder users and nonusers after controlling for age; however, this study was conducted using small samples (Tinder users n = 30, nonusers n = 19) and was not specific to young adults.¹⁶

Young adults seeking sexual partners online have also been associated with negative health outcomes such as increased risk of contracting an STI,^{11,12,17–19} unwanted pregnancies,¹² sexual regret, anxiety, and depression.²⁰ In addition, various risky behaviors have been associated with seeking sexual partners on the Internet and mobile-based applications, including condomless sex,^7,13,17,21 increased number of previous sexual partners,^7,18,22 and increased alcohol use.²¹ Furthermore, a recent study by Cabecinha et al. in British adults (n = 15 162) found that seeking a sexual partner online was associated with condomless sex, higher number of partners, and greater STI diagnoses and HIV testing (in men).⁷ Comparatively, there has been little research examining Tinder use and sexual behaviors. To our knowledge, only one published abstract exists that has associated Tinder use with problematic alcohol use, nonconsensual sex, and sexual hookups in a small sample (n = 44) of female college students.²³

There is a need to better understand the correlates of Tinder use and risky sexual behaviors. In particular, there is a paucity of literature evaluating and comparing the correlates of three risky sexual behaviors: not using condoms, multiple sexual partners, and engaging in nonconsensual sex. Greater research is required to investigate the psychosocial correlates of Tinder use, an increasingly popular GSN application, with sociodemographic characteristics, attitudes, psychosocial factors, and behavioral outcomes in young adults. Furthermore, the available literature on online partner seeking has been mostly examined in men who have sex with men (MSM),^3,22,24,25 with a scarcity of research conducted in the general college population.¹⁷ The objectives of this study were twofold: (1) to assess the correlates of Tinder use and (2) to assess correlates of three sexual behaviors in young adults.

Materials and Methods

Participants and data collection

Data were collected through an English online survey, hosted by Qualtrics, a survey hosting service, between January and May 2016. Males and females, aged 18–26, were eligible to participate in this study. Participants were recruited at McGill University, located in Montreal, Canada. Participants were recruited using two strategies. Students in the psychology undergraduate program received course credit as compensation to participate. In addition, to recruit a larger and more diverse sample of university students, we also recruited participants through advertisements (flyers) placed around the campus and using social media announcements on Facebook, who were entered into a draw to win one of two cash prizes. The recruitment statement specified that ‘We are looking for participants (aged 18–26) to complete a 45-minute questionnaire that will be evaluating dating, relationship, and sexual health practices’. The study was approved by McGill University's Research Ethics Board (#295–1215).

Measures

The survey items were selected based on findings from the existing research literature concerning correlates of online sexual partner seeking.^26,27 The following validated scales were included: (1) the Sexual Compulsivity Scale (10 items measured from 1- “not at all like me” to 4- “very much like me”, e.g., “my sexual thoughts and behaviors are causing problems in my life”)²⁶; (2) the Brief Sexual Attitudes Scale (BSAS; 23 items measured from 1-“strongly agree” to 5-“strongly disagree”).²⁸ The BSAS consists of four subscales: permissiveness (10 items; e.g., “casual sex is acceptable”), birth control (3 items; e.g., “birth control is part of responsible sexuality”), communion (5 items; e.g., “sex is usually an intensive, almost overwhelming experience”), and instrumentality (5 items; e.g., “sex is primarily a bodily function, like eating”)²⁸; and (3) two subscales from the Need for Sexual Intimacy Scale (NSIS; measured from 1- “disagree definitely” to 6- “agree definitely”): Need for Sex (8 items; e.g., “I need sex everyday”), and Need for Affiliation (9 items; “I need a partner who loves me”).²⁷ Mean scores were calculated for sexual compulsivity, permissiveness, birth control, communion, instrumentality, need for sex, and need for affiliation.

Other measures included assessments of sociodemographic characteristics (e.g., gender, sexual orientation, education, and so on), general sexual health related behaviors and outcomes (e.g., age at first sexual intercourse, history of STI, and vaccination against HPV),²⁹ Tinder use (“do you use Tinder?”), and sexual behaviors. Three different sexual behaviors were examined: condom use (“the last time you had oral or genital intercourse, did you or your partner use protection (e.g., a condom)?”), previous number of sexual partners (“during your life, with how many people have you had sexual intercourse (oral and/or genital)?”), and nonconsensual sex (“has someone who you met tried to have oral and/or genital intercourse with you without your consent?”).³⁰

Data cleaning and analysis

Data cleaning involved removing participants in the following successive steps (Fig. 1): (1) duplicates; (2) age eligibility criteria (aged 18–26) were not met; (3) incorrect answer to the attention check question (i.e., “Barack Obama was the first president of the United States”); (4) fewer than 4 minutes questionnaire completion time; (5) missing response to the question “do you use Tinder” without which data analysis would not be possible; (6) missing more than 50% of responses to the survey; and (7) outliers in terms of number of sexual partners. Missing values for scale scores and continuous variables were replaced by means.

FIG. 1.

Data cleaning flow diagram.

Descriptive statistics was calculated for demographic items. We used the two-sample tests for equality of proportions and t tests to assess significant differences. Linear measured outcomes were tested for normality and were dichotomized if extremely skewed.³¹ For binary outcomes, we used multivariate logistic regression and reported odds ratios and 95% confidence intervals. We included in the multivariate logistic regression models all independent variables of interest simultaneously. The following logistic regression model diagnostic criteria were used: (1) Rank Discrimination Index C whereby higher c values indicated better model ability to classify individuals correctly into groups according to their outcome (C = 0.5 indicates random guessing and c = 1 perfect discrimination), (2) Bayesian Information Criterion (BIC) for comparing models whereby the model with the lowest BIC was preferred,³² (3) Variation Inflation Factor (VIF) with a cutoff value of <10 for ruling out collinearity issues,³³ and (4) Cessie–van Houwelingen goodness-of-fit test whereby p > 0.05 suggests no evidence to reject a good fit.³⁴

For Tinder use, we studied multiple models containing interactions between independent variables and compared these models with the model without interactions. The selection of the multivariate logistic regression model for examining Tinder use unfolded in two phases. In the first phase, we excluded term interaction models with VIF >10. In the second phase, we used the lowest BIC value to select the final model.

Analysis was performed in SPSS Statistics v.23 and R v3.3.2.

Results

Sample

Data cleaning results are displayed in Figure 1.^a The final sample consisted of 415 participants, with 166 Tinder users (40%) and 249 non-Tinder users (60%). In total, 210 individuals were recruited from the psychology undergraduate participant pool program (82% female), and 201 individuals were recruited using advertisement around the university (79% female) (Supplementary Table S1; Supplementary Data are available online at www.liebertpub.com/cyber). The sample consisted predominantly of females (81%), individuals who identified as straight (80%), White individuals (55%), individuals who identified as atheist or agnostic (48%), individuals who lived with peers or partners (60%), and individuals who reported being in a serious relationship (42%). Sociodemographic characteristics and significant differences between Tinder users and nonusers are displayed in Table 1.

Table 1.

Sociodemographic Characteristics of the Total Sample, Tinder Users, and Nonusers

	Total n = 415	Tinder users n = 166	Nonusers n = 249
	n (%)	n (%)	n (%)
Gender
Female	336 (81.0)	130 (78.3)	206 (82.7)
Male	77 (18.6)	36 (21.7)	41 (16.5)
Sexual orientation
Straight	333 (80.2)	126 (75.9)	207 (83.1)
Lesbian, Gay, Bisexual (LGB)	57 (13.7)	30 (18.1) ^a	27 (10.8)
Other (e.g., queer, questioning)	25 (6.0)	10 (6.0)	15 (6.0)
Education
High school	215 (51.8)	90 (54.2)	125 (50.2)
College/University	200 (48.2)	76 (45.8)	124 (49.8)
Ethnicity
White	227 (54.7)	100 (60.2)	127 (51.0)
East or South Asian	118 (28.4)	43 (25.9)	75 (30.1)
Other (e.g., Arab, Black, Latin)	70 (16.9)	23 (13.9)	47 (18.9)
Religion
Atheist/agnostic	197 (47.5)	89 (53.6) ^a	108 (43.4)
Christian	89 (21.4)	32 (19.3)	57 (22.9)
Other (i.e., Islam, Hinduism, Buddhism, Judaism)	129 (31.1)	45 (27.1)	84 (33.7)
Living situation
Peers/partners	249 (60.0)	118 (71.1) ^b	131 (52.6)
Parents/relatives	108 (26.0)	28 (16.9)	80 (32.1) ^b
Alone	57 (13.7)	20 (12.0)	37 (14.9)
Relationship status
Serious relationship	175 (42.2)	40 (24.1)	135 (54.2) ^b
Single	172 (41.4)	81 (48.8) ^a	91 (36.5)
Single but casually dating	68 (16.4)	45 (27.1) ^b	23 (9.2)
	Mean (SD)	Mean (SD)	Mean (SD)
Age	20.73 (1.73)	20.56 (1.63)	20.84 (1.79)
GPA	3.36 (0.65)	3.25 (0.51)	3.42 (0.73) ^b

Bold integers indicate a significant difference between Tinder and non-Tinder samples. GPA = grade point average. “Other” is not displayed for “gender” and “living situation” as it contains two or less cases.

significance level <0.05.

Significance level <0.01.

Correlates of Tinder users compared to nonusers

Results of multivariate logistic regression and model fit diagnostics are presented in Table 2. Increased odds of using Tinder were associated with higher education (OR = 2.18) and greater need for sex (OR = 1.64). Decreased odds of using Tinder was associated with having a higher GPA (OR = 0.63), decreased sexual permissiveness (OR = 0.58), living with parents or relatives (OR = 0.38), and being in a serious relationship (OR = 0.24).

Table 2.

Multivariate Logistic Regression of Tinder Use Compared to Nonuse

Independent variables	Independent variable category (Reference)	OR	95% CI
Gender	Female (Male)	0.90	0.46–1.74
Sexual orientation	LGB (Straight)	1.64	0.82–3.26
Sexual orientation	Other (Straight)	1.15	0.39–3.33
Education	College/University (High school)	2.18	1.15–4.16
Ethnicity	East or South Asian (White)	0.96	0.55–1.69
Ethnicity	Other (i.e., Arab, Black, Latin) (White)	0.53	0.27–1.06
Religion	Atheist/Agnostic (Christian)	1.10	0.55–2.19
Religion	Other (i.e., Islam, Hinduism, Buddhism, Judaism) (Christian)	0.97	0.50–1.90
Living situation	Peers/partners (Alone)	1.39	0.66–2.92
Living situation	Parents/relatives (Alone)	0.38	0.15–0.96
Relationship Status	Serious Relationship (Single)	0.24	0.14–0.42
Relationship Status	Single but casually dating (Single)	1.91	0.96–3.80
Age (M = 20.73; SD = 1.73)	22 (19)	0.75	0.45–1.23
GPA (M = 3.36; SD = 0.64)	3.7 (3.09)	0.63	0.46–0.87
Importance of religion in daily life (M = 3.59; SD = 1.38)	5 (2)	1.24	0.65–2.36
Age at first sexual intercourse (M = 17.64; SD = 1.63)	18 (17)	1.02	0.88–1.19
History of STI	Yes (No)	2.72	0.89–8.35
Vaccinated against HPV	Yes (No)	0.86	0.52–1.44
Compulsivity score (M = 1.4; SD = 0.47)	1.5 (1.1)	1.04	0.83–1.30
Permissiveness score (M = 2.99; SD = 0.86)	3.55 (2.35)	0.58	0.37–0.90
Birth control score (M = 1.56; SD = 0.75)	2 (1)	0.89	0.64–1.24
Communion score (M = 2.55; SD = 0.79)	3 (2)	1.05	0.76–1.47
Instrumentality score (M = 3.06; SD = 0.72)	3.6 (2.6)	1.07	0.74–1.55
Need for sex score (M = 2.95; SD = 1.00)	3.63 (2.25)	1.64	1.10–2.44
Need for affiliation score (M = 4.56; SD = 0.85)	5.78 (4.5)	1.22	0.85–1.76

Tinder users (n = 166) were compared to nonusers (n = 246) to examine differences in sociodemographic characteristics, sexual history, and sexual attitudes. Two and one Tinder nonusers were, respectively, excluded due to missing data for gender and living situation. Bold indicates that odds ratios and confidence intervals are statistically significant, (p < 0.05). For interval data, the third quartiles are compared to the first quartiles (reference in brackets). Model fit indices: C = 0.792, Cessie–van Houwelingen p = 0.98, VIF (1.11; 2.82), and BIC = 597.63.

BIC, Bayesian Information Criterion; VIF, variation inflation factor; OR, odds ratio; CI, confidence interval; M, mean; SD, standard deviation.

Correlates of sexual behaviors

The assumption of normality did not hold for the number of previous sexual partners (M = 5.67; SD = 6.31, Shapiro–Wilk test p < 0.001). Moreover, this variable was extremely skewed and was therefore dichotomized.

The binomial simple logistic regression analyses examining the relationship between Tinder use and sexual behaviors can be found in the Supplementary Table S2. We used three multivariate logistic models to assess correlates of three risky sexual behaviors: (1) condom use at the last sexual intercourse, (2) number of previous sexual partners, and (3) nonconsensual sex. A correlation matrix of continuous independent variables can be found in Supplementary Table S3. The correlates of three risky sexual behaviors and model fit diagnostics are presented in Table 3.

Table 3.

Multivariate Logistic Regressions of Risky Sexual Behaviors

Independent variables (Reference)	Condom use at last intercourse OR (95%CI), n = 341	Number of previous sexual partners OR (95%CI), n = 327	Nonconsensual sex OR (95%CI), n = 412
Tinder use (No)	1.40 (0.81–2.39)	2.81 (1.39–5.69)	3.22 (1.77–5.86)
Female (Male)	2.43 (1.21–4.89)	1.09 (0.46–2.60)	2.53 (1.12–5.70)
LGB (Straight)	a	1.05 (0.45–2.43)	2.80 (1.38–5.69)
Other (e.g., queer, questioning) (Straight)	a	0.92 (0.22–3.91)	1.03 (0.32–3.33)
College/University (High school)	1.08 (0.57–2.04)	1.61 (0.70–3.70)	1.23 (0.61–2.48)
East or South Asian (White)	1.18 (0.65–2.14)	0.57 (0.27–1.20)	0.63 (0.32–1.26)
Other (i.e., Arab, Black, Latin) (White)	0.92 (0.46–1.83)	0.81 (0.34–1.96)	0.86 (0.40–1.87)
Atheist or Agnostic (Christian)	1.58 (0.78–3.19)	0.56 (0.23–1.40)	0.91 (0.41–1.99)
Other (i.e., Islam, Hinduism, Buddhism, Judaism) (Christian)	1.04 (0.52–2.05)	0.64 (0.26–1.57)	0.51 (0.23–1.11)
Peers or partners (Alone)	0.73 (0.35–1.53)	0.24 (0.09–0.66)	0.56 (0.26–1.21)
Parents or relatives (Alone)	0.48 (0.19–1.16)	0.14 (0.04–0.49)	0.23 (0.08–0.64)
Serious relationship (Single)	0.41 (0.23–0.73)	0.75 (0.35–1.61)	1.93 (1.00–3.69)
Single but casually dating (Single)	0.68 (0.32–1.42)	4.12 (1.64–10.38)	0.77 (0.34–1.74)
Age (22 vs. 19)	0.77 (0.47–1.26)	2.52 (1.28–4.94)	0.94 (0.53–1.67)
GPA (3.7 vs. 3.09)	0.98 (0.79–1.23)	0.91 (0.71–1.17)	1.08 (0.86–1.35)
Importance of religion (5 vs. 2)	0.78 (0.40–1.49)	0.68 (0.29–1.60)	0.45 (0.21–0.97)
Age at first sexual intercourse (18 vs. 17)	1.15 (1.00–1.33)	0.44 (0.35–0.56)	0.81 (0.68–0.97)
History of a STI (Yes vs. No)	0.65 (0.21–2.01)	20.89 (2.16–202.13)	4.45 (1.19–16.63)
Vaccinated against HPV (Yes vs. No)	0.75 (0.43–1.29)	0.92 (0.46–1.82)	0.61 (0.34–1.08)
Compulsivity score (1.5 vs. 1.1)	1.25 (0.99–1.57)	1.00 (0.75–1.35)	1.77 (1.39–2.26)
Permissiveness score (3.55 vs. 2.35)	0.73 (0.47–1.15)	0.36 (0.19–0.67)	0.85 (0.51–1.40)
Birth control score (2 vs. 1)	1.00 (0.71–1.40)	0.79 (0.50–1.25)	0.88 (0.60–1.29)
Communion score (3 vs. 2)	0.96 (0.68–1.35)	0.71 (0.46–1.11)	1.58 (1.10–2.27)
Instrumentality score (3.6 vs. 2.6)	0.72 (0.50–1.05)	1.20 (0.75–1.93)	0.72 (0.48–1.09)
Need for sex score (3.63 vs. 2.25)	0.51 (0.33–0.79)	0.96 (0.58–1.60)	0.65 (0.41–1.02)
Need for affiliation score (5.22 vs. 4.11)	1.11 (0.75–1.64)	0.91 (0.56–1.46)	0.99 (0.66–1.50)

Bold indicates odds ratios and confidence intervals that are statistically significant. For interval data, the third quartile was compared to the first quartile (reference in brackets). The three multivariate logistic models have good discriminant capacity, adequate goodness of fit, and low multicollinearity: condom use (C = 0.717, Cessie–van Houwelingen p = 0.92, VIF [1.10; 2.78]); number of sexual partners (C = 0.883, Cessie–van Houwelingen p = 0.27, VIF [1.05; 3.21]); and nonconsensual sex (C = 0.802, Cessie–van Houwelingen p = 0.21, VIF [1.11; 2.29]).

Not included because of small sample size within categories.

Condom use

Females had 2.43 times higher odds of reporting using condoms (during last intercourse) compared to males. Reporting higher need for sex (OR = 0.51) and being in a serious relationship (OR = 0.41) were associated with lower odds of using condoms during the last sexual intercourse (Table 3).

Number of sexual partners

Reporting five or more previous sexual partners were associated with reporting a history of a STI (OR = 20.89), casually dating (OR = 4.12), being a Tinder user (OR = 2.81), and older age (OR = 2.52) (Table 3). Lower odds of reporting five or more previous sexual partners were associated with older age at first sexual intercourse (OR = 0.44), lower sexual permissiveness (OR = 0.36), and not living alone (OR = 0.24 for those living with peers or partners and OR = 0.14 for those living with parents or relatives) (Table 3).

Nonconsensual sex

Higher odds of reporting nonconsensual sex were associated with a history of a STI (OR = 4.45), Tinder use (OR = 3.22), sexual orientation (OR = 2.80), being female (OR = 2.53), increased sexual compulsiveness (OR = 1.77), and decreased communion (OR = 1.58). Lower odds of reporting nonconsensual sex were associated with increased age at first sexual intercourse (OR = 0.81), living with parents or relatives (OR = 0.23), and higher importance of religion (OR = 0.45) (Table 3).

Discussion

This study explored the sociodemographic characteristics and psychosocial factors associated with Tinder use and three sexual behaviors in young adults. Often, sexual behaviors are evaluated in separate samples using different correlates. A strength of this study was the ability to compare correlates across sexual behaviors using the identical independent variables and sample. Similar to previous research related to online partner seeking, we found that a large proportion (40%) of young adults aged 18–26 reported using the Tinder application.¹³ Although some studies have found gender differences whereby men are more likely to look for sexual partners online,^7,35 our study, similar to previous research,¹⁵ did not find gender differences.

As expected, being less sexually permissive (e.g., disagreement with casual sex or having sex with multiple partners) was associated with a lower likelihood of using Tinder and lower likelihood of having five or more previous sexual partners. These results are aligned with other research findings that more restrictive attitudes about sex and sexuality, greater religiosity, and less openness to experience are associated with less online sexual activity.^15,36,37 This study found that reporting a higher need for sex (e.g., increased need of having sex every day) was associated with a greater likelihood of using Tinder. Interestingly, while using Tinder was associated with the reported need for sex, it was not associated with the reported need for affiliation (increased need of a loving partner). In contrast, previous research suggests that Tinder users (aged 18–30) did not rate either “casual sex” or “intimacy” as important motivators for using the app.¹⁰ These differences may be due to the use of validated scales in this study, as opposed to single questions. Future research would be useful to clarify the different motivators for using Tinder (i.e., for sex-seeking purposes or finding a long-term relationship).

College students are engaging in risky behaviors that can have a detrimental impact on their health such as an increased chance of getting a STI, having nonconsensual sex, anxiety, and depression.²⁰ Similar to previous research, we found that being in a serious relationship was associated with a lower likelihood of using condoms.³⁸ Our results show that being in a serious relationship was also associated with a lower likelihood of using Tinder; this is in line with Cabecinha et al. who found that females with no stable partner were more likely to use the Internet to find sexual partners.⁷ This study found that a history of having a STI was strongly associated with number of previous sexual partners and nonconsensual sex. It is possible that individuals who are not using Tinder and report only one sexual partner perceive themselves at a lower risk of contracting a STI compared to individuals who seek partners on the Internet and have multiple partners.³⁹ In our opinion, young adults in a relationship who may perceive themselves at lower risk are still vulnerable for contracting a STI and should be included in health promotion interventions.

In line with evidence from previous research related to finding sexual partners online,^7,18,22,23 this study found that using Tinder is positively related to reporting more sexual partners and nonconsensual sex. This study also found higher likelihood of reporting nonconsensual sex in females and sexual minority groups. These results are not surprising as women are thrice more likely to be sexually assaulted on campus.⁴⁰ While evidence exists that higher sexual compulsivity is associated with an increased number of sexual partners in both genders,^41,42 this study's results do not reinforce this association. Interestingly, reporting nonconsensual sex was associated with agreement with beliefs regarding sexual compulsivity (i.e., beliefs that sexual thoughts and behaviors are causing problems in one's life) and disagreement with beliefs regarding sexual communion (i.e., belief that sex is an intense overwhelming experience).

Limitations

There were several limitations to this study. The sample consisted of young adults who were primarily female and White, which restrict the generalizability of these findings. Similarly, as this study examined users of the Tinder application, the results may not generalize to other online dating applications, particularly those that invest time and money to create an online profile (e.g., Match.com). Users on such sites may systematically differ to Tinder users (e.g., be seeking more serious relationships).⁴³

Participants in this study were asked to self-report their sexual preferences and behaviors. These accounts may be subject to unreliability and distortion. According to Coxon (1999), retrospective bias is probably the greatest threat to accuracy in sexual behavior data, and participants' self-reported sexual tendencies must therefore be interpreted with caution.⁴⁴ Furthermore, as there is little previous research in this field, our research was exploratory and included a large number of variables to assess the correlates of Tinder use and risky behaviors. Finally, as this study was cross-sectional in design, a causal relationship could not be determined.

Future research directions

As our sample was predominantly female, future research should focus on replicating this research in males and examining gender differences in Tinder use and risky sexual behaviors. It would also be beneficial for future research to discern the nature and direction of the relationship between using Tinder and high-risk sexual behaviors, potentially in a longitudinal design. Current findings are consistent with the view that Tinder use directly leads to sexually risky situations, but they are also consistent with the view that Tinder use is a marker for “the type of person” who is inclined to engage in risky behaviors. Of course, both may be true. A comparison between Tinder- initiated sexual contacts and non-Tinder initiated sexual contacts within individuals would be useful in teasing out whether Tinder-initiated sexual contact is due to the type of person who seeks sex on Tinder or to the nature of sexual contact that is encouraged on the Tinder application. Moreover, it would be advantageous to explore whether increased frequency of Tinder use is more greatly associated with risky sexual behaviors. In the future, it would also be helpful to compare using Tinder to using other GSN applications.

As Tinder use was associated with a greater risk of nonconsensual sex and multiple sexual partners, public health interventions may seek to protect users by constructing interventions that address nonconsensual sex and the potential STI risk of having multiple sexual partners among Tinder users. As recommended by Holloway et al., the development of app-based programs may be appropriate in reaching college students.³ Another solution to reduce unnecessary risks and sexual violence related to using Tinder (or other GSN applications) would be to provide a consent form as part of the subscription process. Some interventions, such as Britain's “ask Angela” initiative, which encouraged individuals who feel threatened or uneasy on a date to “ask for Angela at the bar”, have been developed (and adapted in other countries) to reduce sexual assault while meeting matches from online dating applications in person.⁴⁵ As such, if a Tinder date or meet-up feels unsafe this code phrase signals that an individual needs help getting to safety to a bartender, waiter, or someone nearby. It would be helpful to evaluate the effectiveness of these different methods in reducing sexual violence.

Conclusions

In a heterogeneous sample of young adults, this study identified the sociodemographic and psychosocial correlates of using Tinder. In multivariate analyses, participants who used Tinder were more likely to have engaged in nonconsensual sexual contact and had multiple sexual partners. However, in multivariate analyses, there was no significant difference in Tinder users versus nonusers in terms of condom protection. These findings may help to effectively target interventions in reducing high-risk behaviors in the young adult population.

Note

a. Only one individual was found to be an extreme outlier in regards to number of sexual partners. This participant reported 150 lifetime partners. This participant was male, 22 years of age, White, gay, educated at the university level, living alone, single, protestant, and had a GPA of 3.71 . The range of sexual partners for the rest of the sample was 0–50.

Footnotes

Acknowledgments

Gilla Shapiro acknowledges support she receives as a CIHR Vanier Canada Graduate Scholar and Queen Elizabeth II Diamond Jubilee Scholar. Samara Perez acknowledges support as a CIHR Vanier Canada Graduate Scholar. This study was supported by the Canadian Institutes of Health Research (Grant #288295).

Author Disclosure Statement

No competing financial interests exist.

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