The use of the smartphone dating application Tinder is increasingly popular and has received much media attention. However, no empirical study to date has investigated the psychological characteristics driving its adaptive or problematic use. The aim of this study is to determine whether reliable subtypes of users can be identified via a cluster analysis approach.
A total of 1,159 Tinder users were recruited. Survey questions investigated user characteristics, including: motives for app use, sexual desire, attachment styles, impulsivity traits, self-esteem, problematic use, depressive mood, and patterns of use.
Four reliable clusters were identified: two with low levels of problematic use (“regulated” and “regulated with low sexual desire”), one with an intermediate level of problematic use (“unregulated-avoidants”), and one with a high level of problematic use (“unregulated-highly motivated”). The clusters differed on gender, marital status, depressive mood, and use patterns.
The findings provide insight into the dynamic relationships among key use-related factors and shed light on the mechanisms underlying the self-regulation difficulties that appear to characterize problematic Tinder use.
Behavioral addiction research has been particularly flourishing over the last two decades. However, recent publications have suggested that nearly all daily life activities might lead to a genuine addiction.
Methods and aim
In this article, we discuss how the use of atheoretical and confirmatory research approaches may result in the identification of an unlimited list of “new” behavioral addictions.
Both methodological and theoretical shortcomings of these studies were discussed.
We suggested that studies overpathologizing daily life activities are likely to prompt a dismissive appraisal of behavioral addiction research. Consequently, we proposed several roadmaps for future research in the field, centrally highlighting the need for longer tenable behavioral addiction research that shifts from a mere criteria-based approach toward an approach focusing on the psychological processes involved.
Behavioral addictions (BAs) and substance use disorders (SUDs) tend to co-occur; both are associated with mental health problems (MHPs). This study aimed to estimate the proportion of variance in the severity of MHPs explained by BAs and SUDs, individually and shared between addictions.
A sample of 5,516 young Swiss men (mean = 25.47 years old; SD = 1.26) completed a self-reporting questionnaire assessing alcohol, cannabis, and tobacco use disorders, illicit drug use other than cannabis, six BAs (Internet, gaming, smartphone, Internet sex, gambling, and work) and four MHPs (major depression, attention-deficit hyperactivity disorder, social anxiety disorder, and borderline personality disorder). Commonality analysis was used to decompose the variance in the severity of MHPs explained (R2) by BAs and SUDs into independent commonality coefficients. These were calculated for unique BA and SUD contributions and for all types of shared contributions.
BAs and SUDs explained between a fifth and a quarter of the variance in severity of MHPs, but individual addictions explained only about half of this explained variance uniquely; the other half was shared between addictions. A greater proportion of variance was explained uniquely or shared within BAs compared to SUDs, especially for social anxiety disorder.
The interactions of a broad range of addictions should be considered when investigating their associations with MHPs. BAs explain a larger part of the variance in MHPs than do SUDs and therefore play an important role in their interaction with MHPs.
The Internet is widely used for sexual activities and pornography. Little is known, however, about why people look for meetings and sexual interactions through the Internet and about the correlates of cybersex addiction. The goal of this study was to construct a questionnaire for cybersex motives [Cybersex Motives Questionnaire (CysexMQ)] by adapting the Gambling Motives Questionnaire to cybersex use and validating its structure.
Two online samples of 191 and 204 cybersex users were collected to conduct a principal component analysis (PCA) on the first sample and a confirmatory factor analysis (CFA) on the second. Cronbach’s α and composite reliability were computed to assess internal consistency. Correlations between the CysexMQ and the Sexual Desire Inventory (SDI) were also evaluated.
Two competing models were retained from the PCA, one with two factors and the other with three factors. The CFA showed better fit for the three-factor solution. After three cross-loading items were removed, the results showed that a final 14-item three-factor solution (enhancement, coping, and social motives) was valid (adjusted goodness-of-fit index: 0.993; normed-fit index: 0.978; Tucker–Lewis index: 0.985; comparative fit index: 0.988; root mean square error of approximation: 0.076). Positive correlations were found between the different motives and the subscales of the SDI.
The results suggest that the CysexMQ is adequate for the assessment of cybersex motives.
Cybersex is increasingly associated with concerns about compulsive use. The aim of this study was to assess the roles of motives and sexual desire in the compulsive use of cybersex.
The sample consisted of 306 cybersex users (150 men and 156 women). The participants were assessed using the Compulsive Internet Use Scale (CIUS) adapted for cybersex, the Cybersex Motives Questionnaire (enhancement, coping, and social motives), and the Sexual Desire Inventory-2 (dyadic and solitary sexual desire).
For both genders, coping motive was associated with CIUS score. For women, an additional association with social motives was found whereas an association with sexual desire was found for men.
The study showed gender differences in the contributors to sex-related CIUS scores.
Controversies remain about the validity of the diagnosis of problematic Internet use. This might be due in part to the lack of longitudinal naturalistic studies that have followed a cohort of patients who self-identify as having Internet-related problems.
This retrospective study included 57 patients who consulted the Geneva Addiction Outpatient Clinic from January 1, 2007, to January 1, 2010. Patients underwent an initial clinical psychiatric evaluation that included collection of data on socio-demographics, method of referral, specific Internet usage, psychiatric diagnosis, and Internet Addiction Test (IAT) and Clinical Global Impression Scale (CGI) scores. Treatment consisted of individual psychotherapeutic sessions.
Of these patients, 98% were male and 37% were 18 years or younger. Most patients were online gamers (46% playing massively multiplayer online role-playing games). The mean IAT score was 52.9 (range 20–90). Sixty-eight percent of patients had a co-morbid psychiatric diagnosis, with social phobia being the most prevalent (17.8%). Patients who remained in treatment (dropout rate 24%) showed an overall improvement of symptoms: 38.6% showed significant or average improvement on their CGI score, 26.3% showed minimal improvement, and 14% showed no change.
Our results support the hypothesis that there are specific types of Internet use, with online gaming mainly affecting young male patients. As Internet addiction is not yet an official diagnosis, better instruments are needed to screen patients and to avoid false-negative and false-positive diagnoses. Successful care should integrate the treatment of co-morbid symptoms and involve families and relatives in the therapeutic process.