Participants

A total of 690 participants (532 women; age M = 20.30 years, SD = 4.51, range = 17–51) took part in the current study, of whom 310 individuals had used dating apps previously. Approximately 11% self-reported currently or previously suffering from an ED and the body mass index (BMI) ranged from 15.35 to 66.06 kg/m2 (M = 22.11, SD = 4.33). As shown in Table 1, the sample was ethnically diverse: 41.2% were White, 30.7% were Eastern Asian, 15.6% were Southern or Southeast Asian, and the remainder were Hispanic or Latino American (0.3%), Middle Eastern (2.9%), or Other (9.3%). Most of the sample was heterosexual (86.8%), 8.1% were bisexual, and the remainder were homosexual (3.3%) or reported their sexuality as other (1.3%). Three-quarters (76.3%) of the sample had completed up to a Year 12 education, 51.8% were unemployed and 95.1% had never been married. English (66.6%) was the most common language spoken.

Table 1 Sociodemographic characteristics for the total sample, and by dating app user statusProcedure

Participants aged over 18 years were recruited from several sources within the University of [redacted], social media advertisements by the authors, and research listservs. Participants completed a 30-min online survey asking about the demographics, lifetime dating app usage and the above-outlined measures. If participants answered that they engaged in dating app usage throughout their lifetime, they were also asked questions about their dating app usage frequency and motivations for using dating apps. As compensation for their time, participants from the university's research experience program (REP) were provided one unit of course credit, whilst those from the community were entered into a draw to win one of three $100 (AUD) iTunes gift cards. The study was approved by the University of [redacted for peer-review] Human Research and Ethics Committee and all participants provided electronically written informed consent to participate.

MeasuresDemographics and ED diagnoses

The baseline questionnaire obtained information concerning age, gender, ethnic background, sexual orientation, marital status, and the highest level of education completed. Current height in centimetres and weight in kilograms was also self-reported, allowing us to calculate individuals’ BMIs. Finally, participants were also asked whether they have ever experienced an ED.

Dating app variables

Dating app usage was assessed by asking whether participants had ever used a dating app (45% yes). We then evaluated users’ motivation for using dating apps by asking whether they used apps for Casual Sex, Ease of Communication, Self-Worth Validation, Thrill of Excitement, Trendiness, or Love. These categories for motivation for app use were taken from Sumter et al. [39] Participants were able to indicate all the motivations that applied to them. To measure current app use frequency, we also asked how many swipes users engaged in per week (M = 55, SD = 91.11, range = 0–1000).

Appearance-based rejection sensitivity

Appearance-based rejection sensitivity was measured via the Appearance-based Rejection Sensitivity Scale short-form scale [28]. The scale presented 10 hypothetical scenarios (e.g., “You are leaving your house to go on a first date when you notice a blemish on your face”) for which the participant indicated their anxiety (1 = very unconcerned, 6 = very concerned), and expectation of rejection (1 = very unlikely, 6 = very likely). For each scenario, anxiety scores were multiplied by rejection scores, which were then averaged across scenarios; leading to a mean score with a range of 1–36 (M = 14.72, SD = 6.78, Cronbach’s α = 0.90). Higher scores indicate higher appearance-based sensitivity to rejection.

Social rank

Social rank was measured using the 11-item Social Comparison Scale [1]. Participants made a global social comparison of themselves in relation to others with a series of bipolar constructs rated 1–10; 1—low subjective social ranking, 10—high subjective social ranking (e.g., “In relation to others I feel….”: 1 = inferior, 10 = superior). Items were summed, with high scores indicating feelings of superiority and self-perceived high rank (M = 64.28, SD = 15.05, α = 0.91).

Fear of negative evaluation

We used the 12-item Brief Fear of Negative Evaluation Scale [23] to measure fear of being negatively evaluated. Each item (e.g., “I am afraid that others will not approve of me”) was rated on a 5-point Likert scale (1 = not at all, 5 = extremely) with a range of 12–60. Items were summed, with higher scores indicating greater fear of negative evaluation (M = 39.02, SD = 9.18, α = 0.76).

Emotion dysregulation

Emotion dysregulation was measured using the 18-item Brief Version of the Difficulties in Emotion Regulation Scale [19]. Items (e.g.,”I pay attention to how I feel”) were rated on a 5-point Likert scale (1 = almost never, 5 = almost always) and summed to create a total score (range = 18–90); higher scores represented more difficulty regulating emotions (M = 50.97, SD = 12.36, α = 0.89).

Disordered eating

We evaluated DE using the 12-item Eating Disorder Examination Questionnaire Short Form [13], which assesses DE symptoms over the last 7 days. Items (e.g.,”Have you had a definite fear that you might gain weight?") were rated from zero (0 days/Not at all) to three (6–7 days/Markedly), and then summed, with higher scores indicating elevated DE psychopathology (M = 9.79, SD = 7.20, α = 0.89).

Data analysis

We were interested in the magnitude of effects of dating app variables on DE, controlling for known predictors (appearance-based rejection sensitivity, social rank, fear of negative evaluation, emotion dysregulation, ED diagnosis) of this outcome variable. Using multiple linear regression, in Model 1 we tested trait-level sociodemographic and clinical predictors (gender, BMI, ED history; Step 1), psychological predictors (appearance-based rejection sensitivity, social rank, fear of negative evaluation, emotion dysregulation; Step 2), and dating app usage (Step 3) on DE for the full sample of app-users and non-app users. We chose these trait level covariates because they have been implicated as correlates or risk factors for disordered eating (i.e., female gender, BMI, and history of an ED). In Model 2 we examined whether dating app usage moderated the effects of trait and psychological predictors on DE. In Model 3 we examined the effects of these same trait predictors (Step 1) and psychological predictors (Step 2) on DE for app-users only; in this model, we also entered the six motivators for dating app usage (Step 3). We examined collinearity using variance inflation factors: all variance inflation factors were below 2.0, indicating that problematic levels of multi-collinearity were unlikely to be present. Where variables were summed, no missing data were present among participants (i.e., all summed scores were accurate, and not biased by missing data on some items within scales). To minimise the deletion of available data, any other missing data were treated using pairwise deletion. A power analysis for linear regression with 15 predictors (Model 2) indicated that the achieved power to detect a medium effect (f = 0.39) for our recruited sample of 690 individuals was b = 0.996.