Depathologizing Queer Adults’ Dating App Use in Canada: Convergent Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Dating apps are virtual sociosexual networking platforms that facilitate varying social and sexual relationships and have considerably changed the way that many queer individuals form social, sexual, and romantic connections. Despite evidence that social media use can be associated with either diminished or improved mental health, few studies have explored the association between dating apps and mental health among queer adults. OBJECTIVE: Using reparative theory and a transformative paradigm, this research sought to critically explore the association between dating apps and mental health among queer adults in Canada.. METHODS: We used a convergent mixed methods design comprising an online survey (N=250) and one-on-one interviews (subsample of n=22) among queer adults from across Canada. Participants were recruited using Grindr advertisements and selected for diverse identities. The survey and interview collected information on dating app use and mental health. A structural equation model assessed the association between dating app use and mental health symptoms and the mediating role of discrimination and community connectedness. Hybrid reflexive thematic analysis of interviews elucidated how power and marginalization are negotiated, resisted, and refused in everyday app use. RESULTS: Participants used an average of 3.22 (SD 1.78) dating apps, most commonly for casual sex (208/249, 83.5%). Dating app use was associated with increased life satisfaction (β=0.31, 95% CI 0.32-1.12; P<.001) and self-esteem (β=0.21, 95% CI 0.04-0.38; P=.02) but not with depression (β=-0.16, 95% CI -0.33 to 0.02; P=.07) or anxiety (β=-0.11, 95% CI -0.45 to 0.10; P=.20). Discrimination and seeking social approval were associated with adverse mental health. Although seeking friendship was the least commonly reported motivation (98/249, 39.4%), interviewees described making friends unintentionally through intimate experiences. Increased community connection was associated with heightened life satisfaction (β=0.18, 95% CI 0.14-0.82; P=.01) and self-esteem (β=0.13, 95% CI 0.004-0.28; P=.04). Interviewees described managing negative impacts of use by adjusting expectations, using technological features to avoid unwanted interactions, and welcoming unexpected interactions in addition to their desired connections from use. Participant accounts of the inconsistent and evolving ways to use dating apps revealed the complex relationship between app use and well-being. CONCLUSIONS: Queer peoples use dating apps conscientiously, leveraging hope and serendipity to stumble upon novel and welcomed connections. Queer peoples use strategies to promote their well-being while navigating this threatening internet-based sociosexual space. The mixed methods approach provides nuance to the relationship between dating app use and well-being, underscoring the context-dependent and temporally dynamic association between them.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".