Swiping with Social Anxiety: Using Dating Apps to Circumvent Barriers to Intimate Relationship Formation
Bibliographic record
Abstract
The present dissertation aims to improve our understanding of the ways in which social anxiety symptoms are associated with location-based dating app (e.g., TinderTM) use. In Study 1 (Chapter 2), participants (N = 159) completed a laboratory task to examine whether social anxiety symptoms were associated with decreased dating profile satisfaction and confidence, and in turn, increased profile rejection over time. Social anxiety symptoms were associated with reduced confidence during the task. Participants became more rejecting of profiles over time; however, this tendency was not moderated by social anxiety symptoms. In Study 2, participants (N = 112) completed a baseline measure of social anxiety symptoms and subsequently completed daily diaries of dating app use for 7 days. In contrast to Study 1, profile swiping (i.e., number of viewed profiles and time spent swiping through profiles) was not associated with next-day profile acceptance or the extent of participants’ social engagement with dating app matches (Chapter 3). Social anxiety symptoms again predicted reduced confidence, which was in turn associated with reduced social engagement with matches. However, the direct and indirect effects of social anxiety symptoms on measures of social engagement with dating app matches either fell below the threshold of statistical significance or met the threshold of statistical significance while accounting for only a small degree of variance in the outcome (Chapter 4). In Study 3 (Chapter 5), participants (N = 128) completed an experimental laboratory paradigm to examine the interactive effect of: (a) social anxiety symptoms and (b) rejection versus acceptance feedback on participants’ negative affect, positive affect, state anger, and willingness to initiate contact with matches. Social anxiety symptoms predicted increased negative affect and reduced willingness to initiate contact with dating app matches following rejection feedback, as well as reduced positive affect following acceptance feedback. State anger was not significantly predicted by feedback type, social anxiety, or their higher order interaction. Taken together, these results suggest that social anxiety symptoms are not associated with social engagement with dating app matches. However, following instances of rejection on dating apps, individuals with elevated social anxiety symptoms may be more likely to limit social engagement. Furthermore, socially anxious individuals may experience greater negative affect and less positive affect when using dating apps.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 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".