The Causal Effects of Relational Security and Insecurity on Condom Use Attitudes and Acquisition Behavior
Bibliographic record
Abstract
Research on attachment and condom use has been limited to correlational studies of self-report measures, yielding inconsistent results. Here, we examined the causal effects of attachment priming on self-reported condom use attitudes and an observational measure of condom acquisition behavior. In three experiments, participants were exposed to one of three attachment primes (security, anxiety, or avoidance) or a control prime. For Study 1, participants in the security and anxiety conditions preferred condom non-use to a greater extent, compared to participants in the avoidance condition. This effect was replicated in Study 2, and was mediated by perceptions of sexual health threat. In Study 3, the effect of security priming on condom acquisition behavior was eliminated through the use of a framing manipulation, though, the effect of primed attachment on condom use attitudes was not significant. A Meta-Analysis, however, revealed that the predicted effects of attachment priming were consistent across the three studies, supporting the role of attachment in evaluations of condom use. Priming attachment security or anxiety lead participants to perceive their sexual partners as less of a sexual health threat, resulting in a devaluation of condom use. Primed security also reduced condom acquisition behavior, though this negative effect eliminated by framing condoms as protecting a partner’s sexual health. Overall, these studies suggest that relational factors, such as attachment, require greater consideration when studying sexual health and designing interventions.
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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 | 0.012 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".