Romantic Attachment, Sex Motives and Sexual Difficulties in Emerging Adults: The Role of Childhood Interpersonal Victimization
Bibliographic record
Abstract
A growing body of research has revealed that many emerging adults (i.e., aged 18 to 25) experience sexual difficulties. Past studies have emphasized the need to examine sexual difficulties by accounting for sex motives (i.e., reasons for engaging in sex) and by using a trauma-focused or attachment-based framework. This study examined the role of sex motives in the associations among attachment insecurities (anxiety, avoidance) and sexual difficulties in emerging adults, and assessed whether these links varied on the basis of low or high exposure to childhood interpersonal victimization (CIV) (i.e., 0-3 different types of CIV or 4 or more types of CIV). A sample of 437 French-Canadian emerging adults completed validated questionnaires online. Path analyses revealed that participants with higher attachment anxiety were more likely to endorse the partner approval sex motive, which was related to more sexual difficulties. Participants with higher attachment avoidance were less likely to endorse the pleasure sex motive, which was associated with more sexual difficulties. Results indicated a significant effect of CIV showing that some indirect effects were significant only in participants who reported high CIV exposure. Results suggest that addressing sex motives using an attachment- and trauma-focused framework might help understand, prevent and treat sexual difficulties among emerging adults.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".