Exploring the Links between Motivations to Engage in Sexualized Drug Use and Sexo-Relational Correlates: A Cross-Sectional Study
Bibliographic record
Abstract
Sexualized drug use (SDU) has been associated with various motivations (e.g. coping with emotional distress, enhancing sexual functioning) and factors related to sexo-relational well-being (e.g., sexual satisfaction, performance anxiety). However, there is a lack of comprehensive models exploring associations between motivations for SDU and sexo-relational correlates. This study examined motivations related to SDU and their associations with sexo-relational correlates (e.g., sexual satisfaction, compulsivity). A community sample of 1,196 adults from Quebec completed an online survey on sexual health, including a questionnaire on SDU and related motivations and validated questionnaires on sexual satisfaction, sexual performance anxiety, body shame, discomfort with sexual communication, sexual compulsivity, and a history of childhood sexual abuse (CSA). Exploratory factor analyses (EFA) were performed on the SDU motivations questionnaire, followed by path analysis to test for sexo-relational correlates motivation domains. The EFA revealed four SDU motivations: increasing satisfaction and sensations (Factor 1), increasing sexual self-esteem (Factor 2), mitigating distress (Factor 3), and increasing sexual responsiveness and functioning (Factor 4). Higher performance anxiety and sexual compulsivity were associated with higher scores on all four motivation factors. Greater body shame was positively linked to Factors 2 and 3 and negatively to Factor 4. Sexual satisfaction, discomfort with sexual communication, and CSA were, respectively, uniquely associated with Factors 1, 3, and 4. The results provide insight into the heterogeneity of motivations for SDU and into the relationship between these motivations and sexo-relational well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".