Sex Toy Use in Québec (Canada): Prevalence Across Demographics, Motivations, and Links with Erotophobia and Sexual Satisfaction
Bibliographic record
Abstract
Sex toys are widely used in both solitary and partnered sexual activities, yet the sociodemographic characteristics and sexual wellbeing of users remain under-researched. This study examined solo and partnered sex toy users’ sociodemographic characteristics and levels of erotophobia and sexual satisfaction in a Canadian community sample (n = 1,959). Participants completed an online survey, including a sociodemographic questionnaire, an inventory of sex toy usage, and validated measures of erotophobia and sexual satisfaction. Comparative analyses (i.e., t-tests, chi-squared) examined the differences in characteristics between individuals who use sex toys and those who do not, while binomial logistic regressions tested the main factors associated with solitary and partnered sex toy usage. Women, younger adults, self-identified virgins, homosexual or bi/pansexual individuals, and those with a history of childhood sexual victimization were more likely to report sex toy use. Sex toy users reported higher sexual satisfaction and lower erotophobia in both solo and partnered contexts than those who had not used sex toys. These findings offer important insights into the characteristics of sex toy users and suggest that further research is needed to understand how individual and sociocultural factors contribute to the relationship between sex toy usage and sexual wellbeing.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".