Positive and Negative Sexual Cognitions of Autistic Individuals
Bibliographic record
Abstract
Abstract Sexual cognitions are an important aspect of sexual well-being for all individuals; however, little is known about the sexual cognitions of autistic individuals. Therefore, our study aimed to explore the diversity, content, and frequencies of positive (PSC) and negative (NSC) sexual cognitions in this population. A total of 332 participants (57.5% women; 42.5% men) between the ages of 21 and 73 (M = 37.72, SD = 11.15) completed an online survey. Our results showed that almost all participants had experienced both positive and negative sexual cognitions. PSC were more diverse and experienced with greater frequency than NSC. In addition, gender (self-identified as being male) and having had relationship experience were associated with greater diversity and frequency of PSC, but not NSC. In terms of content, the most common experienced sexual cognitions for both men and women were intimacy-related. The men experienced 22 of the 56 PSC and 3 of the 56 NSC significantly more frequently than did the women; there were no cognitions that the women experienced more frequently than the men. A comparison to the results of studies of sexual cognitions among neurotypical individuals suggests that autistic individuals experience sexual cognitions in much the same way as their peers. However, sexual cognitions occur slightly less frequently and are somewhat less diverse. Nonetheless, the way in which they are experienced, and the content of the most frequent cognitions (mainly PSC about intimacy) may be indicative of sexual well-being.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".