Looking Beyond the Chair: Psycho-Perceptual Predictors of Sexual Distress and Sexual Satisfaction in Individuals with Spinal Cord Injury
Bibliographic record
Abstract
Despite a large body of biomedical research, little is known about the psychological and perceptual predictors of sexual satisfaction (SS) and sexual distress (SD) post spinal cord injury (SCI). Guided by a bio-psycho-perceptual framework, this cross-sectional research aimed at assessing SS and SD in a large SCI sample using validated patient-reported outcome measures (PROM). Significant correlates and predictors of SS and SD were also identified. Ninety-one men and women with SCI completed PROMs of SS and SD, as well as psychological (mood, sexual and body esteem) and perceptual (interoceptive awareness, trait mindfulness, sexual mindfulness) factors. Neurological profiles were also assessed, along with experience of orgasm. Correlates of SS and SD were first identified using Pearson’s correlations, then multiple hierarchical regression models were computed to isolate predictors. Orgasm experience and psychological factors emerged as moderate correlates of both SS and SD, while neurological factors did not. Interoceptive awareness and trait mindfulness showed weak associations with SD and none with SS. Among the tested predictors, experience of orgasm emerged as the strongest for SS (β = -.29, p < .01), followed by mood, which predicted SS and SD. Sexual and body esteem was predictive of SD only. In sexually active participants, sexual mindfulness predicted both SS (β = 0.55, p < .001) and SD (β = -0.56, p < .001) above and beyond all other variables. This study reveals unique aspects of SS and SD postinjury and supports further consideration of psychological and perceptual dimensions of SCI sexuality in rehabilitation research.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".