Body image self-consciousness, sexting, and sexual satisfaction among midlife Canadians
Bibliographic record
Abstract
Life circumstances at midlife are often different than those for younger adults (e.g., relationship type and duration, physical health, experience of sexual problems), and these circumstances impact experiences of sexuality and sexual behaviour. Past research on sexual behaviours like sexting, which has been primarily conducted on young people, may not generalize to middle-aged adults. Sexting may be a beneficial activity for midlife adults in long-term relationships who are seeking private and convenient ways to communicate sexual interest. Furthermore, as in younger samples, sexting may be associated with body image and sexual satisfaction. A cross-sectional study with a sample of 640 midlife (40–59 years old) married Canadians was conducted to address these suppositions. Structural equation modelling was used to test the factorial validity of a body image self-consciousness (BISC) scale and to investigate the connections between BISC, sexting frequency (to communicate sexual interest, to initiate sexual activity, and that include a picture), and sexual satisfaction. Almost one-half of participants (43%) reported sexting to communicate sexual interest, 37% sexted to initiate sexual activity, and 18% sexted sexy pictures of themselves. Women with lower levels of BISC were more likely to sext (communicate, initiate, and pictures), and men with lower levels of BISC were more likely to send sexts with pictures. Both men and women with lower levels of BISC and those who engaged in sexting to communicate sexual interest had higher levels of sexual satisfaction. Sexting may be an opportunity for busy marital partners to engage in technology-mediated sexual activity when apart. The current results indicate that technology-mediated sexual communication has similar psychological mechanisms to face-to-face interactions and that sexting may be a beneficial behaviour for sexual satisfaction within midlife marriages.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".