Perceiving that one's partner is supportive moderates the associations among attachment insecurity and psychosexual variables
Bibliographic record
Abstract
Attachment representations are associated with psychosexual adjustment in intimate relationships (Mikulincer & Shaver, 2007). Few studies, however, have investigated relationship processes modulating the effect of attachment insecurity on sexuality (Dewitte, 2012). This study examined whether perceived partner support moderates associations among romantic attachment (i.e., anxiety and avoidance) and sexual self-esteem, sexual anxiety, and sexual assertiveness in individuals involved in a romantic relationship (N=214). Results showed that individuals high on avoidance reported lower sexual self-esteem and assertiveness, as well as more sexual anxiety. Unexpectedly, they reported more sexual anxiety and poorer sexual assertiveness when partner support was perceived to be high. Moreover, low perceived partner support was related to higher sexual self-esteem in women scoring high on attachment avoidance whereas high perceived partner support was related to higher sexual self-esteem in men scoring high on avoidance. Individuals scoring high on attachment anxiety reported poorer sexual self-esteem and more sexual anxiety when partner support was perceived to be low, but attachment anxiety was unrelated to either sexual anxiety or self-esteem when partner support was perceived to be high. Findings are consistent with attachment theory and suggest clinical implications for individuals presenting with attachment insecurity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".