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Record W1998550046 · doi:10.1080/00224499.2013.838744

Attachment Insecurities and Women's Sexual Function and Satisfaction: The Mediating Roles of Sexual Self-Esteem, Sexual Anxiety, and Sexual Assertiveness

2013· article· en· W1998550046 on OpenAlexaff
Audrey Brassard, Emmanuelle Dupuy, Sophie Bergeron, Phillip R. Shaver

Bibliographic record

VenueThe Journal of Sex Research · 2013
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversité de MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsAssertivenessPsychologyAnxietyClinical psychologySexual functionDevelopmental psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

We examined the potential role of three mediators--sexual self-esteem, sexual anxiety, and sexual assertiveness--of the association between romantic attachment insecurities (anxiety and avoidance) and two aspects of women's sexual functioning: sexual function and sexual satisfaction. A sample of 556 women aged 18 to 30 agreed to complete an online series of validated questionnaires assessing attachment insecurities and several aspects of sexual functioning. Lower sexual self-esteem and higher sexual anxiety mediated the associations between attachment anxiety and lower sexual function and satisfaction. Lower sexual self-esteem and higher sexual anxiety also partially mediated the links between attachment-related avoidance and the two sexual functioning variables. Sexual assertiveness, however, did not mediate these associations. A significant interaction between attachment anxiety and avoidance was also found to predict sexual satisfaction, with women high in avoidance and low in anxiety being the least satisfied. Results are discussed in terms of theoretical and clinical implications.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.052
GPT teacher head0.345
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations170
Published2013
Admission routes1
Has abstractyes

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