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Record W4200516231 · doi:10.1080/0092623x.2021.2011808

Insecure Attachment and Sexual Satisfaction: A Path Analysis Model Integrating Sexual Mindfulness, Sexual Anxiety, and Sexual Self-Esteem

2021· article· en· W4200516231 on OpenAlexaff

Bibliographic record

VenueJournal of Sex & Marital Therapy · 2021
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPath analysis (statistics)Insecure attachmentAssociation (psychology)Sexual behaviorAttachment theoryRelevance (law)Sexual relationshipMindfulness

Abstract

fetched live from OpenAlex

This study examines the intermediary role of three variables (sexual mindfulness, sexual anxiety, and sexual self-esteem) in a path analysis model to explain the association between insecure attachment and sexual satisfaction. A community sample of 543 adults completed an online survey. Results supported our hypothesized integrative model, which explained 44.1% of the variance in sexual satisfaction and presented satisfactory fit indices. This study suggests that the association between attachment insecurities and lower sexual satisfaction could be partially explained by a proximal association with lower sexual mindfulness, which emphasizes the relevance of examining sexual mindfulness during the screening and treatment of people presenting low sexual satisfaction.Supplemental data for this article is available online at https://doi.org/10.1080/0092623X.2021.2011808 .

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)0.003
metaresearch head score (Gemma)0.006
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.294
Teacher spread0.267 · 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

Citations28
Published2021
Admission routes1
Has abstractyes

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