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Record W2791830100 · doi:10.1111/jmft.12328

Sexual Portrait of Couples Seeking Relationship Therapy

2018· article· en· W2791830100 on OpenAlexaff
Katherine Péloquin, E. Sandra Byers, Melissa Callaci, Nadine Tremblay

Bibliographic record

VenueJournal of Marital and Family Therapy · 2018
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversity of New BrunswickUniversité de Montréal
Fundersnot available
KeywordsSexual functioningPsychologySexual relationshipClinical psychologyPath analysis (statistics)Sexual behaviorDevelopmental psychologyHuman sexualitySexual dysfunctionPsychiatry

Abstract

fetched live from OpenAlex

This study sought to provide information about the sexual well-being of 298 mixed-sex couples seeking relationship therapy and determined the extent to which problems with sexual functioning and dyadic adjustment of both partners are associated with sexual satisfaction. Partners completed measures of dyadic adjustment, sexual satisfaction, and sexual functioning. Thirty percent of couples reported a clinically significant sexual problem. Compared to their male partners, the women were more likely to report a sexual problem as well as lower dyadic adjustment, sexual satisfaction, and overall sexual functioning. Path analysis indicated that relationship adjustment uniquely predicted individuals' own sexual satisfaction; problems in sexual functioning uniquely predicted own and partner sexual satisfaction. Findings underscore the need to address sexual problems in relationship therapy.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.080
GPT teacher head0.307
Teacher spread0.228 · 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

Citations31
Published2018
Admission routes1
Has abstractyes

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