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Record W3206451398 · doi:10.3390/sexes2040035

Factors Associated with Four Sexual Behaviors among Married/Partnered Women Ages 60 and Older in the United States

2021· article· en· W3206451398 on OpenAlexaff
Caroline D. Bergeron, Heather Honoré Goltz, Ali Boolani, Matthew Lee Smith

Bibliographic record

VenueSexes · 2021
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDemographySexual intercourseDemographicsPsychologySexual behaviorAnal intercourseReceiptMedicineReproductive healthGerontologyClinical psychologyPopulationMen who have sex with menFamily medicine

Abstract

fetched live from OpenAlex

Women ages 60 and older vary in sexual behaviors. This study examined the prevalence of vaginal intercourse, outercourse, and receipt and performance of oral sex reported among 461 married/partnered women age ≥ 60 years in the United States and factors associated with these four sexual behaviors. Using data from the National Social Life, Health, and Aging Project, associations between participants’ socio-demographics, health indicators, sexual perceptions, communication, and sexual behaviors were examined. In the past year, 53.6% reported having vaginal intercourse, 56.0% outercourse, and 21.7% receiving and 20.6% performing oral sex. Women with depressive symptomology were less likely to report intercourse and outercourse (p < 0.05). Women endorsing pleasurable sex as necessary to maintain relationships were more likely to report all four behaviors (p < 0.01). Women who communicated openly with partners were more likely to report intercourse (p = 0.002), outercourse (p = 0.001), and performing oral sex (p = 0.025). Findings may inform strategies about positive sex perceptions and strengthening partner communication.

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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.295
Teacher spread0.231 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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