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Sexuality and Quality of Life

2007· article· en· W164843993 on OpenAlexaffabout
Janice Robinson, Anita Molzahn

Bibliographic record

VenueJournal of Gerontological Nursing · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsUniversity of VictoriaBroadcom (Canada)
Fundersnot available
KeywordsMarital statusHuman sexualityGerontologyQuality of life (healthcare)PsychologyPromotion (chess)Cross-sectional studyReproductive healthGerontological nursingMedicineNursingPopulationEnvironmental healthGender studies

Abstract

fetched live from OpenAlex

The purpose of this research was to explore the relationships between sexual activity and intimacy and quality of life (QOL) of older adults. The authors' research question was "To what extent do age, gender, marital status, health status, education, satisfaction with personal relationships, sexual activity, and satisfaction with intimacy explain older adults' ratings of QOL?" A secondary analysis was conducted using results from a cross-sectional survey. Data were available from a convenience sample of 426 individuals living in British Columbia, Canada, who volunteered to complete the questionnaire. Instruments included the WHOQOL-100, WHOQOL-OLD, and a demographic data sheet. It was found that the strongest contributors to the variance of overall QOL were satisfaction with personal relationships, followed by health status andsexual activity. Age, gender, marital status, and education were not significant. The implications for gerontological nurses include the need to support personal relationships for older adults, to encourage health promotion, and to ensure sexuality is discussed with older adults.

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)0.006
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.284
GPT teacher head0.577
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

Citations132
Published2007
Admission routes2
Has abstractyes

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