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Record W1902575929 · doi:10.1111/ajag.12181

Assessment of sexual health and sexual needs in residential aged care

2014· article· en· W1902575929 on OpenAlexaboutno aff
Linda McAuliffe, Michael Bauer, Deirdre Fetherstonhaugh, Carol Chenco

Bibliographic record

VenueAustralasian Journal on Ageing · 2014
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsnot available
FundersLa Trobe University
KeywordsQuarter (Canadian coin)Reproductive healthNeeds assessmentResidential careHealth careMedicineAged careEnvironmental healthCensusGerontologyPsychologyGeographyPopulation

Abstract

fetched live from OpenAlex

AIM: To investigate if, when and how assessments regarding residents' sexual health and needs occur within Australian residential aged care facilities. METHOD: A census of all Australian residential aged care facilities was conducted. A survey developed specifically for the project was posted to all 2766 residential aged care services in Australia. Eight weeks were allowed for the return of surveys. RESULTS: A total of 1094 completed surveys were returned, representing a 39.7% response rate. The type of information most often collected concerned disruptive sexual behaviour, and assessments most frequently occurred following disruptive behaviour. One-quarter of facilities reported having a sexual health/needs assessment form, although only 10 facilities provided evidence of this. CONCLUSION: Survey responses indicated that sexual health and needs are not routinely assessed in residential aged care, and facilities do not commonly have a dedicated sexual health/needs assessment form to guide them through an assessment process.

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)0.002
metaresearch head score (Gemma)0.010
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.339
Teacher spread0.304 · 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

Citations21
Published2014
Admission routes1
Has abstractyes

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