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Knowledge of urinary incontinence among Chinese community nurses and community-dwelling older people

2009· article· en· W2083185422 on OpenAlexaff
Haobin Yuan, Beverly Williams

Bibliographic record

VenueHealth & Social Care in the Community · 2009
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUrinary incontinenceMedicineGerontologyOlder peoplePsychologyNursingUrology

Abstract

fetched live from OpenAlex

The purpose of this study was to describe knowledge of urinary incontinence among community nurses and community-dwelling older people in China. The descriptive study was undertaken in 2007 using a cross-sectional research design. A random sampling method was used to recruit 100 Chinese older people and 100 Chinese nurses in JinShan and NanHui communities, Shanghai, China. All participants completed all items of a demographic survey and the Urinary Incontinence Knowledge Scale (UIKS). Based on the literature, the UIKS was developed in 2007. The value of content validity index tested by five experts was 0.75. Measures of internal consistency (Kuder-Richardson formula 20) were 0.72 for the community nurses and 0.69 for the older people. The UIKS consisted of 30 items with dichotomous choices (Correct = 1; False or Do not know = 0). The mean UIKS score of the nurses (mean 20.7, SD 3.5) was significantly higher than that of the older people (mean 13.4, SD 4.0) with a 95% confidence interval for difference in means 6.3-8.4 (t = 13.84; df = 198; P < 0.001). Although community nurses had moderate knowledge of the impact of incontinence, they still lacked knowledge of risk factors, symptoms, prevention, treatment, and management. Older people had poor knowledge about risk factors, symptoms, impact, prevention, treatment and management of urinary incontinence. Because of their knowledge deficits, community nurses and older people viewed urinary incontinence as a normal part of the ageing process. The findings suggested that both nurses and older people in the community had educational needs related to the incontinence. Further studies to develop specific educational programmes concerning urinary incontinence are suggested. Ways to enhance support and acceptable forms of specific content knowledge, process measures and regulatory enforcement require additional exploration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.366
Teacher spread0.336 · 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 teacher head, not a consensus.

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

Citations49
Published2009
Admission routes1
Has abstractyes

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