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Record W2801634700 · doi:10.1177/1352458518768722

Factors affecting continuation of clean intermittent catheterisation in people with multiple sclerosis: Results of the COSMOS mixed-methods study

2018· article· en· W2801634700 on OpenAlexaff
Doreen McClurg, Carol Bugge, Andrew Elders, Tasneem Irshad, Suzanne Hagen, Katherine Moore, Brian S Buckley, Mandy Fader

Bibliographic record

VenueMultiple Sclerosis Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsUniversity of Alberta
FundersMultiple Sclerosis Society
KeywordsDiscontinuationMedicineContinuationMultiple sclerosisCohortLongitudinal studyIncidence (geometry)PediatricsIntensive care medicineInternal medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Clean intermittent catheterisation (CIC) is often recommended for people with multiple sclerosis (MS). OBJECTIVE: To determine the variables that affect continuation or discontinuation of the use of CIC. METHODS: A three-part mixed-method study (prospective longitudinal cohort ( n = 56), longitudinal qualitative interviews ( n = 20) and retrospective survey ( n = 456)) was undertaken, which identified the variables that influenced CIC continuation/discontinuation. The potential explanatory variables investigated in each study were the individual's age, gender, social circumstances, number of urinary tract infections, bladder symptoms, presence of co-morbidity, stage of multiple sclerosis and years since diagnosis, as well as CIC teaching method and intensity. RESULTS: For some people with MS the prospect of undertaking CIC is difficult and may take a period of time to accept before beginning the process of using CIC. Ongoing support from clinicians, support at home and a perceived improvement in symptoms such as nocturia were positive predictors of continuation. In many cases, the development of a urinary tract infection during the early stages of CIC use had a significant detrimental impact on continuation. CONCLUSION: Procedures for reducing the incidence of urinary tract infection during the learning period (i.e. when being taught and becoming competent) should be considered, as well as the development of a tool to aid identification of a person's readiness to try CIC.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.045
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.073
GPT teacher head0.312
Teacher spread0.240 · 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.

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

Citations23
Published2018
Admission routes1
Has abstractyes

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