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Record W2189374973

The self-management experience of people with mild to moderate chronic kidney disease.

2008· article· en· W2189374973 on OpenAlexaff
Lucia Costantini, Heather Beanlands, Elizabeth McCay, Daniel C. Cattran, Michelle Hladunewich, Daphene Francis

Bibliographic record

VenuePubMed · 2008
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsKidney diseaseDiseaseMedicineNephrologyExploratory researchSelf-managementQualitative researchDisease managementHealth careFamily medicineInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

This qualitative, exploratory study examined the self-management experiences of people with mild to moderate chronic kidney disease (CKD, Stages 1-3) to elicit participants' perceptions of health, kidney disease, and supports needed for self-management. Findings revealed a process of renegotiating life with chronic kidney disease, which encompassed Discovering Kidney Disease and Learning To Live With Kidney Disease. A number of themes were identified including searching for evidence, realizing kidney disease is forever, managing the illness, taking care of the self and the need for disease-specific information. The findings indicate participants with early CKD want to self-manage their illness in collaboration with health care providers. As well, people with early CKD need guidance and support from health professionals to successfully self-manage. Nephrology nurses are uniquely positioned to provide this support while collaborating with other care providers to facilitate self-management.

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)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0010.002
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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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 designQualitative
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

Citations99
Published2008
Admission routes1
Has abstractyes

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