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Record W2138240416 · doi:10.1177/1049732310382789

The Lived Experiences of Children and Adolescents With End-Stage Renal Disease

2010· article· en· W2138240416 on OpenAlexaff
David Nicholas, Gail Picone, Enid K. Selkirk

Bibliographic record

VenueQualitative Health Research · 2010
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsHospital for Sick ChildrenUniversity of Calgary
Fundersnot available
KeywordsLived experienceEnd stage renal diseaseStage (stratigraphy)PsychologyDevelopmental psychologyDiseaseMedicinePediatricsPsychotherapistInternal medicine

Abstract

fetched live from OpenAlex

Relatively little is known about how children perceive and manage end-stage renal disease (ESRD) in daily life. To address this gap in the literature, the experiences and perceptions of children with ESRD were examined in this study. Study design comprised ethnographic interviews with 25 children and adolescents ages 7 to 18 years. Semistructured interviews were audiotaped, transcribed verbatim, and subjected to content analysis. Participants received a range of ESRD treatments including transplantation and dialysis. Findings indicate that ESRD has a profound impact on children. They described a range of challenges and experiences including not feeling "normal"; developing ESRD knowledge; frequent absence from school; gaining responsibility for ESRD care; relying on family, friends, and health care providers; and adjusting despite adversity. These findings depict a multifaceted, dynamic perspective engendered in tensions as children and adolescents grapple with adversity yet experience personal growth and resiliency. Implications and recommendations for clinical practice and research are discussed.

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)0.012
metaresearch head score (Gemma)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.307
GPT teacher head0.603
Teacher spread0.296 · 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 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

Citations77
Published2010
Admission routes1
Has abstractyes

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