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Record W2609785501 · doi:10.1177/2333393617705035

Examining the Roles and Experiences of Fathers of Children With Chronic Kidney Disease

2017· article· en· W2609785501 on OpenAlexafffund
David Nicholas

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2017
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of Calgary
FundersKidney Foundation of Canada
KeywordsKidney diseaseIngenuityMedicineCoping (psychology)Peritoneal dialysisPopulationDiseaseRenal replacement therapyPsychologyClinical psychologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

This study examined roles and experiences of fathers of children with chronic kidney disease (CKD). Based on interpretive description, semistructured interviews were conducted with 22 fathers of children receiving a range of treatments (transplant, peritoneal dialysis, hemodialysis, and CKD not requiring renal replacement therapy). Fathers described various experiences and means of adjusting to shifts associated with pediatric CKD. These included loss of personal control, a sense of personal isolation, and a stance of remaining strong amidst personal suffering. Nuanced differences according to modality of CKD care were identified. Fathers engaged in strategies that fostered coping, such as remaining positive and taking charge. They conveyed deep love for their child, and demonstrated ingenuity and persistence in care. Few resources of support were accessed by fathers. Study recommendations invite holistic approaches to health care, with improved resources for families-including fathers-in addressing the needs of this population.

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)0.005
metaresearch head score (Gemma)0.008
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 score0.006
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.003
Scholarly communication0.0020.002
Open science0.0010.003
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 head0.273
GPT teacher head0.592
Teacher spread0.319 · 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

Citations14
Published2017
Admission routes2
Has abstractyes

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