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Record W2022175107 · doi:10.1177/1367493506067868

‘It's okay, it helps me to breathe’: the experience of home ventilation from a child's perspective

2006· article· en· W2022175107 on OpenAlexafffund
Rebecca Earle, Janet E. Rennick, Franco A. Carnevale, G. M. Davis

Bibliographic record

VenueJournal of Child Health Care · 2006
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal Children's HospitalIzaak Walton Killam Health Centre
FundersHospital for Sick ChildrenCanadian Nurses Foundation
KeywordsPerspective (graphical)MedicalizationTheme (computing)MedicineDevelopmental psychologyFocus groupPsychologyNursingPsychiatrySociology

Abstract

fetched live from OpenAlex

There are few studies that focus on children's subjective responses to home ventilation and how this in turn affects their daily lives. This multiple case study explored the experience of home ventilation from the children's perspective. Data were collected from five children through observation and audiotaped interviews. Children expressed their physical and emotional relationship with the ventilator, stating: 'It's okay. It helps me to breathe' - a theme that had a number of distinct dimensions. Other themes included the medicalization of childhood, being a child and hopes for the future. Unlike other study findings to date, the children in this study concluded that the technology was only one small part of their lives. Nurses must ensure that these children have an opportunity to communicate their perspectives, in order to provide care that is clinically effective and child-centered.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0030.002
Open science0.0010.002
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 head0.032
GPT teacher head0.383
Teacher spread0.351 · 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

Citations47
Published2006
Admission routes2
Has abstractyes

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