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Record W4401728752 · doi:10.4187/respcare.11689

Exploring the Parental Perspectives and Experiences With the Use of a Home Mechanical Insufflation-Exsufflation Device

2024· article· en· W4401728752 on OpenAlexaffabout
Carolyn Jarock, Jordan Sheriko, Karen Hurtubise

Bibliographic record

VenueRespiratory Care · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPediatric health and respiratory diseases
Canadian institutionsMcMaster University Medical CentreDalhousie UniversityNova Scotia Health AuthorityIzaak Walton Killam Health Centre
Fundersnot available
KeywordsExsufflationMedicineInsufflationContext (archaeology)Intensive care medicineNursingAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND: A mechanical insufflation-exsufflation (MI-E) device is a commonly used tool for airway clearance in children with an ineffective cough. Whereas the device has been shown to have multiple benefits, limited evidence exists regarding parents' experiences with its home use in the Canadian context. This study's objective was to explore the perspectives and experiences of parents who receive service through the IWK Health Centre and use an MI-E device at home with their child. METHODS: The study used an interpretive description design. Semi-structured interviews, conducted with 9 participants, were audio recorded and transcribed verbatim. Transcripts were analyzed using a reflective thematic process. RESULTS: outlined the physical, emotional, and social benefits the device provided to the child and their family. CONCLUSIONS: Participants provided detailed descriptions of their journey from learning to integrating the MI-E device into their child's daily routine and family life. Its multiple associated benefits improved the child's and their family's quality of life. However, better education on its use was highlighted as a need for both parents and the health care professionals who work with them.

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)0.012
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 score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.209
GPT teacher head0.397
Teacher spread0.188 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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