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Record W4391716553 · doi:10.1177/10497323241226678

Family Member Experiences in Intensive Care Units Care: Insights From a Family Involvement Tool Implementation Trial

2024· article· en· W4391716553 on OpenAlexafffund
Janet Alexanian, Ian Fraser, Orla Smith, Simon Kitto

Bibliographic record

VenueQualitative Health Research · 2024
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsSt. Michael's HospitalToronto East General HospitalUniversity of Ottawa
FundersInstitute of Health Services and Policy Research
KeywordsContext (archaeology)Intensive care unitIntensive careNursingPsychological interventionHealth careEthnographyGovernment (linguistics)Participant observationMeaning (existential)MedicineQualitative researchFamily memberPsychologyFamily medicineSociologyPsychotherapistIntensive care medicinePolitical science

Abstract

fetched live from OpenAlex

Family involvement is widely considered an important part of patient care in the intensive care unit. From professional health care organizations, government, and hospital associations, there has been a cultural shift toward family presence as part of a wider commitment to patient-centered care. At the same time, the meaning and impact of family involvement in the intensive care unit setting remain opaque and under-studied. This study employed an ethnographic approach to better understand family involvement in practice and from the perspective of health care professionals and family members by studying an implementation trial of a family involvement tool in two intensive care units over 2 years. The findings revealed that an expanded and self-defined role for family members as carers in the intensive care unit challenged the current configuration of the nurse patient/family relationship and that family members were aware of these dynamics. While the intensive care unit implementation teams were both motivated to implement a novel way of facilitating family involvement, the processual, organizational, and contextual factors in the intensive care units largely determined the possibilities of its application. This suggests that interventions should address the specific context in which they are employed.

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.001

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 head0.681
GPT teacher head0.643
Teacher spread0.038 · 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

Citations7
Published2024
Admission routes2
Has abstractyes

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