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Record W4408933900 · doi:10.1177/23743735251330463

Direct Observation of Family Engagement Practice in a Cardiovascular Intensive Care Unit

2025· article· en· W4408933900 on OpenAlexaff
Jillian Kifell, Douglas Slobod, Krystina B. Lewis, Michael Goldfarb

Bibliographic record

VenueJournal of Patient Experience · 2025
Typearticle
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsJewish General HospitalUniversity of OttawaMcGill University Health CentreMcGill University
Fundersnot available
KeywordsPsychological interventionIntensive care unitMedicineFamily medicineFamily memberPsychologyNursingIntensive care medicine

Abstract

fetched live from OpenAlex

The purpose of this study was to describe family engagement practices in a cardiovascular intensive care unit (CVICU) and to explore their relationship with patient outcomes. Observations were conducted on 104 patients, with most (n = 61; 58%) having family members present. On average, 1.3 ± 0.6 family members were present per observation period per patient, spending 69% of the observation time at the bedside. The most common forms of family engagement included communication (n = 61; 100%), active family presence (n = 36; 59%), and direct contribution to care (n = 35; 57%). Patients with family present were 3 times less likely to be re-admitted to the hospital within 30 days compared to those without family present (5% vs 16%; P = .05). This study offers valuable insights through direct observations of family engagement practices in a CVICU setting, offering a foundational understanding of family engagement patterns and their associations with patient outcomes. These findings establish a basis for developing targeted interventions, policies, and training programs aimed at enhancing family engagement and improving outcomes for both patients and their families in critical care settings.

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)0.001
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.129
GPT teacher head0.421
Teacher spread0.293 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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