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Record W2994676408 · doi:10.4037/aacnacc2019275

Role of Family Members in Pain Management in Adult Critical Care

2019· review· en· W2994676408 on OpenAlexaff
Émilie Gosselin, Mélissa Richard-Lalonde

Bibliographic record

VenueAACN Advanced Critical Care · 2019
Typereview
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsCINAHLMedicineMEDLINEPain assessmentPsychological interventionPain managementIntensive care unitNursingFamily medicinePhysical therapyIntensive care medicine

Abstract

fetched live from OpenAlex

This review describes family member involvement in intensive care unit pain assessment and management and generates implications for clinical practice, education, and future research. A literature review was performed in MEDLINE, PubMed, EMBASE, Cochrane, and CINAHL databases from their inception until April 30, 2019. Only 11 studies addressing the topic were identified, and the current quality of evidence is low. Family members can be involved in pain assessment by describing patients' pain behaviors and in pain management by selecting and delivering nonpharmacological interventions tailored to patients' needs, if the family members feel comfortable with this role. More-rigorous research is required to describe the role of family members in patients' pain assessment and management. Advancing knowledge in this field could improve patients' and family members' experiences with pain assessment and management in the intensive care unit.

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)0.000
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.844
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.032
GPT teacher head0.384
Teacher spread0.352 · 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 designOther design
Domainnot available
GenreReview

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

Citations10
Published2019
Admission routes1
Has abstractyes

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