MétaCan
Menu
Back to cohort
Record W3159401660 · doi:10.5737/23688653-321917

Explicit recall related to mechanical ventilation: An evolutionary concept analysis

2020· article· en· W3159401660 on OpenAlexvenueno aff
Mylène Michaud, Marilou Gagnon

Bibliographic record

Venue˜The œCanadian journal of critical care nursing · 2020
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsRecallTerminologyVaguenessPhenomenonSedationCognitive psychologyAnxietyPsychologyModalitiesMechanical ventilationMedical terminologyIntensive care unitMedicineIntensive care medicineClinical psychologyAnesthesiaPsychiatryComputer scienceNursingEpistemologyArtificial intelligenceLinguistics

Abstract

fetched live from OpenAlex

Mechanical ventilation combined with sedation is widely used in the intensive care unit (ICU). However, this intervention is not without consequence on the patient. ICU patients can, in fact, remember perceptions that occurred during their mechanical ventilation—a phenomenon known as explicit recall. This phenomenon is not well defined, and no common terminology exists in the medical and nursing literature, where a variety of concepts are used interchangeably to describe the same experience. The goal of this concept analysis was to address the conceptual vagueness that surrounds explicit recall. Using Rodgers’ evolutionary approach, a total of 68 articles were analyzed to identify the concept’s antecedents, attributes, and consequences. The findings revealed that the explicit recall concept is perceptive, interpretative, subjective, dynamic, and temporal. It occurs following treatment that requires general anesthesia or sedation. It is also shaped by the modalities of anesthesia and sedation, as well as individual characteristics. Consequences of explicit recall can include anxiety, flashbacks, and post-traumatic stress disorder.

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)0.008
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0120.008
Science and technology studies0.0020.003
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0010.001
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 head0.332
Teacher spread0.300 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venue˜The œCanadian journal of critical care nursingSame topicIntensive Care Unit Cognitive DisordersFrench-language works237,207