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Record W2171425834 · doi:10.1111/jan.12837

Chasing the Mirage: a grounded theory of the clinical reasoning processes that Registered Nurses use to recognize delirium

2015· article· en· W2171425834 on OpenAlexaff
Mohamed El Hussein, Sandra P. Hirst

Bibliographic record

VenueJournal of Advanced Nursing · 2015
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity of CalgaryMount Royal University
Fundersnot available
KeywordsDeliriumGrounded theoryConstruct (python library)Intervention (counseling)PsychologyAcute careThinking processesNursingMedicinePsychiatryQualitative researchHealth careComputer science

Abstract

fetched live from OpenAlex

AIM: The aim of this study was to construct a grounded theory that explains the clinical reasoning processes that registered nurses use to recognize delirium in older adults in acute care hospitals. BACKGROUND: Delirium is under-recognized in acute hospital settings, this may stem from underdeveloped clinical reasoning processes. Little is known about registered nurses' (RNs) clinical reasoning processes in complex situations such as delirium recognition. DESIGN: A grounded theory approach was used to analyse interview data about the clinical reasoning processes of RNs in acute hospital settings. METHOD: Seventeen RNs were recruited. Concurrent data collection and comparative analysis and theoretical sampling were conducted in 2013-2014. FINDINGS: The core category to emerge from the data was 'chasing the mirage', which describes RNs' clinical reasoning processes to recognize delirium during their interaction with older adults. CONCLUSION: Understanding the reasoning that contributes to delirium under-recognition provides a strategy by which, this problem can be brought to the forefront of RNs' awareness and intervention. Delirium recognition will contribute to quality care for older adults.

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)0.097
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.097
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 head0.153
GPT teacher head0.408
Teacher spread0.255 · 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

Citations16
Published2015
Admission routes1
Has abstractyes

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