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Record W2228489021 · doi:10.3928/00989134-20080601-03

Caring for Hospitalized Older Adults at Risk for Delirium: The Silent, Unspoken Piece of Nursing Practice

2008· article· en· W2228489021 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Gerontological Nursing · 2008
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDeliriumContext (archaeology)Gerontological nursingNursingMedicinePsychological interventionPopulationNursing Interventions ClassificationQualitative researchMEDLINENursing careGerontologyPsychologyPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

More than half of hospitalized older adults will experience delirium, which--if left untreated--can lead to detrimental outcomes. Despite the prevalence and severity of delirium, nurses recognize less than one third of cases. Because little is known about how nurses manage this problem, a qualitative study was conducted to explore how nurses care for hospitalized older adults at risk for delirium. The data revealed that nurses care for older adults byTaking a Quick Look, Keeping an Eye on Them, and Controlling the Situation. The context in which nurses choose their priorities and interventions was reflected in the themes of the Care Environment and Negative Beliefs and Attitudes about older adults. Nurses are caring for an older population whose care requirements are different than those of younger people and in a context where this challenging work is rarely addressed. To improve care, the older population must be acknowledged, and nurses must possess the knowledge and resources needed to meet this population's unique needs.

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.

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)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.347
Teacher spread0.308 · 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