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Record W6926540164 · doi:10.25384/sage.c.6822925

Organizational Context and Quality Indicators in Nursing Homes: A Microsystem Look

2023· other· en· W6926540164 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicMarine Invertebrate Physiology and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Psychological interventionQuality (philosophy)Set (abstract data type)Nursing careNursing Interventions ClassificationQuality of life (healthcare)Minimum Data Set

Abstract

fetched live from OpenAlex

The association of organizational context with quality of care in nursing homes is not well understood at the clinical microsystem (care unit) level. This cross-sectional study examined the associations of unit-level context with 10 unit-level quality indicators derived from the Minimum Data Set 2.0. Study settings comprised 262 care units within 91 Canadian nursing homes. We assessed context using unit-aggregated care-aide-reported scores on the 10 scales of the Alberta Context Tool. Mixed-effects regression analysis showed that structural resources were negatively associated with antipsychotics use (B = −.06; <i>p</i> = .001) and worsened late-loss activities of daily living (B = −.03, <i>p</i> = .04). Organizational slack in time was negatively associated with worsened pain (B = −.04, <i>p</i> = .01). Social capital was positively associated with delirium symptoms (B = .12, <i>p</i> = .02) and worsened depressive symptoms (B = .10, <i>p</i> = .01). The findings suggested that targeting interventions to modifiable contextual elements and unit-level quality improvement will be promising.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.516
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0430.001

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 head0.037
GPT teacher head0.296
Teacher spread0.259 · 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 designObservational
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

Explore more

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