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Record W2018457651 · doi:10.1177/1054773811431491

The Contribution Falls Have to Increasing Risk of Nursing Home Placement in Community-Dwelling Older Adults

2011· article· en· W2018457651 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

VenueClinical Nursing Research · 2011
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsCentre for Family Medicine
FundersNational Institute of Nursing Research
KeywordsNursing homesGerontologyNursingHuman factors and ergonomicsSuicide preventionMedicineInjury preventionAging in placePoison controlPsychologyEnvironmental health

Abstract

fetched live from OpenAlex

PURPOSE: To determine whether a fall, as an adverse event in combination with other risk factors, influences nursing home placement (NHP). METHOD: A retrospective longitudinal study of 6,515 high-risk, community-dwelling, dually eligible (Medicare/Medicaid) participants in a waiver program during 2002-2007 are examined. Data are obtained from the Minimum Data Set-Home Care linked with Medicaid claim files. The authors fit multiple factors to a logistic curve, using generalized linear modeling to predict increased risk of NHP when a fall occurred. RESULTS: Prior NHP and an increased rate of falls (Odds Ratio [OR] = 1.52, 95% Confidence Interval [CI] = 1.25-1.84) and prior NHP and the same rate of falls (OR = 1.55, 95% CI = 1.26-1.91) both increased NHP. CONCLUSION: An adverse event such as a fall and prior NHP is a strong predictor of future NHP and should be taken into consideration while developing care plans for community-dwelling 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.

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)0.033
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.005
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 head0.223
GPT teacher head0.554
Teacher spread0.331 · 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