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Record W2542813023 · doi:10.1177/084456211504700403

Developing a Web Site: A Strategy for Employment Integration of Internationally Educated Nurses

2015· article· en· W2542813023 on OpenAlexaffvenue

Bibliographic record

VenueCanadian Journal of Nursing Research · 2015
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster University
Fundersnot available
KeywordsPsychological interventionEconomic evaluationSpecialtyNursingRandomized controlled trialMedicineHealth carePsychologyFamily medicinePolitical scienceSurgery

Abstract

fetched live from OpenAlex

This review is focused on the effectiveness of nursing interventions for patient outcomes and healthcare costs. It was guided by ecological and economic evaluation frameworks. Restricting the first-tier search of over 4,000 articles to randomized controlled trials (RCTs) yielded 203 studies and 9 additional trials that used identical methods of cost evaluation. Of 212 RCTs, 37 met the eligibility criteria. Of the 37 articles, 29 came from the literature search and 8 came from the first author's research unit, which used identical methods of economic evaluation. Of the first 29 studies, 26 found that nurse interventions were more or equally effective and less or equally costly compared to usual care, as was true of 7 of the 9 RCTs with comprehensive economic evaluations. It is effective and efficient to deploy specialty-trained nurses to lead teams of professionals, including physicians, assembled to address complex patient needs. A nurse-led model of proactive and supplemental care for the chronically ill, versus the on-demand, physician-led model now in place, would be more or equally effective and less or equally costly.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.472
GPT teacher head0.609
Teacher spread0.137 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations6
Published2015
Admission routes2
Has abstractyes

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