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Record W4392381405 · doi:10.1097/nhh.0000000000001241

New Graduate Nurse Transition into Rural Home

2024· article· en· W4392381405 on OpenAlexaff
Laurie Generous

Bibliographic record

VenueHome Healthcare Now · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsIsland Health
Fundersnot available
KeywordsMentorshipNursingAttritionContext (archaeology)MedicineAcute careMedical educationPolitical scienceHealth care

Abstract

fetched live from OpenAlex

The global shortage of nurses and high attrition rates for newly graduated nurses along with the shifting demand for home care has created a critical need for retention strategies that address the specific challenges of rural settings. The effectiveness of structured transition or mentoring programs are primarily studied in acute care settings, making it difficult to translate to the unique context of rural home care nursing. The complexities of the independent nature of home care nursing practice and limited resources to address transition shock make it difficult to successfully transition newly graduated nurses to rural home care. A case study supports mentorship facilitation as a readily available, effective strategy that can overcome the challenges of rural home care settings. A comparative analysis will link Duchscher's (2008) transition shock theory to mentorship as an effective strategy for supporting NGNs' transition in home care nursing. Recommendations offer rural care leaders practical strategies bundled with mentorship to optimize the successful transition and retention of newly graduated nurses in their workplaces.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.008

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 head0.057
GPT teacher head0.441
Teacher spread0.384 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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