MétaCan
Menu
Back to cohort
Record W6907369450 · doi:10.20381/ruor-30288

New Graduate Nurse Transition to Practice and Retention in Rural Settings: A Mixed Methods Study

2024· article· en· W6907369450 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Ottawa - Library · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsAgency (philosophy)Transition (genetics)Economic shortageJob embeddednessNursing practiceQualitative research

Abstract

fetched live from OpenAlex

Given the global shortage of nurses, New Graduate Nurses (NGN) play an integral role in ensuring a strong nursing workforce. However, retention of these nurses is problematic, especially in rural settings where there remains a gap in our understanding of this concept. The purpose of this master's study is to explore the transition to practice of NGNs and the factors that influence their retention in rural settings across Ontario using a mixed methods design. Utilizing the models of Job Embeddedness (Mitchell & Lee, 2001) and Transition Stages (Boychuk Duchscher, 2008), the results show the unique challenges that influence NGNs transition to practice in these settings such as the presence of higher role expectations and responsibilities, a lack of support during orientation and the difficulties associated with working amongst casual agency nurses. By contrast, a strong sense of belonging was identified as being an important facilitator. Les infirmières nouvellement diplômées (IND) jouent un rôle essentiel. Cependant, la rétention de ces infirmières est problématique, surtout en milieu rural où il reste des lacunes dans notre compréhension de la transition de celles-ci. Le but de cette étude de maîtrise est d'explorer la transition vers la pratique des IND et les facteurs qui influencent la rétention de celles-ci dans les milieux ruraux en Ontario à l’aide d’un devis de méthodes mixtes. En utilisant les modèles d'intégration de l'emploi (Mitchell et Lee, 2001) et d'étapes de transition (Boychuk Duchscher, 2008), les résultats décrivent les défis uniques qui agissent comme barrières à la transition des IND dans ces milieux, tels que des attentes et des responsabilités plus élevées de la part des IND, le manque de soutien lors de l'orientation initiale et les difficultés associées au travail avec les infirmières d'agence occasionnelles. Des facilitateurs de transition ont également été identifiés, telle qu’un fort sentiment d’appartenance.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.008
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.402
Teacher spread0.370 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Explore more

Same venueUniversity of Ottawa - LibrarySame topicGlobal Health Workforce IssuesFrench-language works237,207