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Record W2952630109 · doi:10.12927/cjnl.2019.25849

Optimizing Licensed Practical Nurses in Home Care: Their Role, Scope and Opportunities

2019· article· en· W2952630109 on OpenAlexaffvenueabout
Kimberly D. Fraser, Neelam Saleem Punjani, Beth Wilkey, Susan Labonte, Sarah A. Lartey, Janine Gubersky, Kimberly Nickoriuk, Szjermae Joseph, Sarah Younus, John Miklavcic

Bibliographic record

VenueNursing leadership · 2019
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsInterior HealthAlberta HealthUniversity of AlbertaAlberta Health ServicesAthabasca University
Fundersnot available
KeywordsScope (computer science)Scope of practiceNursingCase managementData collectionFocus groupParticipant observationBusinessPsychologyKnowledge managementMedical educationProcess managementMedicineHealth careSociologyComputer sciencePolitical scienceMarketing

Abstract

fetched live from OpenAlex

This research examined the role and scope of licensed practical nurses (LPNs) in home care (HC) and case management. Case management is relatively new to LPNs in Alberta having been added to their list of competencies in 2015. The extent to which LPNs are performing functions and the circumstances or criteria that shape their reported case management functions and role are not clear. Our research questions were: a) What roles do LPNs play within HC and case management? and b) What roles could LPNs play within HC and case management given their scope of practice to achieve optimal client outcomes and system efficiencies? We used a mixed methods multiple case study design to engage LPNs in case management practice, their managers and HC leaders from rural, urban and suburban HC offices. Approaches for data collection included semi-structured interviews, participant observation, focus groups, document review and survey.

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)0.015
metaresearch head score (Gemma)0.025
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.003
Scholarly communication0.0040.003
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.271
GPT teacher head0.399
Teacher spread0.128 · 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

Citations2
Published2019
Admission routes3
Has abstractyes

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