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Record W2432618454 · doi:10.3912/ojin.vol18no01ppt01

Facilitating Change Among Nursing Assistants in Long Term Care

2012· article· en· W2432618454 on OpenAlexaffabout
François Aubry, Francis Etheridge, Yves Couturier

Bibliographic record

VenueOJIN The Online Journal of Issues in Nursing · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsNursingTeamworkWork (physics)Organizational changeProcess (computing)Nursing AssistantLong-term careTeam nursingMedicinePsychologyNurse educationNursing homesComputer sciencePublic relationsPolitical scienceEngineering

Abstract

fetched live from OpenAlex

In this article, the authors consider the implementation of change in long term care organizations (LTCOs) and present their study describing the process by which new nursing assistants are informally integrated into LTCOs in Quebec, Canada. The study method included 23 in-depth interviews with nursing assistants in two long term care centres. The findings enabled the authors to describe the informal process by which new nursing assistants are integrated into LTCOs and the manner in which informal work strategies enhance the work of nursing care, thus enabling the nursing assistants to manage heavy workloads. The authors discuss whether this teamwork is a deterrent to change or a lever for change and address issues regarding the collective structure of nursing assistant teams. Implications for practice include a Five-Step Innovation Plan. In conclusion, the authors propose that organizational change among nursing assistants in a LTCO is best accomplished when the leaders consider the nursing assistants' strong sense of community to be a change engine rather than a change obstacle.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.058
GPT teacher head0.469
Teacher spread0.410 · 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 designObservational
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

Citations12
Published2012
Admission routes2
Has abstractyes

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Same venueOJIN The Online Journal of Issues in NursingSame topicGeriatric Care and Nursing HomesFrench-language works237,207