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Record W2519720054 · doi:10.1111/jonm.12417

Mandatory internal mobility in French hospitals: the results of imposed management practices

2016· article· en· W2519720054 on OpenAlexaff
Édith van Schingen, Odessa Petit dit Dariel, Hélène Lefebvre, Marie-Pierre Challier, Monique Rothan‐Tondeur

Bibliographic record

VenueJournal of Nursing Management · 2016
Typearticle
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsUniversité de MontréalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsNursing managementNursingUnit (ring theory)SpecialtyWork (physics)Service (business)MedicineProductivityEvent (particle physics)BusinessPsychologyFamily medicineMarketing

Abstract

fetched live from OpenAlex

AIM: To describe the impact of a mandatory internal mobility policy on nurses working in French state-funded health establishments. BACKGROUND: Public hospitals in France rely on the internal mobility of nursing staff to respond to organisational needs, to reduce costs and to increase productivity. However, there is very little data on the impact of such management practices on the nurses themselves. METHOD: A cross-sectional study, including 3077 nurses from 35 hospitals in the region of Paris, was conducted. Data were collected using a validated self-assessment questionnaire. RESULTS: Forty per cent of French nurses are required to work in different units. This mobility differs according to individual characteristics [age (P = 0.04), length of service (P = 0.017)] and type of environment [hospital (P < 0.0001), specialty (P < 0.0001)]. CONCLUSION: We can distinguish two types of approaches for implementing a mandatory staff nurse mobility policy. The first is an event that is regular, planned and lasts for several days. The second is an event that is irregular, short and organised the day before or the day of the change. Overall, while nurses are dissatisfied with all types of mandatory unit changes, this dissatisfaction is primarily a result of the irregular mobility events. IMPLICATIONS FOR NURSING MANAGEMENT: This study demonstrates the importance of implementing a planned inter-unit mobility event and proposes recommendations for this type of implementation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.348
Teacher spread0.321 · 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 designOther design
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

Citations10
Published2016
Admission routes1
Has abstractyes

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