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Record W2092888377 · doi:10.3917/rsi.118.0085

Les difficultés/souffrances vécues par les infirmières : stratégies permettant de préserver leur santé mentale, leur sens au travail et leur performance au travail

2014· article· fr· W2092888377 on OpenAlexaff
Camille Boivin-Desrochers, Marie Alderson

Bibliographic record

VenueRecherche en soins infirmiers · 2014
Typearticle
Languagefr
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMental healthContext (archaeology)PsychologyNursingWork (physics)Mental health careMedicinePsychiatry

Abstract

fetched live from OpenAlex

The nursing profession is faced with an issue of growing concern, that of the mental health of its practitioners. The many difficulties that nurses experience in the workplace may prove to be detrimental to the maintenance of an optimal mental state. With respect to these difficulties, several strategies can be implemented and used by nurses and managers. The present literature review aims to identify the difficulties and suffering experienced by nurses and the strategies employed to ensure the preservation of mental health, as well as maintaining the calling of the profession and job performance. It also aims to provide nurses and managers of the health care system with ideas to promote optimal mental health for nurses. In this context, « psychodynamique du travail » was chosen as the framework to structure the analysis of the literature dealing with elements surrounding the suffering and difficulties experienced by nurses. The use of this theoretical framework deepens and supports the relationship between the suffering experienced at work and the mental health of nurses.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.132
GPT teacher head0.437
Teacher spread0.305 · 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 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

Citations10
Published2014
Admission routes1
Has abstractyes

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