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Engaging health care workers in improving their work environment

2007· article· en· W2031175737 on OpenAlexaffabout
Louise Hamelin Brabant, Mélanie Lavoie‐Tremblay, Chantal Viens, Linda Lefrançois

Bibliographic record

VenueJournal of Nursing Management · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsHôpital Charles-Le MoyneMcGill UniversityUniversité Laval
Fundersnot available
KeywordsCitizen journalismHealth careWork (physics)NursingResistance (ecology)Participatory managementParticipatory action researchParticipatory evaluationLegitimacyPsychologyPublic relationsMedicineSociologyPolitical scienceSocial psychologyEngineering

Abstract

fetched live from OpenAlex

AIM: This study describes the perceptions of health care workers who were involved in a participatory approach for the reorganization of care and work, aimed at creating an optimum work environment. BACKGROUND: Quebec's health network has undertaken large-scale organizational changes to ensure the quality of health care and services for the population. METHOD: This participatory research was carried out by means of interviews. The sample consisted of 20 participants involved in the participatory approach for making changes to the organization of care and work in two pilot units. RESULTS: Four main perspectives emerged from the analysis: (1) views on the legitimacy of change, (2) commitment, indifference and resistance, (3) day-to-day concrete changes as signs of hope and (4) the elements of the success of the participatory approach. CONCLUSION: The management team's support and leadership and the participatory approach were significant factors in the success of the project.

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)0.013
metaresearch head score (Gemma)0.012
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 score0.013
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.004
Scholarly communication0.0030.001
Open science0.0010.006
Research integrity0.0020.001
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 head0.038
GPT teacher head0.380
Teacher spread0.342 · 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

Citations30
Published2007
Admission routes2
Has abstractyes

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