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Record W2053367106 · doi:10.1097/nnd.0b013e31824b41a1

Quality of Work Life of Novice Nurses

2012· article· en· W2053367106 on OpenAlexaboutno aff
Victor Maddalena, Anne J. Kearney, Lisa G. Adams

Bibliographic record

VenueJournal for Nurses in Staff Development · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingStressorNursingPsychologyAffect (linguistics)Economic shortageQuality (philosophy)Work (physics)Health careOrientation (vector space)Personality psychologyApplied psychologyMedical educationMedicinePersonalitySocial psychologyClinical psychologyPolitical scienceGovernment (linguistics)

Abstract

fetched live from OpenAlex

In Brief This qualitative research study examines factors influencing the quality of work life of novice nurses (less than 2 years’ experience) in the Eastern Regional Health Authority in St. John’s, Newfoundland and Labrador, Canada. Although novice nurses are highly motivated to provide quality patient care, they encounter many sources of stress, including “difficult personalities,” inadequate orientation and mentoring, and horizontal violence from nursing and medical colleagues. These stressors are compounded by staffing shortages and heavy workloads. Supportive mentoring and adequate orientation are key factors to successful transition. In this article, the authors describe a study of novice nurses to determine sources of stress that may affect their transition into practice.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.138
GPT teacher head0.509
Teacher spread0.371 · 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 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

Citations15
Published2012
Admission routes1
Has abstractyes

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