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Record W2607238498 · doi:10.5430/jnep.v7n9p78

Nurses’ professional values on patient care provisions and decisions

2017· article· en· W2607238498 on OpenAlexvenueno aff
Farhan Al Shammari, Rizal Angelo N. Grande, Daisy A. Vicencio, Saud Al Mutairi

Bibliographic record

VenueJournal of Nursing Education and Practice · 2017
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupGovernment (linguistics)Value (mathematics)Educational attainmentUnit (ring theory)NursingDescriptive statisticsPsychologyPosition (finance)Rank (graph theory)Family medicinePatient careDescriptive researchMedicinePolitical scienceSociologyBusiness

Abstract

fetched live from OpenAlex

Objective: To determine the relationship of professional value system of nurses to their duties and functions specifically on patient care provisions and decisions among selected government hospitals in Hail city, Kingdom of Saudi Arabia.Methods: The study utilized a Descriptive Correlational method of research inquiry where a 26-item questionnaire on nurse professional value system (NPVSR) were distributed to 150 staff nurses employed in 3 government hospitals in the City of Hail after which, their responses were correlated using Pearson r against their demographic profiles such as gender, age, religion, ethnicity, educational attainment, years of practice, current unit or ward assignment and current rank or position.Results: Based on the responses of the 150 participants, the results showed that there was no significant relationship that exists between their demographic profiles to their value systems on different patient care provisions and decisions during their clinical duties and employment as staff nurses.Conclusions: The study implicated that the value systems of the participants are not dependent or influenced largely or directly by their gender, age, religion, ethnicity, years of practice, educational attainment, current ward or unit assignment and current rank or position. The data further revealed that for this specific group of participants, their professional value system may in some other ways influenced by other factors not mentioned or included in their demographic profiles for the study.

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)0.004
metaresearch head score (Gemma)0.125
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.125
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.003
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 head0.226
GPT teacher head0.634
Teacher spread0.408 · 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.

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

Citations14
Published2017
Admission routes1
Has abstractyes

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