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Record W4392813048 · doi:10.53555/sfs.v10i6.2253

Evaluation Of Nurses' Practice Related To Injection Safety

2023· article· en· W4392813048 on OpenAlexvenueno aff
Nawal faleh Humoud Albugami, Fawziah Faleh Humoud albugami, Haya faleh hamod albuqmi, Maha faleh al-bugomi, Alanood Khaleed Mohammed Alnfeai, Rawabi Saeed Abdullah Alqahtani

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldMedicine
TopicIntramuscular injections and effects
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessMedicine

Abstract

fetched live from OpenAlex

This study aims to evaluate nurses' practice related to injection safety in healthcare settings. Injection safety is crucial for preventing infections and ensuring patient safety. Assessing nurses' adherence to injection safety practices helps identify gaps and implement interventions for improvement. The study utilized a cross-sectional design, collecting data through questionnaires and direct observations. The sample consisted of nurses working in various clinical areas within the healthcare facility. Data analysis involved descriptive statistics and correlation analysis. The findings revealed both areas of strengths and weaknesses in nurses' practice related to injection safety. Recommendations were provided to enhance adherence to injection safety practices, including targeted education, improved availability of supplies, and creating a culture of safety within the organization. The study highlights the importance of ongoing evaluation and continuous improvement in injection safety practices among 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 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)0.017
metaresearch head score (Gemma)0.061
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.061
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.170
GPT teacher head0.385
Teacher spread0.215 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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Same venueJournal of Survey in Fisheries SciencesSame topicIntramuscular injections and effectsFrench-language works237,207