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Record W2996846932 · doi:10.1097/nan.0000000000000351

Peripheral Venipuncture Education Strategies for Nursing Students

2019· review· en· W2996846932 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Infusion Nursing · 2019
Typereview
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of CalgaryWiLAN (Canada)
Fundersnot available
KeywordsVenipunctureCINAHLScopusMEDLINEMedical educationMedicineCochrane LibraryConstruct (python library)NursingComputer scienceAlternative medicineSurgeryPathology

Abstract

fetched live from OpenAlex

This integrative literature review identified strategies to teach peripheral venipuncture to nursing students. The following databases were searched for primary studies: Biblioteca Virtual em Saúde (BVS), PubMed, Web of Science, Education Resources Information Center (ERIC), SCOPUS, and Cumulative Index to Nursing and Allied Health Literature (CINAHL). The final sample was composed of 24 studies. The literature ranged from descriptive studies to controlled clinical trials and methodologic studies to construct products/instruments for teaching peripheral venipuncture. The most frequently identified teaching strategies were theoretical contents taught via theoretical lecture, e-learning courses, video lessons, and demonstration by specialists combined with practical exercises using a mannequin, human arms, and/or haptic devices. Despite the different methods used currently, the best patient outcomes were achieved when the student received the theoretical content in an educational setting before the practical training on a mannequin and/or a virtual simulator.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.101
GPT teacher head0.513
Teacher spread0.413 · 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