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CREATION AND CONTENT VALIDITY OF 5R-MEDSAFE: ASSESSING ADHERENCE TO THE SAFE DRUG ADMINISTRATION “FIVE RIGHTS”

2024· article· en· W4398768486 on OpenAlexaff
Rafaela Andolhe, Adriel Padilha, Edinêis de Brito Guirardello, Maria Cecília Bueno Jayme Gallani, Roberta Cunha Matheus Rodrigues

Bibliographic record

VenueTexto & Contexto - Enfermagem · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicReliability and Agreement in Measurement
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAdministration (probate law)Drug administrationContent validityDrugContent analysisContent (measure theory)Political scienceMedicinePsychologyNursingPharmacologySociologyLawSocial scienceHealth careMathematics

Abstract

fetched live from OpenAlex

ABSTRACT Objective: to present the creation and content validity stages of a questionnaire to assess the determinants of adherence to the safe drug administration five “rights” “x”, based on the Theory of Planned Behavior integrative model. Method: a methodological study to create and validate a self-reported measuring instrument for psychosocial variables. It took place in two public university teaching hospitals: one located in the South and the other in the Southeast of Brazil. Results: the results were organized according to each stage of the 5R-MEDSAFE content validation process. Conclusion: the results obtained in this creation and content validation study of the 5R-MEDSAFE indicated that the tool presented diverse content validity evidence. Its application can be useful in different contexts as a way of assessing adherence to these behaviors among Nursing workers. This will make it possible to identify which elements of the behaviors are amenable to intervention, as well as to implement the most appropriate intervention, according to the Theory of Planned Behavior constructs.

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)0.027
metaresearch head score (Gemma)0.053
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 score0.027
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.053
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.771
GPT teacher head0.541
Teacher spread0.230 · 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
Published2024
Admission routes1
Has abstractyes

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